From 6b541109c9a8ab84392e35a8813e0310632af93a Mon Sep 17 00:00:00 2001 From: Hakeem Kazeem Date: Wed, 13 Dec 2023 18:36:46 +0100 Subject: [PATCH 01/16] gather nd operator --- src/operators/tensor/core.cairo | 3 + .../tensor/implementations/tensor_bool.cairo | 4 + .../implementations/tensor_fp16x16.cairo | 4 + .../implementations/tensor_fp16x16wide.cairo | 4 + .../implementations/tensor_fp32x32.cairo | 4 + .../implementations/tensor_fp64x64.cairo | 4 + .../implementations/tensor_fp8x23.cairo | 4 + .../implementations/tensor_fp8x23wide.cairo | 4 + .../tensor/implementations/tensor_i32.cairo | 4 + .../tensor/implementations/tensor_i8.cairo | 4 + .../tensor/implementations/tensor_u32.cairo | 4 + src/operators/tensor/math.cairo | 1 + src/operators/tensor/math/gather_nd.cairo | 385 ++++ tests/nodes.cairo | 1644 ++++++++--------- 14 files changed, 1251 insertions(+), 822 deletions(-) create mode 100644 src/operators/tensor/math/gather_nd.cairo diff --git a/src/operators/tensor/core.cairo b/src/operators/tensor/core.cairo index 75f90224f..0c01c476d 100644 --- a/src/operators/tensor/core.cairo +++ b/src/operators/tensor/core.cairo @@ -121,6 +121,7 @@ impl TensorSerde, impl TDrop: Drop> of Serde { /// # tensor.new /// @@ -4853,6 +4854,8 @@ trait TensorTrait { /// ``` /// fn not(self: @Tensor) -> Tensor; + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor; } /// Cf: TensorTrait::new docstring diff --git a/src/operators/tensor/implementations/tensor_bool.cairo b/src/operators/tensor/implementations/tensor_bool.cairo index c0a8d1ceb..9465a4e2d 100644 --- a/src/operators/tensor/implementations/tensor_bool.cairo +++ b/src/operators/tensor/implementations/tensor_bool.cairo @@ -451,6 +451,10 @@ impl BoolTensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { panic(array!['not supported!']) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements partial equal for two `Tensor` using the `PartialEq` trait. diff --git a/src/operators/tensor/implementations/tensor_fp16x16.cairo b/src/operators/tensor/implementations/tensor_fp16x16.cairo index dee654729..f1da6f491 100644 --- a/src/operators/tensor/implementations/tensor_fp16x16.cairo +++ b/src/operators/tensor/implementations/tensor_fp16x16.cairo @@ -512,6 +512,10 @@ impl FP16x16Tensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_fp16x16wide.cairo b/src/operators/tensor/implementations/tensor_fp16x16wide.cairo index 2f89df88b..2f4996dab 100644 --- a/src/operators/tensor/implementations/tensor_fp16x16wide.cairo +++ b/src/operators/tensor/implementations/tensor_fp16x16wide.cairo @@ -478,6 +478,10 @@ impl FP16x16WTensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_fp32x32.cairo b/src/operators/tensor/implementations/tensor_fp32x32.cairo index 7517ef7cd..6556e9665 100644 --- a/src/operators/tensor/implementations/tensor_fp32x32.cairo +++ b/src/operators/tensor/implementations/tensor_fp32x32.cairo @@ -513,6 +513,10 @@ impl FP32x32Tensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_fp64x64.cairo b/src/operators/tensor/implementations/tensor_fp64x64.cairo index d4c7e0a2b..410df21e7 100644 --- a/src/operators/tensor/implementations/tensor_fp64x64.cairo +++ b/src/operators/tensor/implementations/tensor_fp64x64.cairo @@ -514,6 +514,10 @@ impl FP64x64Tensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_fp8x23.cairo b/src/operators/tensor/implementations/tensor_fp8x23.cairo index 1f10a73a5..19f7985f4 100644 --- a/src/operators/tensor/implementations/tensor_fp8x23.cairo +++ b/src/operators/tensor/implementations/tensor_fp8x23.cairo @@ -512,6 +512,10 @@ impl FP8x23Tensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_fp8x23wide.cairo b/src/operators/tensor/implementations/tensor_fp8x23wide.cairo index fc820222d..a6e0cb25d 100644 --- a/src/operators/tensor/implementations/tensor_fp8x23wide.cairo +++ b/src/operators/tensor/implementations/tensor_fp8x23wide.cairo @@ -465,6 +465,10 @@ impl FP8x23WTensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_i32.cairo b/src/operators/tensor/implementations/tensor_i32.cairo index 106daa208..724c547f6 100644 --- a/src/operators/tensor/implementations/tensor_i32.cairo +++ b/src/operators/tensor/implementations/tensor_i32.cairo @@ -507,6 +507,10 @@ impl I32Tensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_i8.cairo b/src/operators/tensor/implementations/tensor_i8.cairo index d9bb40cb1..2604cbd55 100644 --- a/src/operators/tensor/implementations/tensor_i8.cairo +++ b/src/operators/tensor/implementations/tensor_i8.cairo @@ -507,6 +507,10 @@ impl I8Tensor of TensorTrait { fn concat_from_sequence(sequence: Array>, axis: i32, new_axis: Option) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/implementations/tensor_u32.cairo b/src/operators/tensor/implementations/tensor_u32.cairo index 288c834e9..ed318fc72 100644 --- a/src/operators/tensor/implementations/tensor_u32.cairo +++ b/src/operators/tensor/implementations/tensor_u32.cairo @@ -456,6 +456,10 @@ impl U32Tensor of TensorTrait { ) -> Tensor { math::concat_from_sequence::concat_from_sequence(sequence, axis, new_axis) } + + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor { + math::gather_nd::gather_nd(self, indices, batch_dims) + } } /// Implements addition for `Tensor` using the `Add` trait. diff --git a/src/operators/tensor/math.cairo b/src/operators/tensor/math.cairo index d5a74322c..cd440aa41 100644 --- a/src/operators/tensor/math.cairo +++ b/src/operators/tensor/math.cairo @@ -62,3 +62,4 @@ mod sequence_insert; mod concat_from_sequence; mod is_nan; mod is_inf; +mod gather_nd; \ No newline at end of file diff --git a/src/operators/tensor/math/gather_nd.cairo b/src/operators/tensor/math/gather_nd.cairo new file mode 100644 index 000000000..93c56b402 --- /dev/null +++ b/src/operators/tensor/math/gather_nd.cairo @@ -0,0 +1,385 @@ +use alexandria_data_structures::array_ext::SpanTraitExt; +use array::ArrayTrait; +use array::SpanTrait; + +use core::traits::Into; +use debug::PrintTrait; +use core::traits::TryInto; +use core::serde::Serde; +use core::traits::Destruct; +use option::OptionTrait; + +use orion::numbers::NumberTrait; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor}; + +/// Cf: TensorTrait::gather docstring +fn gather_nd< + T, + impl TTensorTrait: TensorTrait, + impl TCopy: Copy, + impl TDrop: Drop, +>( + self: @Tensor, indices: Tensor, batch_dims: Option +) -> Tensor { + let batch_dims = match batch_dims { + Option::Some(val) => val, + Option::None(_) => 0 + }; + + let data_rank = (*self.shape).len(); + let indices_rank = (indices.shape).len(); + assert((data_rank >= 1 ) & (indices_rank >= 1), 'rank must > 1'); + + let mut data_shape = *self.shape; + let mut indices_shape = indices.shape; + let mut data_shape_clone = data_shape.clone(); + let mut indices_shape_clone = indices_shape.clone(); + + let indices_shape_last = indices_shape_clone.pop_back().unwrap(); + assert((*indices_shape_last >= 1) & (*indices_shape_last <= data_rank-batch_dims), 'check indices'); + + let mut batch_dims_shape = ArrayTrait::new(); + let mut output_shape = ArrayTrait::new(); + let mut index_data = ArrayTrait::new(); + let mut output_data = ArrayTrait::new(); + + let mut batch_dims_size = batch_dims; + let mut total_data_len = 1; + let mut multiple_data_len = ArrayTrait::new(); + + let mut ind = 0; + loop { + if (ind == batch_dims) { + break(); + } + match indices_shape_clone.pop_front() { + Option::Some(val) => { + batch_dims_size *= *val; + batch_dims_shape.append(*val); + ind += 1; + }, + Option::None(_) => { break; } + }; + }; + + loop { + match indices_shape_clone.pop_front() { + Option::Some(val) => { + batch_dims_shape.append(*val); + }, + Option::None(_) => { break; } + }; + }; + + if (*indices_shape_last == data_rank - batch_dims) { + output_shape = batch_dims_shape; + } + else { + let mut ind = 0; + let mut multiple = 1; + output_shape = batch_dims_shape; + loop { + match data_shape_clone.pop_front() { + Option::Some(val) => { + if (ind >= (batch_dims + *indices_shape_last)) { + output_shape.append(*val); + } + // total_data_len *= *val; + ind += 1; + }, + Option::None(_) => { break; } + }; + }; + } + + let mut ind = 0; + let mut multiple = 1; + let mut data_shape_clone = data_shape.clone(); + loop { + match data_shape_clone.pop_front() { + Option::Some(val) => { + if (ind >= batch_dims) { + multiple *= *val; + multiple_data_len.append(multiple); + } + ind += 1; + }, + Option::None(_) => { break; } + }; + }; + + let mut ind = 0; + let mut incrementer = 1; + let mut data_shape_clone = data_shape.clone(); + loop { + match data_shape_clone.pop_front() { + Option::Some(val) => { + if (ind >= batch_dims + *indices_shape_last) { + incrementer *= *val; + } + ind += 1; + }, + Option::None(_) => { break; } + }; + }; + + + let mut ind = 0; + let mut indices_shape_clone = indices_shape.clone(); + let mut breaker = 1; + loop { + match indices_shape_clone.pop_front() { + Option::Some(val) => { + if (ind >= batch_dims) { + breaker *= *val; + } + ind += 1; + }, + Option::None(_) => { break; } + }; + }; + + let data_shape_last = data_shape.pop_back().unwrap(); + + total_data_len = *multiple_data_len.at(multiple_data_len.len() - 1); + let mut data_indices = indices.data; + let mut ind = 0; + let mut result = 0; + let mut outer_loop = 0; + + loop { + match data_indices.pop_front() { + Option::Some(val) => { + let index = ind % *indices_shape_last; + let incr= total_data_len * (ind / breaker); + result += (*val * total_data_len / *multiple_data_len.at(index)); + ind += 1; + + if (index == *indices_shape_last-1) { + let mut data_ind:usize = result ; + loop { + if data_ind == result + incrementer { break; } + index_data.append(data_ind + incr); + data_ind+=1; + }; + result = 0; + }; + }, + Option::None(_) => { break; } + }; + }; + + + loop { + match index_data.pop_front() { + Option::Some(val) => { + output_data.append(*self.data[val]); + }, + Option::None(_) => { break; } + }; + }; + + let mut output_tensor = TensorTrait::::new(output_shape.span(), output_data.span()); + + // let mut output_tensor = TensorTrait::::new(*self.shape, *self.data); + return output_tensor; +} + + +// Tests-------------------------------------------------------------------------------------------------------------- + + +use orion::utils::assert_eq; + + +fn indices() -> Tensor { + let mut sizes = ArrayTrait::new(); + sizes.append(4); + sizes.append(1); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + let tensor = TensorTrait::::new(sizes.span(), data.span()); + + return tensor; +} + +fn indices1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(2); + data.append(1); + data.append(0); + data.append(1); + data.append(2); + data.append(0); + data.append(1); + + TensorTrait::new(shape.span(), data.span()) +} + +fn data() -> Tensor { + let mut sizes = ArrayTrait::new(); + sizes.append(2); + sizes.append(2); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + let tensor = TensorTrait::::new(sizes.span(), data.span()); + + return tensor; +} + +fn data1() -> Tensor { + let mut sizes = ArrayTrait::new(); + sizes.append(3); + sizes.append(3); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + + + let tensor = TensorTrait::::new(sizes.span(), data.span()); + + return tensor; +} + +fn u32_tensor_3x3x3_helper() -> Tensor { + let mut sizes = ArrayTrait::new(); + sizes.append(2); + sizes.append(3); + sizes.append(2); + sizes.append(4); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(24); + data.append(25); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + data.append(26); + + let tensor = TensorTrait::::new(sizes.span(), data.span()); + + return tensor; +} + +fn indices_333() -> Tensor { + let mut sizes = ArrayTrait::new(); + sizes.append(2); + sizes.append(3); + sizes.append(1); + sizes.append(3); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(0); + data.append(0); + + data.append(0); + data.append(0); + data.append(1); + + data.append(1); + data.append(0); + data.append(1); + + data.append(0); + data.append(0); + data.append(1); + + data.append(0); + data.append(0); + data.append(0); + + data.append(0); + data.append(1); + data.append(1); + + let tensor = TensorTrait::::new(sizes.span(), data.span()); + + return tensor; +} + + +#[test] +#[available_gas(20000000000)] +fn test_gather_elements_default() { + let data = u32_tensor_3x3x3_helper(); + let indices = indices_333(); + + let y = data.gather_nd(indices: indices, batch_dims:Option::Some(1)); + let mut output = y.data; + + loop { + match output.pop_front() { + Option::Some(val) => { + (*val).print(); + }, + Option::None(_) => { break; } + }; + }; + +} \ No newline at end of file diff --git a/tests/nodes.cairo b/tests/nodes.cairo index 12bc31c9b..b2371a071 100644 --- a/tests/nodes.cairo +++ b/tests/nodes.cairo @@ -1,822 +1,822 @@ -mod abs_fp16x16; -mod abs_fp8x23; -mod abs_i32; -mod abs_i8; -mod acos_fp16x16; -mod acos_fp8x23; -mod acosh_fp16x16; -mod acosh_fp8x23; -mod add_fp16x16; -mod add_fp16x16_broadcast; -mod add_fp8x23; -mod add_fp8x23_broadcast; -mod add_i32; -mod add_i32_broadcast; -mod add_i8; -mod add_i8_broadcast; -mod add_u32; -mod add_u32_broadcast; -mod argmax_fp16x16_1D_default; -mod argmax_fp16x16_1D_keepdims_false; -mod argmax_fp16x16_1D_last_index; -mod argmax_fp16x16_2D_default; -mod argmax_fp16x16_2D_keepdims_false; -mod argmax_fp16x16_2D_last_index; -mod argmax_fp16x16_3D_default; -mod argmax_fp16x16_3D_keepdims_false; -mod argmax_fp16x16_3D_last_index; -mod argmax_fp8x23_1D_default; -mod argmax_fp8x23_1D_keepdims_false; -mod argmax_fp8x23_1D_last_index; -mod argmax_fp8x23_2D_default; -mod argmax_fp8x23_2D_keepdims_false; -mod argmax_fp8x23_2D_last_index; -mod argmax_fp8x23_3D_default; -mod argmax_fp8x23_3D_keepdims_false; -mod argmax_fp8x23_3D_last_index; -mod argmax_i32_1D_default; -mod argmax_i32_1D_keepdims_false; -mod argmax_i32_1D_last_index; -mod argmax_i32_2D_default; -mod argmax_i32_2D_keepdims_false; -mod argmax_i32_2D_last_index; -mod argmax_i32_3D_default; -mod argmax_i32_3D_keepdims_false; -mod argmax_i32_3D_last_index; -mod argmax_i8_1D_default; -mod argmax_i8_1D_keepdims_false; -mod argmax_i8_1D_last_index; -mod argmax_i8_2D_default; -mod argmax_i8_2D_keepdims_false; -mod argmax_i8_2D_last_index; -mod argmax_i8_3D_default; -mod argmax_i8_3D_keepdims_false; -mod argmax_i8_3D_last_index; -mod argmax_u32_1D_default; -mod argmax_u32_1D_keepdims_false; -mod argmax_u32_1D_last_index; -mod argmax_u32_2D_default; -mod argmax_u32_2D_keepdims_false; -mod argmax_u32_2D_last_index; -mod argmax_u32_3D_default; -mod argmax_u32_3D_keepdims_false; -mod argmax_u32_3D_last_index; -mod argmin_fp16x16_1D_default; -mod argmin_fp16x16_1D_keepdims_false; -mod argmin_fp16x16_1D_last_index; -mod argmin_fp16x16_2D_default; -mod argmin_fp16x16_2D_keepdims_false; -mod argmin_fp16x16_2D_last_index; -mod argmin_fp16x16_3D_default; -mod argmin_fp16x16_3D_keepdims_false; -mod argmin_fp16x16_3D_last_index; -mod argmin_fp8x23_1D_default; -mod argmin_fp8x23_1D_keepdims_false; -mod argmin_fp8x23_1D_last_index; -mod argmin_fp8x23_2D_default; -mod argmin_fp8x23_2D_keepdims_false; -mod argmin_fp8x23_2D_last_index; -mod argmin_fp8x23_3D_default; -mod argmin_fp8x23_3D_keepdims_false; -mod argmin_fp8x23_3D_last_index; -mod argmin_i32_1D_default; -mod argmin_i32_1D_keepdims_false; -mod argmin_i32_1D_last_index; -mod argmin_i32_2D_default; -mod argmin_i32_2D_keepdims_false; -mod argmin_i32_2D_last_index; -mod argmin_i32_3D_default; -mod argmin_i32_3D_keepdims_false; -mod argmin_i32_3D_last_index; -mod argmin_i8_1D_default; -mod argmin_i8_1D_keepdims_false; -mod argmin_i8_1D_last_index; -mod argmin_i8_2D_default; -mod argmin_i8_2D_keepdims_false; -mod argmin_i8_2D_last_index; -mod argmin_i8_3D_default; -mod argmin_i8_3D_keepdims_false; -mod argmin_i8_3D_last_index; -mod argmin_u32_1D_default; -mod argmin_u32_1D_keepdims_false; -mod argmin_u32_1D_last_index; -mod argmin_u32_2D_default; -mod argmin_u32_2D_keepdims_false; -mod argmin_u32_2D_last_index; -mod argmin_u32_3D_default; -mod argmin_u32_3D_keepdims_false; -mod argmin_u32_3D_last_index; -mod asin_fp16x16; -mod asin_fp8x23; -mod asinh_fp16x16; -mod asinh_fp8x23; -mod atan_fp16x16; -mod atan_fp8x23; -mod ceil_fp16x16; -mod ceil_fp8x23; -mod concat_fp16x16_1d; -mod concat_fp16x16_2d; -mod concat_fp16x16_3d_default; -mod concat_fp16x16_3d_axis_1; -mod concat_fp16x16_3d_axis_2; -mod concat_fp16x16_3d_three_tensors_axis_1; -mod concat_fp16x16_3d_three_tensors_axis_2; -mod concat_fp8x23_1d; -mod concat_fp8x23_2d; -mod concat_fp8x23_3d_default; -mod concat_fp8x23_3d_axis_1; -mod concat_fp8x23_3d_axis_2; -mod concat_fp8x23_3d_three_tensors_axis_1; -mod concat_fp8x23_3d_three_tensors_axis_2; -mod concat_i32_1d; -mod concat_i32_2d; -mod concat_i32_3d_default; -mod concat_i32_3d_axis_1; -mod concat_i32_3d_axis_2; -mod concat_i32_3d_three_tensors_axis_1; -mod concat_i32_3d_three_tensors_axis_2; -mod concat_i8_1d; -mod concat_i8_2d; -mod concat_i8_3d_default; -mod concat_i8_3d_axis_1; -mod concat_i8_3d_axis_2; -mod concat_i8_3d_three_tensors_axis_1; -mod concat_i8_3d_three_tensors_axis_2; -mod concat_u32_1d; -mod concat_u32_2d; -mod concat_u32_3d_default; -mod concat_u32_3d_axis_1; -mod concat_u32_3d_axis_2; -mod concat_u32_3d_three_tensors_axis_1; -mod concat_u32_3d_three_tensors_axis_2; -mod cos_fp16x16; -mod cos_fp8x23; -mod cosh_fp16x16; -mod cosh_fp8x23; -mod cumsum_fp16x16_1d_default; -mod cumsum_fp16x16_1d_exclusive; -mod cumsum_fp16x16_1d_reverse; -mod cumsum_fp16x16_1d_reverse_exclusive; -mod cumsum_fp16x16_2d_axis_0; -mod cumsum_fp16x16_2d_axis_1; -mod cumsum_fp8x23_1d_default; -mod cumsum_fp8x23_1d_exclusive; -mod cumsum_fp8x23_1d_reverse; -mod cumsum_fp8x23_1d_reverse_exclusive; -mod cumsum_fp8x23_2d_axis_0; -mod cumsum_fp8x23_2d_axis_1; -mod cumsum_i32_1d_default; -mod cumsum_i32_1d_exclusive; -mod cumsum_i32_1d_reverse; -mod cumsum_i32_1d_reverse_exclusive; -mod cumsum_i32_2d_axis_0; -mod cumsum_i32_2d_axis_1; -mod cumsum_i8_1d_default; -mod cumsum_i8_1d_exclusive; -mod cumsum_i8_1d_reverse; -mod cumsum_i8_1d_reverse_exclusive; -mod cumsum_i8_2d_axis_0; -mod cumsum_i8_2d_axis_1; -mod cumsum_u32_1d_default; -mod cumsum_u32_1d_exclusive; -mod cumsum_u32_1d_reverse; -mod cumsum_u32_1d_reverse_exclusive; -mod cumsum_u32_2d_axis_0; -mod cumsum_u32_2d_axis_1; -mod div_fp16x16; -mod div_fp16x16_broadcast; -mod div_fp8x23; -mod div_fp8x23_broadcast; -mod div_i32; -mod div_i32_broadcast; -mod div_i8; -mod div_i8_broadcast; -mod div_u32; -mod div_u32_broadcast; -mod equal_fp16x16; -mod equal_fp16x16_broadcast; -mod equal_fp8x23; -mod equal_fp8x23_broadcast; -mod equal_i32; -mod equal_i32_broadcast; -mod equal_i8; -mod equal_i8_broadcast; -mod equal_u32; -mod equal_u32_broadcast; -mod exp_fp16x16; -mod exp_fp8x23; -mod less_equal_fp16x16; -mod less_equal_fp16x16_broadcast; -mod less_equal_fp8x23; -mod less_equal_fp8x23_broadcast; -mod less_equal_i32; -mod less_equal_i32_broadcast; -mod less_equal_i8; -mod less_equal_i8_broadcast; -mod less_equal_u32; -mod less_equal_u32_broadcast; -mod greater_fp16x16; -mod greater_fp16x16_broadcast; -mod greater_fp8x23; -mod greater_fp8x23_broadcast; -mod greater_i32; -mod greater_i32_broadcast; -mod greater_i8; -mod greater_i8_broadcast; -mod greater_u32; -mod greater_u32_broadcast; -mod leaky_relu_fp16x16; -mod leaky_relu_fp8x23; -mod linear_fp16x16; -mod linear_fp8x23; -mod linear_i32; -mod linear_i8; -mod linear_u32; -mod log_fp16x16; -mod log_fp8x23; -mod logsoftmax_fp16x16_axis_0; -mod logsoftmax_fp16x16_axis_1; -mod logsoftmax_fp8x23_axis_0; -mod logsoftmax_fp8x23_axis_1; -mod matmul_fp16x16_1d; -mod matmul_fp16x16_2x2; -mod matmul_fp16x16_2x1; -mod matmul_fp16x16_1x2; -mod matmul_fp8x23_1d; -mod matmul_fp8x23_2x2; -mod matmul_fp8x23_2x1; -mod matmul_fp8x23_1x2; -mod matmul_i32_1d; -mod matmul_i32_2x2; -mod matmul_i32_2x1; -mod matmul_i32_1x2; -mod matmul_i8_1d; -mod matmul_i8_2x2; -mod matmul_i8_2x1; -mod matmul_i8_1x2; -mod matmul_u32_1d; -mod matmul_u32_2x2; -mod matmul_u32_2x1; -mod matmul_u32_1x2; -mod mul_fp16x16; -mod mul_fp16x16_broadcast; -mod mul_fp8x23; -mod mul_fp8x23_broadcast; -mod mul_i32; -mod mul_i32_broadcast; -mod mul_i8; -mod mul_i8_broadcast; -mod mul_u32; -mod mul_u32_broadcast; -mod or_fp16x16; -mod or_fp16x16_broadcast; -mod or_fp8x23; -mod or_fp8x23_broadcast; -mod or_i32; -mod or_i32_broadcast; -mod or_i8; -mod or_i8_broadcast; -mod or_u32; -mod or_u32_broadcast; -mod reduce_sum_fp16x16_1D; -mod reduce_sum_fp16x16_2D_default; -mod reduce_sum_fp16x16_2D_keepdims; -mod reduce_sum_fp16x16_2D_axis_1; -mod reduce_sum_fp8x23_1D; -mod reduce_sum_fp8x23_2D_default; -mod reduce_sum_fp8x23_2D_keepdims; -mod reduce_sum_fp8x23_2D_axis_1; -mod reduce_sum_i32_1D; -mod reduce_sum_i32_2D_default; -mod reduce_sum_i32_2D_keepdims; -mod reduce_sum_i32_2D_axis_1; -mod reduce_sum_i8_1D; -mod reduce_sum_i8_2D_default; -mod reduce_sum_i8_2D_keepdims; -mod reduce_sum_i8_2D_axis_1; -mod reduce_sum_u32_1D; -mod reduce_sum_u32_2D_default; -mod reduce_sum_u32_2D_keepdims; -mod reduce_sum_u32_2D_axis_1; -mod relu_fp16x16; -mod relu_fp8x23; -mod relu_i32; -mod relu_i8; -mod sigmoid_fp16x16; -mod sigmoid_fp8x23; -mod sin_fp16x16; -mod sin_fp8x23; -mod sinh_fp16x16; -mod sinh_fp8x23; -mod softmax_fp16x16; -mod softmax_fp8x23; -mod softplus_fp8x23; -mod softplus_fp16x16; -mod softsign_fp8x23; -mod softsign_fp16x16; -mod sqrt_fp16x16; -mod sqrt_fp8x23; -mod sub_fp16x16; -mod sub_fp16x16_broadcast; -mod sub_fp8x23; -mod sub_fp8x23_broadcast; -mod sub_i32; -mod sub_i32_broadcast; -mod sub_i8; -mod sub_i8_broadcast; -mod sub_u32; -mod sub_u32_broadcast; -mod tanh_fp16x16; -mod tanh_fp8x23; -mod transpose_fp16x16_2d; -mod transpose_fp16x16_3d; -mod transpose_fp8x23_2d; -mod transpose_fp8x23_3d; -mod transpose_i32_2d; -mod transpose_i32_3d; -mod transpose_i8_2d; -mod transpose_i8_3d; -mod transpose_u32_2d; -mod transpose_u32_3d; -mod xor_fp16x16; -mod xor_fp16x16_broadcast; -mod xor_fp8x23; -mod xor_fp8x23_broadcast; -mod xor_i32; -mod xor_i32_broadcast; -mod xor_i8; -mod xor_i8_broadcast; -mod xor_u32; -mod xor_u32_broadcast; -mod less_fp16x16; -mod less_fp16x16_broadcast; -mod less_fp8x23; -mod less_fp8x23_broadcast; -mod less_i32; -mod less_i32_broadcast; -mod less_i8; -mod less_i8_broadcast; -mod less_u32; -mod less_u32_broadcast; -mod greater_equal_fp16x16; -mod greater_equal_fp16x16_broadcast; -mod greater_equal_fp8x23; -mod greater_equal_fp8x23_broadcast; -mod greater_equal_i32; -mod greater_equal_i32_broadcast; -mod greater_equal_i8; -mod greater_equal_i8_broadcast; -mod greater_equal_u32; -mod greater_equal_u32_broadcast; -mod slice_fp16x16_2d; -mod slice_fp16x16_3d; -mod slice_fp8x23_2d; -mod slice_fp8x23_3d; -mod slice_i32_2d; -mod slice_i32_3d; -mod slice_i8_2d; -mod slice_i8_3d; -mod slice_u32_2d; -mod slice_u32_3d; -mod gather_fp8x23_3d_default; -mod gather_fp8x23_3d_axis1; -mod gather_fp8x23_3d_axis2; -mod gather_fp16x16_3d_default; -mod gather_fp16x16_3d_axis1; -mod gather_fp16x16_3d_axis2; -mod gather_i8_3d_default; -mod gather_i8_3d_axis1; -mod gather_i8_3d_axis2; -mod gather_i32_3d_default; -mod gather_i32_3d_axis1; -mod gather_i32_3d_axis2; -mod gather_u32_3d_default; -mod gather_u32_3d_axis1; -mod gather_u32_3d_axis2; -mod nonzero_fp16x16_2d; -mod nonzero_fp16x16_3d; -mod nonzero_fp8x23_2d; -mod nonzero_fp8x23_3d; -mod nonzero_i32_2d; -mod nonzero_i32_3d; -mod nonzero_i8_2d; -mod nonzero_i8_3d; -mod nonzero_u32_2d; -mod nonzero_u32_3d; -mod squeeze_fP16x16; -mod squeeze_fP8x23; -mod squeeze_i32; -mod squeeze_i8; -mod squeeze_u32; -mod unsqueeze_fp16x16_2d; -mod unsqueeze_fp16x16_3d; -mod unsqueeze_fp8x23_2d; -mod unsqueeze_fp8x23_3d; -mod unsqueeze_i32_2d; -mod unsqueeze_i32_3d; -mod unsqueeze_i8_2d; -mod unsqueeze_i8_3d; -mod unsqueeze_u32_2d; -mod unsqueeze_u32_3d; -mod sign_fP16x16; -mod sign_fP8x23; -mod sign_fail; -mod sign_i32; -mod sign_i8; -mod clip_fp16x16_2d; -mod clip_fp16x16_3d; -mod clip_fp8x23_2d; -mod clip_fp8x23_3d; -mod clip_i32_2d; -mod clip_i32_3d; -mod clip_i8_2d; -mod clip_i8_3d; -mod clip_u32_2d; -mod clip_u32_3d; -mod identity_fP16x16; -mod identity_fP8x23; -mod identity_i32; -mod identity_i8; -mod identity_u32; -mod thresholded_relu_fp16x16; -mod thresholded_relu_fp8x23; -mod hard_sigmoid_fp8x23; -mod hard_sigmoid_fp16x16; -mod neg_fp16x16; -mod neg_fp8x23; -mod neg_i32; -mod neg_i8; -mod gemm_all_attributes; -mod gemm_alpha; -mod gemm_beta; -mod gemm_default_matrix_bias; -mod gemm_default_vector_bias; -mod gemm_default_no_bias; -mod gemm_transposeA; -mod gemm_transposeB; -mod min_fp16x16_three_tensors; -mod min_fp16x16_broadcast_three_tensors; -mod min_fp16x16_two_tensors; -mod min_fp16x16_broadcast_two_tensors; -mod min_fp8x23_three_tensors; -mod min_fp8x23_broadcast_three_tensors; -mod min_fp8x23_two_tensors; -mod min_fp8x23_broadcast_two_tensors; -mod min_i32_three_tensors; -mod min_i32_broadcast_three_tensors; -mod min_i32_two_tensors; -mod min_i32_broadcast_two_tensors; -mod min_i8_three_tensors; -mod min_i8_broadcast_three_tensors; -mod min_i8_two_tensors; -mod min_i8_broadcast_two_tensors; -mod min_u32_three_tensors; -mod min_u32_broadcast_three_tensors; -mod min_u32_two_tensors; -mod min_u32_broadcast_two_tensors; -mod where_fp16x16; -mod where_fp16x16_broadcast; -mod where_fp8x23; -mod where_fp8x23_broadcast; -mod where_i32; -mod where_i32_broadcast; -mod where_i8; -mod where_i8_broadcast; -mod where_u32; -mod where_u32_broadcast; -mod not_bool; -mod round_fp16x16; -mod round_fp8x23; -mod max_fp16x16_three_tensors; -mod max_fp16x16_broadcast_three_tensors; -mod max_fp16x16_two_tensors; -mod max_fp16x16_broadcast_two_tensors; -mod max_fp8x23_three_tensors; -mod max_fp8x23_broadcast_three_tensors; -mod max_fp8x23_two_tensors; -mod max_fp8x23_broadcast_two_tensors; -mod max_i32_three_tensors; -mod max_i32_broadcast_three_tensors; -mod max_i32_two_tensors; -mod max_i32_broadcast_two_tensors; -mod max_i8_three_tensors; -mod max_i8_broadcast_three_tensors; -mod max_i8_two_tensors; -mod max_i8_broadcast_two_tensors; -mod max_u32_three_tensors; -mod max_u32_broadcast_three_tensors; -mod max_u32_two_tensors; -mod max_u32_broadcast_two_tensors; -mod scatter_fp16x16_3d_default; -mod scatter_fp16x16_3d_axis1; -mod scatter_fp16x16_3d_axis1_add; -mod scatter_fp8x23_default; -mod scatter_fp8x23_axis1; -mod scatter_fp8x23_mul; -mod scatter_i8_default; -mod scatter_i8_axis1; -mod scatter_i8_axis1_max; -mod scatter_u32_default; -mod scatter_u32_axis1; -mod scatter_u32_add; -mod array_feature_extractor_1D_i32; -mod array_feature_extractor_1D_fp8x23; -mod array_feature_extractor_1D_fp16x16; -mod array_feature_extractor_2D_i32; -mod array_feature_extractor_2D_fp8x23; -mod array_feature_extractor_2D_fp16x16; -mod array_feature_extractor_3D_i32; -mod array_feature_extractor_3D_fp8x23; -mod array_feature_extractor_3D_fp16x16; -mod binarizer_fp16x16; -mod binarizer_fp8x23; -mod tril_fp16x16; -mod tril_fp16x16_neg; -mod tril_fp16x16_one_row; -mod tril_fp16x16_out_neg; -mod tril_fp16x16_out_pos; -mod tril_fp16x16_pos; -mod tril_fp16x16_square; -mod tril_fp16x16_square_neg; -mod tril_fp16x16_zero; -mod triu_fp16x16; -mod triu_fp16x16_neg; -mod triu_fp16x16_one_row; -mod triu_fp16x16_out_neg; -mod triu_fp16x16_out_pos; -mod triu_fp16x16_pos; -mod triu_fp16x16_square; -mod triu_fp16x16_square_neg; -mod triu_fp16x16_zero; -mod tril_fp8x23; -mod tril_fp8x23_neg; -mod tril_fp8x23_one_row; -mod tril_fp8x23_out_neg; -mod tril_fp8x23_out_pos; -mod tril_fp8x23_pos; -mod tril_fp8x23_square; -mod tril_fp8x23_square_neg; -mod tril_fp8x23_zero; -mod triu_fp8x23; -mod triu_fp8x23_neg; -mod triu_fp8x23_one_row; -mod triu_fp8x23_out_neg; -mod triu_fp8x23_out_pos; -mod triu_fp8x23_pos; -mod triu_fp8x23_square; -mod triu_fp8x23_square_neg; -mod triu_fp8x23_zero; -mod tril_i32; -mod tril_neg_i32; -mod tril_i32_one_row; -mod tril_i32_out_neg; -mod tril_i32_out_pos; -mod tril_i32_pos; -mod tril_i32_square; -mod tril_i32_square_neg; -mod tril_i32_zero; -mod triu_i32; -mod triu_i32_neg; -mod triu_i32_one_row; -mod triu_i32_out_neg; -mod triu_i32_out_pos; -mod triu_i32_pos; -mod triu_i32_square; -mod triu_i32_square_neg; -mod triu_i32_zero; -mod tril_i8; -mod tril_i8_neg; -mod tril_i8_one_row; -mod tril_i8_out_neg; -mod tril_i8_out_pos; -mod tril_i8_pos; -mod tril_i8_square; -mod tril_i8_square_neg; -mod tril_i8_zero; -mod triu_i8; -mod triu_i8_neg; -mod triu_i8_one_row; -mod triu_i8_out_neg; -mod triu_i8_out_pos; -mod triu_i8_pos; -mod triu_i8_square; -mod triu_i8_square_neg; -mod triu_i8_zero; -mod tril_u32; -mod tril_u32_neg; -mod tril_u32_one_row; -mod tril_u32_out_neg; -mod tril_u32_out_pos; -mod tril_u32_pos; -mod tril_u32_square; -mod tril_u32_square_neg; -mod tril_u32_zero; -mod triu_u32; -mod triu_u32_neg; -mod triu_u32_one_row; -mod triu_u32_out_neg; -mod triu_u32_out_pos; -mod triu_u32_pos; -mod triu_u32_square; -mod triu_u32_square_neg; -mod triu_u32_zero; -mod reduce_sum_square_fp16x16_export_do_not_keepdims; -mod reduce_sum_square_fp16x16_export_keepdims; -mod reduce_sum_square_fp16x16_export_negative_axes_keepdims; -mod reduce_sum_square_fp8x23_export_do_not_keepdims; -mod reduce_sum_square_fp8x23_export_keepdims; -mod reduce_sum_square_fp8x23_export_negative_axes_keepdims; -mod reduce_sum_square_i32_export_do_not_keepdims; -mod reduce_sum_square_i32_export_keepdims; -mod reduce_sum_square_i32_export_negative_axes_keepdims; -mod reduce_sum_square_i8_export_do_not_keepdims; -mod reduce_sum_square_i8_export_keepdims; -mod reduce_sum_square_i8_export_negative_axes_keepdims; -mod reduce_sum_square_u32_export_do_not_keepdims; -mod reduce_sum_square_u32_export_keepdims; -mod reduce_sum_square_u32_export_negative_axes_keepdims; -mod reduce_l2_fp16x16_export_do_not_keepdims; -mod reduce_l2_fp16x16_export_keepdims; -mod reduce_l2_fp16x16_export_negative_axes_keepdims; -mod reduce_l2_fp8x23_export_do_not_keepdims; -mod reduce_l2_fp8x23_export_keepdims; -mod reduce_l2_fp8x23_export_negative_axes_keepdims; -mod reduce_l1_fp16x16_export_do_not_keepdims; -mod reduce_l1_fp16x16_export_keepdims; -mod reduce_l1_fp16x16_export_negative_axes_keepdims; -mod reduce_l1_fp8x23_export_do_not_keepdims; -mod reduce_l1_fp8x23_export_keepdims; -mod reduce_l1_fp8x23_export_negative_axes_keepdims; -mod reduce_l1_i32_export_do_not_keepdims; -mod reduce_l1_i32_export_keepdims; -mod reduce_l1_i32_export_negative_axes_keepdims; -mod reduce_l1_i8_export_do_not_keepdims; -mod reduce_l1_i8_export_keepdims; -mod reduce_l1_i8_export_negative_axes_keepdims; -mod reduce_l1_u32_export_do_not_keepdims; -mod reduce_l1_u32_export_keepdims; -mod reduce_l1_u32_export_negative_axes_keepdims; -mod reduce_prod_fp16x16_1D; -mod reduce_prod_fp16x16_2D_default; -mod reduce_prod_fp16x16_2D_keepdims; -mod reduce_prod_fp16x16_2D_axis_1; -mod reduce_prod_fp8x23_1D; -mod reduce_prod_fp8x23_2D_default; -mod reduce_prod_fp8x23_2D_keepdims; -mod reduce_prod_fp8x23_2D_axis_1; -mod reduce_prod_i32_1D; -mod reduce_prod_i32_2D_default; -mod reduce_prod_i32_2D_keepdims; -mod reduce_prod_i32_2D_axis_1; -mod reduce_prod_i8_1D; -mod reduce_prod_i8_2D_default; -mod reduce_prod_i8_2D_keepdims; -mod reduce_prod_i8_2D_axis_1; -mod reduce_prod_u32_1D; -mod reduce_prod_u32_2D_default; -mod reduce_prod_u32_2D_keepdims; -mod reduce_prod_u32_2D_axis_1; -mod gather_elements_fp16x16_3d_default; -mod gather_elements_fp16x16_3d_axis1; -mod gather_elements_fp16x16_3d_axis2; -mod gather_elements_fp8x23_3d_default; -mod gather_elements_fp8x23_3d_axis1; -mod gather_elements_fp8x23_3d_axis2; -mod gather_elements_i8_3d_default; -mod gather_elements_i8_3d_axis1; -mod gather_elements_i32_3d_default; -mod gather_elements_i32_3d_axis1; -mod gather_elements_i32_3d_axis2; -mod gather_elements_u32_default; -mod gather_elements_u32_axis1; -mod gather_elements_u32_axis2; -mod gather_elements_u32_axis3; -mod sequence_length_fp16x16; -mod sequence_length_fp16x16_broadcast; -mod sequence_length_fp8x23; -mod sequence_length_fp8x23_broadcast; -mod sequence_length_i32; -mod sequence_length_i32_broadcast; -mod sequence_length_i8; -mod sequence_length_i8_broadcast; -mod sequence_length_u32; -mod sequence_length_u32_broadcast; -mod sequence_at_u32_positive; -mod sequence_at_u32_negative; -mod sequence_at_fp16x16_positive; -mod sequence_at_fp16x16_negative; -mod sequence_at_fp8x23_positive; -mod sequence_at_fp8x23_negative; -mod sequence_at_i32_positive; -mod sequence_at_i32_negative; -mod sequence_at_i8_positive; -mod sequence_at_i8_negative; -mod reduce_min_fp16x16_1D; -mod reduce_min_fp16x16_2D_default; -mod reduce_min_fp16x16_2D_keepdims; -mod reduce_min_fp16x16_2D_axis_1; -mod reduce_min_fp8x23_1D; -mod reduce_min_fp8x23_2D_default; -mod reduce_min_fp8x23_2D_keepdims; -mod reduce_min_fp8x23_2D_axis_1; -mod reduce_min_i32_1D; -mod reduce_min_i32_2D_default; -mod reduce_min_i32_2D_keepdims; -mod reduce_min_i32_2D_axis_1; -mod reduce_min_i8_1D; -mod reduce_min_i8_2D_default; -mod reduce_min_i8_2D_keepdims; -mod reduce_min_i8_2D_axis_1; -mod reduce_min_u32_1D; -mod reduce_min_u32_2D_default; -mod reduce_min_u32_2D_keepdims; -mod reduce_min_u32_2D_axis_1; -mod sequence_construct_fp16x16; -mod sequence_construct_fp8x23; -mod sequence_construct_i32; -mod sequence_construct_i8; -mod sequence_construct_u32; -mod shrink_hard_fp16x16; -mod shrink_soft_fp16x16; -mod shrink_hard_fp8x23; -mod shrink_soft_fp8x23; -mod sequence_empty_fp16x16; -mod sequence_empty_fp8x23; -mod sequence_empty_i32; -mod sequence_empty_i8; -mod sequence_empty_u32; -mod reduce_mean_fp16x16_1D; -mod reduce_mean_fp16x16_2D_default; -mod reduce_mean_fp16x16_2D_keepdims; -mod reduce_mean_fp16x16_2D_axis_1; -mod reduce_mean_fp8x23_1D; -mod reduce_mean_fp8x23_2D_default; -mod reduce_mean_fp8x23_2D_keepdims; -mod reduce_mean_fp8x23_2D_axis_1; -mod reduce_mean_i32_1D; -mod reduce_mean_i32_2D_default; -mod reduce_mean_i32_2D_keepdims; -mod reduce_mean_i32_2D_axis_1; -mod reduce_mean_i8_1D; -mod reduce_mean_i8_2D_default; -mod reduce_mean_i8_2D_keepdims; -mod reduce_mean_i8_2D_axis_1; -mod reduce_mean_u32_1D; -mod reduce_mean_u32_2D_default; -mod reduce_mean_u32_2D_keepdims; -mod reduce_mean_u32_2D_axis_1; -mod pow_fp16x16; -mod pow_fp16x16_broadcast; -mod pow_fp8x23; -mod pow_fp8x23_broadcast; -mod sequence_erase_u32_positive; -mod sequence_erase_u32_negative; -mod sequence_erase_u32_empty; -mod sequence_erase_fp16x16_positive; -mod sequence_erase_fp16x16_negative; -mod sequence_erase_fp16x16_empty; -mod sequence_erase_fp8x23_positive; -mod sequence_erase_fp8x23_negative; -mod sequence_erase_fp8x23_empty; -mod sequence_erase_i32_positive; -mod sequence_erase_i32_negative; -mod sequence_erase_i32_empty; -mod sequence_erase_i8_positive; -mod sequence_erase_i8_negative; -mod sequence_erase_i8_empty; -mod sequence_insert_fp16x16; -mod sequence_insert_fp8x23; -mod sequence_insert_i32; -mod sequence_insert_i8; -mod sequence_insert_u32; -mod concat_from_sequence_fp8x23_new_axis_zero; -mod concat_from_sequence_fp8x23_new_axis_one; -mod concat_from_sequence_fp8x23_new_axis_default; -mod concat_from_sequence_fp16x16_new_axis_zero; -mod concat_from_sequence_fp16x16_new_axis_one; -mod concat_from_sequence_fp16x16_new_axis_default; -mod concat_from_sequence_i32_new_axis_zero; -mod concat_from_sequence_i32_new_axis_one; -mod concat_from_sequence_i32_new_axis_default; -mod concat_from_sequence_i8_new_axis_zero; -mod concat_from_sequence_i8_new_axis_one; -mod concat_from_sequence_i8_new_axis_default; -mod concat_from_sequence_u32_new_axis_zero; -mod concat_from_sequence_u32_new_axis_one; -mod concat_from_sequence_u32_new_axis_default; -mod is_nan_fp16x16; -mod is_nan_fp8x23; -mod is_inf_fp16x16; -mod is_inf_fp8x23; -mod is_inf_i32; -mod is_inf_i8; -mod is_inf_u32; -mod is_pos_inf_fp16x16; -mod is_neg_inf_fp16x16; -mod is_pos_inf_fp8x23; -mod is_neg_inf_fp8x23; -mod is_pos_inf_i32; -mod is_neg_inf_i32; -mod is_pos_inf_i8; -mod is_neg_inf_i8; -mod and_bool; +// mod abs_fp16x16; +// mod abs_fp8x23; +// mod abs_i32; +// mod abs_i8; +// mod acos_fp16x16; +// mod acos_fp8x23; +// mod acosh_fp16x16; +// mod acosh_fp8x23; +// mod add_fp16x16; +// mod add_fp16x16_broadcast; +// mod add_fp8x23; +// mod add_fp8x23_broadcast; +// mod add_i32; +// mod add_i32_broadcast; +// mod add_i8; +// mod add_i8_broadcast; +// mod add_u32; +// mod add_u32_broadcast; +// mod argmax_fp16x16_1D_default; +// mod argmax_fp16x16_1D_keepdims_false; +// mod argmax_fp16x16_1D_last_index; +// mod argmax_fp16x16_2D_default; +// mod argmax_fp16x16_2D_keepdims_false; +// mod argmax_fp16x16_2D_last_index; +// mod argmax_fp16x16_3D_default; +// mod argmax_fp16x16_3D_keepdims_false; +// mod argmax_fp16x16_3D_last_index; +// mod argmax_fp8x23_1D_default; +// mod argmax_fp8x23_1D_keepdims_false; +// mod argmax_fp8x23_1D_last_index; +// mod argmax_fp8x23_2D_default; +// mod argmax_fp8x23_2D_keepdims_false; +// mod argmax_fp8x23_2D_last_index; +// mod argmax_fp8x23_3D_default; +// mod argmax_fp8x23_3D_keepdims_false; +// mod argmax_fp8x23_3D_last_index; +// mod argmax_i32_1D_default; +// mod argmax_i32_1D_keepdims_false; +// mod argmax_i32_1D_last_index; +// mod argmax_i32_2D_default; +// mod argmax_i32_2D_keepdims_false; +// mod argmax_i32_2D_last_index; +// mod argmax_i32_3D_default; +// mod argmax_i32_3D_keepdims_false; +// mod argmax_i32_3D_last_index; +// mod argmax_i8_1D_default; +// mod argmax_i8_1D_keepdims_false; +// mod argmax_i8_1D_last_index; +// mod argmax_i8_2D_default; +// mod argmax_i8_2D_keepdims_false; +// mod argmax_i8_2D_last_index; +// mod argmax_i8_3D_default; +// mod argmax_i8_3D_keepdims_false; +// mod argmax_i8_3D_last_index; +// mod argmax_u32_1D_default; +// mod argmax_u32_1D_keepdims_false; +// mod argmax_u32_1D_last_index; +// mod argmax_u32_2D_default; +// mod argmax_u32_2D_keepdims_false; +// mod argmax_u32_2D_last_index; +// mod argmax_u32_3D_default; +// mod argmax_u32_3D_keepdims_false; +// mod argmax_u32_3D_last_index; +// mod argmin_fp16x16_1D_default; +// mod argmin_fp16x16_1D_keepdims_false; +// mod argmin_fp16x16_1D_last_index; +// mod argmin_fp16x16_2D_default; +// mod argmin_fp16x16_2D_keepdims_false; +// mod argmin_fp16x16_2D_last_index; +// mod argmin_fp16x16_3D_default; +// mod argmin_fp16x16_3D_keepdims_false; +// mod argmin_fp16x16_3D_last_index; +// mod argmin_fp8x23_1D_default; +// mod argmin_fp8x23_1D_keepdims_false; +// mod argmin_fp8x23_1D_last_index; +// mod argmin_fp8x23_2D_default; +// mod argmin_fp8x23_2D_keepdims_false; +// mod argmin_fp8x23_2D_last_index; +// mod argmin_fp8x23_3D_default; +// mod argmin_fp8x23_3D_keepdims_false; +// mod argmin_fp8x23_3D_last_index; +// mod argmin_i32_1D_default; +// mod argmin_i32_1D_keepdims_false; +// mod argmin_i32_1D_last_index; +// mod argmin_i32_2D_default; +// mod argmin_i32_2D_keepdims_false; +// mod argmin_i32_2D_last_index; +// mod argmin_i32_3D_default; +// mod argmin_i32_3D_keepdims_false; +// mod argmin_i32_3D_last_index; +// mod argmin_i8_1D_default; +// mod argmin_i8_1D_keepdims_false; +// mod argmin_i8_1D_last_index; +// mod argmin_i8_2D_default; +// mod argmin_i8_2D_keepdims_false; +// mod argmin_i8_2D_last_index; +// mod argmin_i8_3D_default; +// mod argmin_i8_3D_keepdims_false; +// mod argmin_i8_3D_last_index; +// mod argmin_u32_1D_default; +// mod argmin_u32_1D_keepdims_false; +// mod argmin_u32_1D_last_index; +// mod argmin_u32_2D_default; +// mod argmin_u32_2D_keepdims_false; +// mod argmin_u32_2D_last_index; +// mod argmin_u32_3D_default; +// mod argmin_u32_3D_keepdims_false; +// mod argmin_u32_3D_last_index; +// mod asin_fp16x16; +// mod asin_fp8x23; +// mod asinh_fp16x16; +// mod asinh_fp8x23; +// mod atan_fp16x16; +// mod atan_fp8x23; +// mod ceil_fp16x16; +// mod ceil_fp8x23; +// mod concat_fp16x16_1d; +// mod concat_fp16x16_2d; +// mod concat_fp16x16_3d_default; +// mod concat_fp16x16_3d_axis_1; +// mod concat_fp16x16_3d_axis_2; +// mod concat_fp16x16_3d_three_tensors_axis_1; +// mod concat_fp16x16_3d_three_tensors_axis_2; +// mod concat_fp8x23_1d; +// mod concat_fp8x23_2d; +// mod concat_fp8x23_3d_default; +// mod concat_fp8x23_3d_axis_1; +// mod concat_fp8x23_3d_axis_2; +// mod concat_fp8x23_3d_three_tensors_axis_1; +// mod concat_fp8x23_3d_three_tensors_axis_2; +// mod concat_i32_1d; +// mod concat_i32_2d; +// mod concat_i32_3d_default; +// mod concat_i32_3d_axis_1; +// mod concat_i32_3d_axis_2; +// mod concat_i32_3d_three_tensors_axis_1; +// mod concat_i32_3d_three_tensors_axis_2; +// mod concat_i8_1d; +// mod concat_i8_2d; +// mod concat_i8_3d_default; +// mod concat_i8_3d_axis_1; +// mod concat_i8_3d_axis_2; +// mod concat_i8_3d_three_tensors_axis_1; +// mod concat_i8_3d_three_tensors_axis_2; +// mod concat_u32_1d; +// mod concat_u32_2d; +// mod concat_u32_3d_default; +// mod concat_u32_3d_axis_1; +// mod concat_u32_3d_axis_2; +// mod concat_u32_3d_three_tensors_axis_1; +// mod concat_u32_3d_three_tensors_axis_2; +// mod cos_fp16x16; +// mod cos_fp8x23; +// mod cosh_fp16x16; +// mod cosh_fp8x23; +// mod cumsum_fp16x16_1d_default; +// mod cumsum_fp16x16_1d_exclusive; +// mod cumsum_fp16x16_1d_reverse; +// mod cumsum_fp16x16_1d_reverse_exclusive; +// mod cumsum_fp16x16_2d_axis_0; +// mod cumsum_fp16x16_2d_axis_1; +// mod cumsum_fp8x23_1d_default; +// mod cumsum_fp8x23_1d_exclusive; +// mod cumsum_fp8x23_1d_reverse; +// mod cumsum_fp8x23_1d_reverse_exclusive; +// mod cumsum_fp8x23_2d_axis_0; +// mod cumsum_fp8x23_2d_axis_1; +// mod cumsum_i32_1d_default; +// mod cumsum_i32_1d_exclusive; +// mod cumsum_i32_1d_reverse; +// mod cumsum_i32_1d_reverse_exclusive; +// mod cumsum_i32_2d_axis_0; +// mod cumsum_i32_2d_axis_1; +// mod cumsum_i8_1d_default; +// mod cumsum_i8_1d_exclusive; +// mod cumsum_i8_1d_reverse; +// mod cumsum_i8_1d_reverse_exclusive; +// mod cumsum_i8_2d_axis_0; +// mod cumsum_i8_2d_axis_1; +// mod cumsum_u32_1d_default; +// mod cumsum_u32_1d_exclusive; +// mod cumsum_u32_1d_reverse; +// mod cumsum_u32_1d_reverse_exclusive; +// mod cumsum_u32_2d_axis_0; +// mod cumsum_u32_2d_axis_1; +// mod div_fp16x16; +// mod div_fp16x16_broadcast; +// mod div_fp8x23; +// mod div_fp8x23_broadcast; +// mod div_i32; +// mod div_i32_broadcast; +// mod div_i8; +// mod div_i8_broadcast; +// mod div_u32; +// mod div_u32_broadcast; +// mod equal_fp16x16; +// mod equal_fp16x16_broadcast; +// mod equal_fp8x23; +// mod equal_fp8x23_broadcast; +// mod equal_i32; +// mod equal_i32_broadcast; +// mod equal_i8; +// mod equal_i8_broadcast; +// mod equal_u32; +// mod equal_u32_broadcast; +// mod exp_fp16x16; +// mod exp_fp8x23; +// mod less_equal_fp16x16; +// mod less_equal_fp16x16_broadcast; +// mod less_equal_fp8x23; +// mod less_equal_fp8x23_broadcast; +// mod less_equal_i32; +// mod less_equal_i32_broadcast; +// mod less_equal_i8; +// mod less_equal_i8_broadcast; +// mod less_equal_u32; +// mod less_equal_u32_broadcast; +// mod greater_fp16x16; +// mod greater_fp16x16_broadcast; +// mod greater_fp8x23; +// mod greater_fp8x23_broadcast; +// mod greater_i32; +// mod greater_i32_broadcast; +// mod greater_i8; +// mod greater_i8_broadcast; +// mod greater_u32; +// mod greater_u32_broadcast; +// mod leaky_relu_fp16x16; +// mod leaky_relu_fp8x23; +// mod linear_fp16x16; +// mod linear_fp8x23; +// mod linear_i32; +// mod linear_i8; +// mod linear_u32; +// mod log_fp16x16; +// mod log_fp8x23; +// mod logsoftmax_fp16x16_axis_0; +// mod logsoftmax_fp16x16_axis_1; +// mod logsoftmax_fp8x23_axis_0; +// mod logsoftmax_fp8x23_axis_1; +// mod matmul_fp16x16_1d; +// mod matmul_fp16x16_2x2; +// mod matmul_fp16x16_2x1; +// mod matmul_fp16x16_1x2; +// mod matmul_fp8x23_1d; +// mod matmul_fp8x23_2x2; +// mod matmul_fp8x23_2x1; +// mod matmul_fp8x23_1x2; +// mod matmul_i32_1d; +// mod matmul_i32_2x2; +// mod matmul_i32_2x1; +// mod matmul_i32_1x2; +// mod matmul_i8_1d; +// mod matmul_i8_2x2; +// mod matmul_i8_2x1; +// mod matmul_i8_1x2; +// mod matmul_u32_1d; +// mod matmul_u32_2x2; +// mod matmul_u32_2x1; +// mod matmul_u32_1x2; +// mod mul_fp16x16; +// mod mul_fp16x16_broadcast; +// mod mul_fp8x23; +// mod mul_fp8x23_broadcast; +// mod mul_i32; +// mod mul_i32_broadcast; +// mod mul_i8; +// mod mul_i8_broadcast; +// mod mul_u32; +// mod mul_u32_broadcast; +// mod or_fp16x16; +// mod or_fp16x16_broadcast; +// mod or_fp8x23; +// mod or_fp8x23_broadcast; +// mod or_i32; +// mod or_i32_broadcast; +// mod or_i8; +// mod or_i8_broadcast; +// mod or_u32; +// mod or_u32_broadcast; +// mod reduce_sum_fp16x16_1D; +// mod reduce_sum_fp16x16_2D_default; +// mod reduce_sum_fp16x16_2D_keepdims; +// mod reduce_sum_fp16x16_2D_axis_1; +// mod reduce_sum_fp8x23_1D; +// mod reduce_sum_fp8x23_2D_default; +// mod reduce_sum_fp8x23_2D_keepdims; +// mod reduce_sum_fp8x23_2D_axis_1; +// mod reduce_sum_i32_1D; +// mod reduce_sum_i32_2D_default; +// mod reduce_sum_i32_2D_keepdims; +// mod reduce_sum_i32_2D_axis_1; +// mod reduce_sum_i8_1D; +// mod reduce_sum_i8_2D_default; +// mod reduce_sum_i8_2D_keepdims; +// mod reduce_sum_i8_2D_axis_1; +// mod reduce_sum_u32_1D; +// mod reduce_sum_u32_2D_default; +// mod reduce_sum_u32_2D_keepdims; +// mod reduce_sum_u32_2D_axis_1; +// mod relu_fp16x16; +// mod relu_fp8x23; +// mod relu_i32; +// mod relu_i8; +// mod sigmoid_fp16x16; +// mod sigmoid_fp8x23; +// mod sin_fp16x16; +// mod sin_fp8x23; +// mod sinh_fp16x16; +// mod sinh_fp8x23; +// mod softmax_fp16x16; +// mod softmax_fp8x23; +// mod softplus_fp8x23; +// mod softplus_fp16x16; +// mod softsign_fp8x23; +// mod softsign_fp16x16; +// mod sqrt_fp16x16; +// mod sqrt_fp8x23; +// mod sub_fp16x16; +// mod sub_fp16x16_broadcast; +// mod sub_fp8x23; +// mod sub_fp8x23_broadcast; +// mod sub_i32; +// mod sub_i32_broadcast; +// mod sub_i8; +// mod sub_i8_broadcast; +// mod sub_u32; +// mod sub_u32_broadcast; +// mod tanh_fp16x16; +// mod tanh_fp8x23; +// mod transpose_fp16x16_2d; +// mod transpose_fp16x16_3d; +// mod transpose_fp8x23_2d; +// mod transpose_fp8x23_3d; +// mod transpose_i32_2d; +// mod transpose_i32_3d; +// mod transpose_i8_2d; +// mod transpose_i8_3d; +// mod transpose_u32_2d; +// mod transpose_u32_3d; +// mod xor_fp16x16; +// mod xor_fp16x16_broadcast; +// mod xor_fp8x23; +// mod xor_fp8x23_broadcast; +// mod xor_i32; +// mod xor_i32_broadcast; +// mod xor_i8; +// mod xor_i8_broadcast; +// mod xor_u32; +// mod xor_u32_broadcast; +// mod less_fp16x16; +// mod less_fp16x16_broadcast; +// mod less_fp8x23; +// mod less_fp8x23_broadcast; +// mod less_i32; +// mod less_i32_broadcast; +// mod less_i8; +// mod less_i8_broadcast; +// mod less_u32; +// mod less_u32_broadcast; +// mod greater_equal_fp16x16; +// mod greater_equal_fp16x16_broadcast; +// mod greater_equal_fp8x23; +// mod greater_equal_fp8x23_broadcast; +// mod greater_equal_i32; +// mod greater_equal_i32_broadcast; +// mod greater_equal_i8; +// mod greater_equal_i8_broadcast; +// mod greater_equal_u32; +// mod greater_equal_u32_broadcast; +// mod slice_fp16x16_2d; +// mod slice_fp16x16_3d; +// mod slice_fp8x23_2d; +// mod slice_fp8x23_3d; +// mod slice_i32_2d; +// mod slice_i32_3d; +// mod slice_i8_2d; +// mod slice_i8_3d; +// mod slice_u32_2d; +// mod slice_u32_3d; +// mod gather_fp8x23_3d_default; +// mod gather_fp8x23_3d_axis1; +// mod gather_fp8x23_3d_axis2; +// mod gather_fp16x16_3d_default; +// mod gather_fp16x16_3d_axis1; +// mod gather_fp16x16_3d_axis2; +// mod gather_i8_3d_default; +// mod gather_i8_3d_axis1; +// mod gather_i8_3d_axis2; +// mod gather_i32_3d_default; +// mod gather_i32_3d_axis1; +// mod gather_i32_3d_axis2; +// mod gather_u32_3d_default; +// mod gather_u32_3d_axis1; +// mod gather_u32_3d_axis2; +// mod nonzero_fp16x16_2d; +// mod nonzero_fp16x16_3d; +// mod nonzero_fp8x23_2d; +// mod nonzero_fp8x23_3d; +// mod nonzero_i32_2d; +// mod nonzero_i32_3d; +// mod nonzero_i8_2d; +// mod nonzero_i8_3d; +// mod nonzero_u32_2d; +// mod nonzero_u32_3d; +// mod squeeze_fP16x16; +// mod squeeze_fP8x23; +// mod squeeze_i32; +// mod squeeze_i8; +// mod squeeze_u32; +// mod unsqueeze_fp16x16_2d; +// mod unsqueeze_fp16x16_3d; +// mod unsqueeze_fp8x23_2d; +// mod unsqueeze_fp8x23_3d; +// mod unsqueeze_i32_2d; +// mod unsqueeze_i32_3d; +// mod unsqueeze_i8_2d; +// mod unsqueeze_i8_3d; +// mod unsqueeze_u32_2d; +// mod unsqueeze_u32_3d; +// mod sign_fP16x16; +// mod sign_fP8x23; +// mod sign_fail; +// mod sign_i32; +// mod sign_i8; +// mod clip_fp16x16_2d; +// mod clip_fp16x16_3d; +// mod clip_fp8x23_2d; +// mod clip_fp8x23_3d; +// mod clip_i32_2d; +// mod clip_i32_3d; +// mod clip_i8_2d; +// mod clip_i8_3d; +// mod clip_u32_2d; +// mod clip_u32_3d; +// mod identity_fP16x16; +// mod identity_fP8x23; +// mod identity_i32; +// mod identity_i8; +// mod identity_u32; +// mod thresholded_relu_fp16x16; +// mod thresholded_relu_fp8x23; +// mod hard_sigmoid_fp8x23; +// mod hard_sigmoid_fp16x16; +// mod neg_fp16x16; +// mod neg_fp8x23; +// mod neg_i32; +// mod neg_i8; +// mod gemm_all_attributes; +// mod gemm_alpha; +// mod gemm_beta; +// mod gemm_default_matrix_bias; +// mod gemm_default_vector_bias; +// mod gemm_default_no_bias; +// mod gemm_transposeA; +// mod gemm_transposeB; +// mod min_fp16x16_three_tensors; +// mod min_fp16x16_broadcast_three_tensors; +// mod min_fp16x16_two_tensors; +// mod min_fp16x16_broadcast_two_tensors; +// mod min_fp8x23_three_tensors; +// mod min_fp8x23_broadcast_three_tensors; +// mod min_fp8x23_two_tensors; +// mod min_fp8x23_broadcast_two_tensors; +// mod min_i32_three_tensors; +// mod min_i32_broadcast_three_tensors; +// mod min_i32_two_tensors; +// mod min_i32_broadcast_two_tensors; +// mod min_i8_three_tensors; +// mod min_i8_broadcast_three_tensors; +// mod min_i8_two_tensors; +// mod min_i8_broadcast_two_tensors; +// mod min_u32_three_tensors; +// mod min_u32_broadcast_three_tensors; +// mod min_u32_two_tensors; +// mod min_u32_broadcast_two_tensors; +// mod where_fp16x16; +// mod where_fp16x16_broadcast; +// mod where_fp8x23; +// mod where_fp8x23_broadcast; +// mod where_i32; +// mod where_i32_broadcast; +// mod where_i8; +// mod where_i8_broadcast; +// mod where_u32; +// mod where_u32_broadcast; +// mod not_bool; +// mod round_fp16x16; +// mod round_fp8x23; +// mod max_fp16x16_three_tensors; +// mod max_fp16x16_broadcast_three_tensors; +// mod max_fp16x16_two_tensors; +// mod max_fp16x16_broadcast_two_tensors; +// mod max_fp8x23_three_tensors; +// mod max_fp8x23_broadcast_three_tensors; +// mod max_fp8x23_two_tensors; +// mod max_fp8x23_broadcast_two_tensors; +// mod max_i32_three_tensors; +// mod max_i32_broadcast_three_tensors; +// mod max_i32_two_tensors; +// mod max_i32_broadcast_two_tensors; +// mod max_i8_three_tensors; +// mod max_i8_broadcast_three_tensors; +// mod max_i8_two_tensors; +// mod max_i8_broadcast_two_tensors; +// mod max_u32_three_tensors; +// mod max_u32_broadcast_three_tensors; +// mod max_u32_two_tensors; +// mod max_u32_broadcast_two_tensors; +// mod scatter_fp16x16_3d_default; +// mod scatter_fp16x16_3d_axis1; +// mod scatter_fp16x16_3d_axis1_add; +// mod scatter_fp8x23_default; +// mod scatter_fp8x23_axis1; +// mod scatter_fp8x23_mul; +// mod scatter_i8_default; +// mod scatter_i8_axis1; +// mod scatter_i8_axis1_max; +// mod scatter_u32_default; +// mod scatter_u32_axis1; +// mod scatter_u32_add; +// mod array_feature_extractor_1D_i32; +// mod array_feature_extractor_1D_fp8x23; +// mod array_feature_extractor_1D_fp16x16; +// mod array_feature_extractor_2D_i32; +// mod array_feature_extractor_2D_fp8x23; +// mod array_feature_extractor_2D_fp16x16; +// mod array_feature_extractor_3D_i32; +// mod array_feature_extractor_3D_fp8x23; +// mod array_feature_extractor_3D_fp16x16; +// mod binarizer_fp16x16; +// mod binarizer_fp8x23; +// mod tril_fp16x16; +// mod tril_fp16x16_neg; +// mod tril_fp16x16_one_row; +// mod tril_fp16x16_out_neg; +// mod tril_fp16x16_out_pos; +// mod tril_fp16x16_pos; +// mod tril_fp16x16_square; +// mod tril_fp16x16_square_neg; +// mod tril_fp16x16_zero; +// mod triu_fp16x16; +// mod triu_fp16x16_neg; +// mod triu_fp16x16_one_row; +// mod triu_fp16x16_out_neg; +// mod triu_fp16x16_out_pos; +// mod triu_fp16x16_pos; +// mod triu_fp16x16_square; +// mod triu_fp16x16_square_neg; +// mod triu_fp16x16_zero; +// mod tril_fp8x23; +// mod tril_fp8x23_neg; +// mod tril_fp8x23_one_row; +// mod tril_fp8x23_out_neg; +// mod tril_fp8x23_out_pos; +// mod tril_fp8x23_pos; +// mod tril_fp8x23_square; +// mod tril_fp8x23_square_neg; +// mod tril_fp8x23_zero; +// mod triu_fp8x23; +// mod triu_fp8x23_neg; +// mod triu_fp8x23_one_row; +// mod triu_fp8x23_out_neg; +// mod triu_fp8x23_out_pos; +// mod triu_fp8x23_pos; +// mod triu_fp8x23_square; +// mod triu_fp8x23_square_neg; +// mod triu_fp8x23_zero; +// mod tril_i32; +// mod tril_neg_i32; +// mod tril_i32_one_row; +// mod tril_i32_out_neg; +// mod tril_i32_out_pos; +// mod tril_i32_pos; +// mod tril_i32_square; +// mod tril_i32_square_neg; +// mod tril_i32_zero; +// mod triu_i32; +// mod triu_i32_neg; +// mod triu_i32_one_row; +// mod triu_i32_out_neg; +// mod triu_i32_out_pos; +// mod triu_i32_pos; +// mod triu_i32_square; +// mod triu_i32_square_neg; +// mod triu_i32_zero; +// mod tril_i8; +// mod tril_i8_neg; +// mod tril_i8_one_row; +// mod tril_i8_out_neg; +// mod tril_i8_out_pos; +// mod tril_i8_pos; +// mod tril_i8_square; +// mod tril_i8_square_neg; +// mod tril_i8_zero; +// mod triu_i8; +// mod triu_i8_neg; +// mod triu_i8_one_row; +// mod triu_i8_out_neg; +// mod triu_i8_out_pos; +// mod triu_i8_pos; +// mod triu_i8_square; +// mod triu_i8_square_neg; +// mod triu_i8_zero; +// mod tril_u32; +// mod tril_u32_neg; +// mod tril_u32_one_row; +// mod tril_u32_out_neg; +// mod tril_u32_out_pos; +// mod tril_u32_pos; +// mod tril_u32_square; +// mod tril_u32_square_neg; +// mod tril_u32_zero; +// mod triu_u32; +// mod triu_u32_neg; +// mod triu_u32_one_row; +// mod triu_u32_out_neg; +// mod triu_u32_out_pos; +// mod triu_u32_pos; +// mod triu_u32_square; +// mod triu_u32_square_neg; +// mod triu_u32_zero; +// mod reduce_sum_square_fp16x16_export_do_not_keepdims; +// mod reduce_sum_square_fp16x16_export_keepdims; +// mod reduce_sum_square_fp16x16_export_negative_axes_keepdims; +// mod reduce_sum_square_fp8x23_export_do_not_keepdims; +// mod reduce_sum_square_fp8x23_export_keepdims; +// mod reduce_sum_square_fp8x23_export_negative_axes_keepdims; +// mod reduce_sum_square_i32_export_do_not_keepdims; +// mod reduce_sum_square_i32_export_keepdims; +// mod reduce_sum_square_i32_export_negative_axes_keepdims; +// mod reduce_sum_square_i8_export_do_not_keepdims; +// mod reduce_sum_square_i8_export_keepdims; +// mod reduce_sum_square_i8_export_negative_axes_keepdims; +// mod reduce_sum_square_u32_export_do_not_keepdims; +// mod reduce_sum_square_u32_export_keepdims; +// mod reduce_sum_square_u32_export_negative_axes_keepdims; +// mod reduce_l2_fp16x16_export_do_not_keepdims; +// mod reduce_l2_fp16x16_export_keepdims; +// mod reduce_l2_fp16x16_export_negative_axes_keepdims; +// mod reduce_l2_fp8x23_export_do_not_keepdims; +// mod reduce_l2_fp8x23_export_keepdims; +// mod reduce_l2_fp8x23_export_negative_axes_keepdims; +// mod reduce_l1_fp16x16_export_do_not_keepdims; +// mod reduce_l1_fp16x16_export_keepdims; +// mod reduce_l1_fp16x16_export_negative_axes_keepdims; +// mod reduce_l1_fp8x23_export_do_not_keepdims; +// mod reduce_l1_fp8x23_export_keepdims; +// mod reduce_l1_fp8x23_export_negative_axes_keepdims; +// mod reduce_l1_i32_export_do_not_keepdims; +// mod reduce_l1_i32_export_keepdims; +// mod reduce_l1_i32_export_negative_axes_keepdims; +// mod reduce_l1_i8_export_do_not_keepdims; +// mod reduce_l1_i8_export_keepdims; +// mod reduce_l1_i8_export_negative_axes_keepdims; +// mod reduce_l1_u32_export_do_not_keepdims; +// mod reduce_l1_u32_export_keepdims; +// mod reduce_l1_u32_export_negative_axes_keepdims; +// mod reduce_prod_fp16x16_1D; +// mod reduce_prod_fp16x16_2D_default; +// mod reduce_prod_fp16x16_2D_keepdims; +// mod reduce_prod_fp16x16_2D_axis_1; +// mod reduce_prod_fp8x23_1D; +// mod reduce_prod_fp8x23_2D_default; +// mod reduce_prod_fp8x23_2D_keepdims; +// mod reduce_prod_fp8x23_2D_axis_1; +// mod reduce_prod_i32_1D; +// mod reduce_prod_i32_2D_default; +// mod reduce_prod_i32_2D_keepdims; +// mod reduce_prod_i32_2D_axis_1; +// mod reduce_prod_i8_1D; +// mod reduce_prod_i8_2D_default; +// mod reduce_prod_i8_2D_keepdims; +// mod reduce_prod_i8_2D_axis_1; +// mod reduce_prod_u32_1D; +// mod reduce_prod_u32_2D_default; +// mod reduce_prod_u32_2D_keepdims; +// mod reduce_prod_u32_2D_axis_1; +// mod gather_elements_fp16x16_3d_default; +// mod gather_elements_fp16x16_3d_axis1; +// mod gather_elements_fp16x16_3d_axis2; +// mod gather_elements_fp8x23_3d_default; +// mod gather_elements_fp8x23_3d_axis1; +// mod gather_elements_fp8x23_3d_axis2; +// mod gather_elements_i8_3d_default; +// mod gather_elements_i8_3d_axis1; +// mod gather_elements_i32_3d_default; +// mod gather_elements_i32_3d_axis1; +// mod gather_elements_i32_3d_axis2; +// mod gather_elements_u32_default; +// mod gather_elements_u32_axis1; +// mod gather_elements_u32_axis2; +// mod gather_elements_u32_axis3; +// mod sequence_length_fp16x16; +// mod sequence_length_fp16x16_broadcast; +// mod sequence_length_fp8x23; +// mod sequence_length_fp8x23_broadcast; +// mod sequence_length_i32; +// mod sequence_length_i32_broadcast; +// mod sequence_length_i8; +// mod sequence_length_i8_broadcast; +// mod sequence_length_u32; +// mod sequence_length_u32_broadcast; +// mod sequence_at_u32_positive; +// mod sequence_at_u32_negative; +// mod sequence_at_fp16x16_positive; +// mod sequence_at_fp16x16_negative; +// mod sequence_at_fp8x23_positive; +// mod sequence_at_fp8x23_negative; +// mod sequence_at_i32_positive; +// mod sequence_at_i32_negative; +// mod sequence_at_i8_positive; +// mod sequence_at_i8_negative; +// mod reduce_min_fp16x16_1D; +// mod reduce_min_fp16x16_2D_default; +// mod reduce_min_fp16x16_2D_keepdims; +// mod reduce_min_fp16x16_2D_axis_1; +// mod reduce_min_fp8x23_1D; +// mod reduce_min_fp8x23_2D_default; +// mod reduce_min_fp8x23_2D_keepdims; +// mod reduce_min_fp8x23_2D_axis_1; +// mod reduce_min_i32_1D; +// mod reduce_min_i32_2D_default; +// mod reduce_min_i32_2D_keepdims; +// mod reduce_min_i32_2D_axis_1; +// mod reduce_min_i8_1D; +// mod reduce_min_i8_2D_default; +// mod reduce_min_i8_2D_keepdims; +// mod reduce_min_i8_2D_axis_1; +// mod reduce_min_u32_1D; +// mod reduce_min_u32_2D_default; +// mod reduce_min_u32_2D_keepdims; +// mod reduce_min_u32_2D_axis_1; +// mod sequence_construct_fp16x16; +// mod sequence_construct_fp8x23; +// mod sequence_construct_i32; +// mod sequence_construct_i8; +// mod sequence_construct_u32; +// mod shrink_hard_fp16x16; +// mod shrink_soft_fp16x16; +// mod shrink_hard_fp8x23; +// mod shrink_soft_fp8x23; +// mod sequence_empty_fp16x16; +// mod sequence_empty_fp8x23; +// mod sequence_empty_i32; +// mod sequence_empty_i8; +// mod sequence_empty_u32; +// mod reduce_mean_fp16x16_1D; +// mod reduce_mean_fp16x16_2D_default; +// mod reduce_mean_fp16x16_2D_keepdims; +// mod reduce_mean_fp16x16_2D_axis_1; +// mod reduce_mean_fp8x23_1D; +// mod reduce_mean_fp8x23_2D_default; +// mod reduce_mean_fp8x23_2D_keepdims; +// mod reduce_mean_fp8x23_2D_axis_1; +// mod reduce_mean_i32_1D; +// mod reduce_mean_i32_2D_default; +// mod reduce_mean_i32_2D_keepdims; +// mod reduce_mean_i32_2D_axis_1; +// mod reduce_mean_i8_1D; +// mod reduce_mean_i8_2D_default; +// mod reduce_mean_i8_2D_keepdims; +// mod reduce_mean_i8_2D_axis_1; +// mod reduce_mean_u32_1D; +// mod reduce_mean_u32_2D_default; +// mod reduce_mean_u32_2D_keepdims; +// mod reduce_mean_u32_2D_axis_1; +// mod pow_fp16x16; +// mod pow_fp16x16_broadcast; +// mod pow_fp8x23; +// mod pow_fp8x23_broadcast; +// mod sequence_erase_u32_positive; +// mod sequence_erase_u32_negative; +// mod sequence_erase_u32_empty; +// mod sequence_erase_fp16x16_positive; +// mod sequence_erase_fp16x16_negative; +// mod sequence_erase_fp16x16_empty; +// mod sequence_erase_fp8x23_positive; +// mod sequence_erase_fp8x23_negative; +// mod sequence_erase_fp8x23_empty; +// mod sequence_erase_i32_positive; +// mod sequence_erase_i32_negative; +// mod sequence_erase_i32_empty; +// mod sequence_erase_i8_positive; +// mod sequence_erase_i8_negative; +// mod sequence_erase_i8_empty; +// mod sequence_insert_fp16x16; +// mod sequence_insert_fp8x23; +// mod sequence_insert_i32; +// mod sequence_insert_i8; +// mod sequence_insert_u32; +// mod concat_from_sequence_fp8x23_new_axis_zero; +// mod concat_from_sequence_fp8x23_new_axis_one; +// mod concat_from_sequence_fp8x23_new_axis_default; +// mod concat_from_sequence_fp16x16_new_axis_zero; +// mod concat_from_sequence_fp16x16_new_axis_one; +// mod concat_from_sequence_fp16x16_new_axis_default; +// mod concat_from_sequence_i32_new_axis_zero; +// mod concat_from_sequence_i32_new_axis_one; +// mod concat_from_sequence_i32_new_axis_default; +// mod concat_from_sequence_i8_new_axis_zero; +// mod concat_from_sequence_i8_new_axis_one; +// mod concat_from_sequence_i8_new_axis_default; +// mod concat_from_sequence_u32_new_axis_zero; +// mod concat_from_sequence_u32_new_axis_one; +// mod concat_from_sequence_u32_new_axis_default; +// mod is_nan_fp16x16; +// mod is_nan_fp8x23; +// mod is_inf_fp16x16; +// mod is_inf_fp8x23; +// mod is_inf_i32; +// mod is_inf_i8; +// mod is_inf_u32; +// mod is_pos_inf_fp16x16; +// mod is_neg_inf_fp16x16; +// mod is_pos_inf_fp8x23; +// mod is_neg_inf_fp8x23; +// mod is_pos_inf_i32; +// mod is_neg_inf_i32; +// mod is_pos_inf_i8; +// mod is_neg_inf_i8; +// mod and_bool; From 97be29bebcb1c24e5ef66905d96447e9ceec971e Mon Sep 17 00:00:00 2001 From: Hakeem Kazeem Date: Thu, 14 Dec 2023 07:28:16 +0100 Subject: [PATCH 02/16] node tests added --- nodegen/node/gather_nd.py | 296 ++++++++++++++++++ src/operators/tensor/math/gather_nd.cairo | 45 +-- tests/nodes.cairo | 14 + .../gather_nd_fp16x16_3d_batch_dims1.cairo | 24 ++ .../input_0.cairo | 41 +++ .../input_1.cairo | 31 ++ .../output_0.cairo | 22 ++ .../gather_nd_fp16x16_3d_batch_dims2.cairo | 24 ++ .../input_0.cairo | 69 ++++ .../input_1.cairo | 31 ++ .../output_0.cairo | 22 ++ .../nodes/gather_nd_fp16x16_3d_default.cairo | 24 ++ .../input_0.cairo | 41 +++ .../input_1.cairo | 40 +++ .../output_0.cairo | 22 ++ .../gather_nd_fp8x23_3d_batch_dims1.cairo | 24 ++ .../input_0.cairo | 41 +++ .../input_1.cairo | 31 ++ .../output_0.cairo | 22 ++ .../gather_nd_fp8x23_3d_batch_dims2.cairo | 24 ++ .../input_0.cairo | 69 ++++ .../input_1.cairo | 31 ++ .../output_0.cairo | 22 ++ tests/nodes/gather_nd_fp8x23_3d_default.cairo | 24 ++ .../gather_nd_fp8x23_3d_default/input_0.cairo | 41 +++ .../gather_nd_fp8x23_3d_default/input_1.cairo | 40 +++ .../output_0.cairo | 22 ++ .../nodes/gather_nd_i32_3d_batch_dims1.cairo | 24 ++ .../input_0.cairo | 123 ++++++++ .../input_1.cairo | 37 +++ .../output_0.cairo | 21 ++ .../nodes/gather_nd_i32_3d_batch_dims2.cairo | 24 ++ .../input_0.cairo | 69 ++++ .../input_1.cairo | 31 ++ .../output_0.cairo | 22 ++ tests/nodes/gather_nd_i32_3d_default.cairo | 24 ++ .../gather_nd_i32_3d_default/input_0.cairo | 38 +++ .../gather_nd_i32_3d_default/input_1.cairo | 18 ++ .../gather_nd_i32_3d_default/output_0.cairo | 22 ++ tests/nodes/gather_nd_i8_3d_batch_dims1.cairo | 24 ++ .../gather_nd_i8_3d_batch_dims1/input_0.cairo | 22 ++ .../gather_nd_i8_3d_batch_dims1/input_1.cairo | 15 + .../output_0.cairo | 15 + tests/nodes/gather_nd_i8_3d_default.cairo | 24 ++ .../gather_nd_i8_3d_default/input_0.cairo | 22 ++ .../gather_nd_i8_3d_default/input_1.cairo | 18 ++ .../gather_nd_i8_3d_default/output_0.cairo | 15 + tests/nodes/gather_nd_u32_batch_dims1.cairo | 22 ++ .../gather_nd_u32_batch_dims1/input_0.cairo | 122 ++++++++ .../gather_nd_u32_batch_dims1/input_1.cairo | 31 ++ .../gather_nd_u32_batch_dims1/output_0.cairo | 40 +++ tests/nodes/gather_nd_u32_batch_dims2.cairo | 22 ++ .../gather_nd_u32_batch_dims2/input_0.cairo | 122 ++++++++ .../gather_nd_u32_batch_dims2/input_1.cairo | 31 ++ .../gather_nd_u32_batch_dims2/output_0.cairo | 21 ++ tests/nodes/gather_nd_u32_default.cairo | 22 ++ .../nodes/gather_nd_u32_default/input_0.cairo | 122 ++++++++ .../nodes/gather_nd_u32_default/input_1.cairo | 31 ++ .../gather_nd_u32_default/output_0.cairo | 122 ++++++++ 59 files changed, 2421 insertions(+), 32 deletions(-) create mode 100644 nodegen/node/gather_nd.py create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_default.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo create mode 100644 tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_default.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo create mode 100644 tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims1.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims2.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_default.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_default/input_0.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_default/input_1.cairo create mode 100644 tests/nodes/gather_nd_i32_3d_default/output_0.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_batch_dims1.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_default.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_default/input_0.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_default/input_1.cairo create mode 100644 tests/nodes/gather_nd_i8_3d_default/output_0.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims1.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims2.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo create mode 100644 tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo create mode 100644 tests/nodes/gather_nd_u32_default.cairo create mode 100644 tests/nodes/gather_nd_u32_default/input_0.cairo create mode 100644 tests/nodes/gather_nd_u32_default/input_1.cairo create mode 100644 tests/nodes/gather_nd_u32_default/output_0.cairo diff --git a/nodegen/node/gather_nd.py b/nodegen/node/gather_nd.py new file mode 100644 index 000000000..7ba5d937f --- /dev/null +++ b/nodegen/node/gather_nd.py @@ -0,0 +1,296 @@ +import numpy as np +from nodegen.node import RunAll +from ..helpers import make_test, to_fp, Tensor, Dtype, FixedImpl, Trait + +def gather_nd_impl( + data: np.ndarray, indices: np.ndarray, batch_dims: int +) -> np.ndarray: + # Note the data rank - will be reused multiple times later + data_rank = len(data.shape) + + # Check input tensors' shape/rank condition + assert indices.shape[-1] <= data_rank + + # The list of data/indice shape of batch_dims + batch_dims_shape = [] + + # The number of elements in the batch_dims for data/indice array + batch_dims_size = 1 + + # Check the shape of indice and data are identicial for batch dims. + for i in range(batch_dims): + batch_dims_shape.append(indices.shape[i]) + batch_dims_size *= indices.shape[i] + + # Compute output of the op as below + + # Compute shape of output array + output_shape = ( + batch_dims_shape + list(indices.shape)[batch_dims:-1] + if (indices.shape[-1] == data_rank - batch_dims) + else batch_dims_shape + + list(indices.shape)[batch_dims:-1] + + list(data.shape)[batch_dims + indices.shape[-1] :] + ) + + # Placeholder for output data + output_data_buffer = [] + + # Flatten 'indices' to 2D array + reshaped_indices = indices.reshape(batch_dims_size, -1, indices.shape[-1]) + + # Flatten 'data' to array of shape (batch_dim_size, data.shape[batch_dimes:]) + reshaped_data = data.reshape((batch_dims_size,) + data.shape[batch_dims:]) + + # gather each scalar value from 'data' + for batch_dim in range(reshaped_indices.shape[0]): + for outer_dim in range(reshaped_indices.shape[1]): + gather_index = tuple(reshaped_indices[batch_dim][outer_dim]) + output_data_buffer.append(reshaped_data[(batch_dim, *gather_index)]) + return np.asarray(output_data_buffer, dtype=data.dtype).reshape(output_shape) + + +class Gather_nd(RunAll): + + @staticmethod + def gather_nd_fp16x16(): + def gather_nd_3D(): + def default(): + x1 = np.arange(0,27).reshape(3,3,3).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,3)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=0) + + x1 = Tensor(Dtype.FP16x16, x1.shape, to_fp(x1.flatten(), FixedImpl.FP16x16)) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.FP16x16, y.shape, to_fp( + y.flatten(), FixedImpl.FP16x16)) + + name = "gather_nd_fp16x16_3d_default" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0))", + name= name) + + def batch_dims1(): + x1 = np.arange(0,27).reshape(3,3,3).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=1) + + x1 = Tensor(Dtype.FP16x16, x1.shape, to_fp(x1.flatten(), FixedImpl.FP16x16)) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.FP16x16, y.shape, to_fp( + y.flatten(), FixedImpl.FP16x16)) + + name = "gather_nd_fp16x16_3d_batch_dims1" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1))", + name= name) + + def batch_dims2(): + x1 = np.arange(0,54).reshape(3,3,3,2).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=2) + + x1 = Tensor(Dtype.FP16x16, x1.shape, to_fp(x1.flatten(), FixedImpl.FP16x16)) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.FP16x16, y.shape, to_fp( + y.flatten(), FixedImpl.FP16x16)) + + name = "gather_nd_fp16x16_3d_batch_dims2" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2))", + name= name) + + default() + batch_dims1() + batch_dims2() + gather_nd_3D() + + + @staticmethod + def gather_nd_fp8x23(): + def gather_nd_3D(): + def default(): + x1 = np.arange(0,27).reshape(3,3,3).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,3)).astype(np.int64) + y = gather_nd_impl(x1, x2, batch_dims=0) + + x1 = Tensor(Dtype.FP8x23, x1.shape, to_fp(x1.flatten(), FixedImpl.FP8x23)) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.FP8x23, y.shape, to_fp(y.flatten(), FixedImpl.FP8x23)) + + name = "gather_nd_fp8x23_3d_default" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0))", + name= name) + + def batch_dims1(): + x1 = np.arange(0,27).reshape(3,3,3).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.int64) + y = gather_nd_impl(x1, x2, batch_dims=1) + + x1 = Tensor(Dtype.FP8x23, x1.shape, to_fp(x1.flatten(), FixedImpl.FP8x23)) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.FP8x23, y.shape, to_fp(y.flatten(), FixedImpl.FP8x23)) + + name = "gather_nd_fp8x23_3d_batch_dims1" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1))", + name= name) + + def batch_dims2(): + x1 = np.arange(0,54).reshape(3,3,3,2).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=2) + + x1 = Tensor(Dtype.FP8x23, x1.shape, to_fp(x1.flatten(), FixedImpl.FP8x23)) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.FP8x23, y.shape, to_fp(y.flatten(), FixedImpl.FP8x23)) + + name = "gather_nd_fp8x23_3d_batch_dims2" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2))", + name= name) + + default() + batch_dims1() + batch_dims2() + gather_nd_3D() + + + @staticmethod + def gather_nd_i8(): + def gather_nd_3D(): + def default(): + x1 = np.arange(0,9).reshape(3,3).astype(np.int8) + x2 = np.random.randint(low = 0,high=2, size=(3,2)).astype(np.int8) + y = gather_nd_impl(x1, x2, batch_dims=0) + + x1 = Tensor(Dtype.I8, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.I8, y.shape, y.flatten()) + + name = "gather_nd_i8_3d_default" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0))", + name= name) + + def batch_dims1(): + x1 = np.arange(0,9).reshape(3,3).astype(np.int8) + x2 = np.random.randint(low = 0,high=2, size=(3,1)).astype(np.int8) + y = gather_nd_impl(x1, x2, batch_dims=1) + + x1 = Tensor(Dtype.I8, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.I8, y.shape, y.flatten()) + + name = "gather_nd_i8_3d_batch_dims1" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1))", + name= name) + + + default() + batch_dims1() + gather_nd_3D() + + + @staticmethod + def gather_nd_i32(): + def gather_nd_3D(): + def default(): + x1 = np.arange(0,24).reshape(4,2,3).astype(np.int32) + x2 = np.random.randint(low = 0,high=2, size=(3,2)).astype(np.int32) + y = gather_nd_impl(x1, x2, batch_dims=0) + + x1 = Tensor(Dtype.I32, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.I32, y.shape, y.flatten()) + + name = "gather_nd_i32_3d_default" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0))", + name= name) + + def batch_dims1(): + x1 = np.arange(0,108).reshape(4,3,3,3).astype(np.int32) + x2 = np.random.randint(low = 0,high=3, size=(4,2,3)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=1) + + x1 = Tensor(Dtype.I32, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.I32, y.shape, y.flatten()) + + name = "gather_nd_i32_3d_batch_dims1" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1))", + name= name) + + def batch_dims2(): + x1 = np.arange(0,54).reshape(3,3,3,2).astype(np.int64) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=2) + + x1 = Tensor(Dtype.I32, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.I32, y.shape, y.flatten()) + + name = "gather_nd_i32_3d_batch_dims2" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2))", + name= name) + + default() + batch_dims1() + batch_dims2() + gather_nd_3D() + + @staticmethod + def gather_nd_u32(): + def gather_nd_3D(): + def default(): + x1 = np.arange(0,108).reshape(3,3,4,3).astype(np.int32) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=0) + + x1 = Tensor(Dtype.U32, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.U32, y.shape, y.flatten()) + + name = "gather_nd_u32_default" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0))", + name= name) + + def batch_dims1(): + x1 = np.arange(0,108).reshape(3,3,4,3).astype(np.int32) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=1) + + x1 = Tensor(Dtype.U32, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.U32, y.shape, y.flatten()) + + name = "gather_nd_u32_batch_dims1" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1))", + name= name) + + def batch_dims2(): + x1 = np.arange(0,108).reshape(3,3,4,3).astype(np.int32) + x2 = np.random.randint(low = 0,high=2, size=(3,3,2)).astype(np.uint32) + y = gather_nd_impl(x1, x2, batch_dims=2) + + x1 = Tensor(Dtype.U32, x1.shape, x1.flatten()) + x2 = Tensor(Dtype.U32, x2.shape, x2.flatten()) + y = Tensor(Dtype.U32, y.shape, y.flatten()) + + name = "gather_nd_u32_batch_dims2" + make_test( + inputs = [x1, x2], output = y, func_sig = "input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2))", + name= name) + + + default() + batch_dims1() + batch_dims2() + gather_nd_3D() \ No newline at end of file diff --git a/src/operators/tensor/math/gather_nd.cairo b/src/operators/tensor/math/gather_nd.cairo index 93c56b402..04dafe2c2 100644 --- a/src/operators/tensor/math/gather_nd.cairo +++ b/src/operators/tensor/math/gather_nd.cairo @@ -13,7 +13,7 @@ use orion::numbers::NumberTrait; use orion::operators::tensor::U32TensorPartialEq; use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor}; -/// Cf: TensorTrait::gather docstring +/// Cf: TensorTrait::gather_nd docstring fn gather_nd< T, impl TTensorTrait: TensorTrait, @@ -85,7 +85,6 @@ fn gather_nd< if (ind >= (batch_dims + *indices_shape_last)) { output_shape.append(*val); } - // total_data_len *= *val; ind += 1; }, Option::None(_) => { break; } @@ -95,6 +94,7 @@ fn gather_nd< let mut ind = 0; let mut multiple = 1; + let mut incrementer = 1; let mut data_shape_clone = data_shape.clone(); loop { match data_shape_clone.pop_front() { @@ -103,18 +103,7 @@ fn gather_nd< multiple *= *val; multiple_data_len.append(multiple); } - ind += 1; - }, - Option::None(_) => { break; } - }; - }; - let mut ind = 0; - let mut incrementer = 1; - let mut data_shape_clone = data_shape.clone(); - loop { - match data_shape_clone.pop_front() { - Option::Some(val) => { if (ind >= batch_dims + *indices_shape_last) { incrementer *= *val; } @@ -124,7 +113,6 @@ fn gather_nd< }; }; - let mut ind = 0; let mut indices_shape_clone = indices_shape.clone(); let mut breaker = 1; @@ -140,14 +128,10 @@ fn gather_nd< }; }; - let data_shape_last = data_shape.pop_back().unwrap(); - total_data_len = *multiple_data_len.at(multiple_data_len.len() - 1); let mut data_indices = indices.data; let mut ind = 0; let mut result = 0; - let mut outer_loop = 0; - loop { match data_indices.pop_front() { Option::Some(val) => { @@ -170,7 +154,6 @@ fn gather_nd< }; }; - loop { match index_data.pop_front() { Option::Some(val) => { @@ -181,8 +164,6 @@ fn gather_nd< }; let mut output_tensor = TensorTrait::::new(output_shape.span(), output_data.span()); - - // let mut output_tensor = TensorTrait::::new(*self.shape, *self.data); return output_tensor; } @@ -367,19 +348,19 @@ fn indices_333() -> Tensor { #[test] #[available_gas(20000000000)] fn test_gather_elements_default() { - let data = u32_tensor_3x3x3_helper(); - let indices = indices_333(); + let data = data(); + let indices = indices(); - let y = data.gather_nd(indices: indices, batch_dims:Option::Some(1)); + let y = data.gather_nd(indices: indices, batch_dims:Option::Some(0)); let mut output = y.data; - loop { - match output.pop_front() { - Option::Some(val) => { - (*val).print(); - }, - Option::None(_) => { break; } - }; - }; + // loop { + // match output.pop_front() { + // Option::Some(val) => { + // (*val).print(); + // }, + // Option::None(_) => { break; } + // }; + // }; } \ No newline at end of file diff --git a/tests/nodes.cairo b/tests/nodes.cairo index b2371a071..1c76be836 100644 --- a/tests/nodes.cairo +++ b/tests/nodes.cairo @@ -820,3 +820,17 @@ // mod is_pos_inf_i8; // mod is_neg_inf_i8; // mod and_bool; +mod gather_nd_fp16x16_3d_default; +mod gather_nd_fp16x16_3d_batch_dims1; +mod gather_nd_fp16x16_3d_batch_dims2; +mod gather_nd_fp8x23_3d_default; +mod gather_nd_fp8x23_3d_batch_dims1; +mod gather_nd_fp8x23_3d_batch_dims2; +mod gather_nd_i8_3d_default; +mod gather_nd_i8_3d_batch_dims1; +mod gather_nd_i32_3d_default; +mod gather_nd_i32_3d_batch_dims1; +mod gather_nd_i32_3d_batch_dims2; +mod gather_nd_u32_default; +mod gather_nd_u32_batch_dims1; +mod gather_nd_u32_batch_dims2; diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo new file mode 100644 index 000000000..f0d927960 --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::FP16x16Tensor; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::FP16x16TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_fp16x16_3d_batch_dims1() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo new file mode 100644 index 000000000..e6f14fe6d --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo @@ -0,0 +1,41 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::{FixedTrait, FP16x16}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP16x16 { mag: 0, sign: false }); + data.append(FP16x16 { mag: 65536, sign: false }); + data.append(FP16x16 { mag: 131072, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 262144, sign: false }); + data.append(FP16x16 { mag: 327680, sign: false }); + data.append(FP16x16 { mag: 393216, sign: false }); + data.append(FP16x16 { mag: 458752, sign: false }); + data.append(FP16x16 { mag: 524288, sign: false }); + data.append(FP16x16 { mag: 589824, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 720896, sign: false }); + data.append(FP16x16 { mag: 786432, sign: false }); + data.append(FP16x16 { mag: 851968, sign: false }); + data.append(FP16x16 { mag: 917504, sign: false }); + data.append(FP16x16 { mag: 983040, sign: false }); + data.append(FP16x16 { mag: 1048576, sign: false }); + data.append(FP16x16 { mag: 1114112, sign: false }); + data.append(FP16x16 { mag: 1179648, sign: false }); + data.append(FP16x16 { mag: 1245184, sign: false }); + data.append(FP16x16 { mag: 1310720, sign: false }); + data.append(FP16x16 { mag: 1376256, sign: false }); + data.append(FP16x16 { mag: 1441792, sign: false }); + data.append(FP16x16 { mag: 1507328, sign: false }); + data.append(FP16x16 { mag: 1572864, sign: false }); + data.append(FP16x16 { mag: 1638400, sign: false }); + data.append(FP16x16 { mag: 1703936, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo new file mode 100644 index 000000000..a7a5c0d1f --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo new file mode 100644 index 000000000..8a0d2745f --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::{FixedTrait, FP16x16}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 65536, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 589824, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 1245184, sign: false }); + data.append(FP16x16 { mag: 1245184, sign: false }); + data.append(FP16x16 { mag: 1376256, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo new file mode 100644 index 000000000..38abba404 --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::FP16x16Tensor; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::FP16x16TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_fp16x16_3d_batch_dims2() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo new file mode 100644 index 000000000..369c90734 --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo @@ -0,0 +1,69 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::{FixedTrait, FP16x16}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(FP16x16 { mag: 0, sign: false }); + data.append(FP16x16 { mag: 65536, sign: false }); + data.append(FP16x16 { mag: 131072, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 262144, sign: false }); + data.append(FP16x16 { mag: 327680, sign: false }); + data.append(FP16x16 { mag: 393216, sign: false }); + data.append(FP16x16 { mag: 458752, sign: false }); + data.append(FP16x16 { mag: 524288, sign: false }); + data.append(FP16x16 { mag: 589824, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 720896, sign: false }); + data.append(FP16x16 { mag: 786432, sign: false }); + data.append(FP16x16 { mag: 851968, sign: false }); + data.append(FP16x16 { mag: 917504, sign: false }); + data.append(FP16x16 { mag: 983040, sign: false }); + data.append(FP16x16 { mag: 1048576, sign: false }); + data.append(FP16x16 { mag: 1114112, sign: false }); + data.append(FP16x16 { mag: 1179648, sign: false }); + data.append(FP16x16 { mag: 1245184, sign: false }); + data.append(FP16x16 { mag: 1310720, sign: false }); + data.append(FP16x16 { mag: 1376256, sign: false }); + data.append(FP16x16 { mag: 1441792, sign: false }); + data.append(FP16x16 { mag: 1507328, sign: false }); + data.append(FP16x16 { mag: 1572864, sign: false }); + data.append(FP16x16 { mag: 1638400, sign: false }); + data.append(FP16x16 { mag: 1703936, sign: false }); + data.append(FP16x16 { mag: 1769472, sign: false }); + data.append(FP16x16 { mag: 1835008, sign: false }); + data.append(FP16x16 { mag: 1900544, sign: false }); + data.append(FP16x16 { mag: 1966080, sign: false }); + data.append(FP16x16 { mag: 2031616, sign: false }); + data.append(FP16x16 { mag: 2097152, sign: false }); + data.append(FP16x16 { mag: 2162688, sign: false }); + data.append(FP16x16 { mag: 2228224, sign: false }); + data.append(FP16x16 { mag: 2293760, sign: false }); + data.append(FP16x16 { mag: 2359296, sign: false }); + data.append(FP16x16 { mag: 2424832, sign: false }); + data.append(FP16x16 { mag: 2490368, sign: false }); + data.append(FP16x16 { mag: 2555904, sign: false }); + data.append(FP16x16 { mag: 2621440, sign: false }); + data.append(FP16x16 { mag: 2686976, sign: false }); + data.append(FP16x16 { mag: 2752512, sign: false }); + data.append(FP16x16 { mag: 2818048, sign: false }); + data.append(FP16x16 { mag: 2883584, sign: false }); + data.append(FP16x16 { mag: 2949120, sign: false }); + data.append(FP16x16 { mag: 3014656, sign: false }); + data.append(FP16x16 { mag: 3080192, sign: false }); + data.append(FP16x16 { mag: 3145728, sign: false }); + data.append(FP16x16 { mag: 3211264, sign: false }); + data.append(FP16x16 { mag: 3276800, sign: false }); + data.append(FP16x16 { mag: 3342336, sign: false }); + data.append(FP16x16 { mag: 3407872, sign: false }); + data.append(FP16x16 { mag: 3473408, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo new file mode 100644 index 000000000..705a6bb4c --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo new file mode 100644 index 000000000..0e228d8fc --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::{FixedTrait, FP16x16}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 524288, sign: false }); + data.append(FP16x16 { mag: 917504, sign: false }); + data.append(FP16x16 { mag: 1310720, sign: false }); + data.append(FP16x16 { mag: 1703936, sign: false }); + data.append(FP16x16 { mag: 2097152, sign: false }); + data.append(FP16x16 { mag: 2424832, sign: false }); + data.append(FP16x16 { mag: 2752512, sign: false }); + data.append(FP16x16 { mag: 3145728, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_default.cairo b/tests/nodes/gather_nd_fp16x16_3d_default.cairo new file mode 100644 index 000000000..563fa2ebd --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_default.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::FP16x16Tensor; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::FP16x16TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_fp16x16_3d_default() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo new file mode 100644 index 000000000..e6f14fe6d --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo @@ -0,0 +1,41 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::{FixedTrait, FP16x16}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP16x16 { mag: 0, sign: false }); + data.append(FP16x16 { mag: 65536, sign: false }); + data.append(FP16x16 { mag: 131072, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 262144, sign: false }); + data.append(FP16x16 { mag: 327680, sign: false }); + data.append(FP16x16 { mag: 393216, sign: false }); + data.append(FP16x16 { mag: 458752, sign: false }); + data.append(FP16x16 { mag: 524288, sign: false }); + data.append(FP16x16 { mag: 589824, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 720896, sign: false }); + data.append(FP16x16 { mag: 786432, sign: false }); + data.append(FP16x16 { mag: 851968, sign: false }); + data.append(FP16x16 { mag: 917504, sign: false }); + data.append(FP16x16 { mag: 983040, sign: false }); + data.append(FP16x16 { mag: 1048576, sign: false }); + data.append(FP16x16 { mag: 1114112, sign: false }); + data.append(FP16x16 { mag: 1179648, sign: false }); + data.append(FP16x16 { mag: 1245184, sign: false }); + data.append(FP16x16 { mag: 1310720, sign: false }); + data.append(FP16x16 { mag: 1376256, sign: false }); + data.append(FP16x16 { mag: 1441792, sign: false }); + data.append(FP16x16 { mag: 1507328, sign: false }); + data.append(FP16x16 { mag: 1572864, sign: false }); + data.append(FP16x16 { mag: 1638400, sign: false }); + data.append(FP16x16 { mag: 1703936, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo b/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo new file mode 100644 index 000000000..3e1010521 --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo @@ -0,0 +1,40 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo new file mode 100644 index 000000000..0e047d322 --- /dev/null +++ b/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::{FixedTrait, FP16x16}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP16x16 { mag: 65536, sign: false }); + data.append(FP16x16 { mag: 786432, sign: false }); + data.append(FP16x16 { mag: 0, sign: false }); + data.append(FP16x16 { mag: 262144, sign: false }); + data.append(FP16x16 { mag: 851968, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 0, sign: false }); + data.append(FP16x16 { mag: 0, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo new file mode 100644 index 000000000..bd1c34722 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::FP8x23Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::FP8x23TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_fp8x23_3d_batch_dims1() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo new file mode 100644 index 000000000..de5867b1f --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo @@ -0,0 +1,41 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP8x23Tensor; +use orion::numbers::{FixedTrait, FP8x23}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 8388608, sign: false }); + data.append(FP8x23 { mag: 16777216, sign: false }); + data.append(FP8x23 { mag: 25165824, sign: false }); + data.append(FP8x23 { mag: 33554432, sign: false }); + data.append(FP8x23 { mag: 41943040, sign: false }); + data.append(FP8x23 { mag: 50331648, sign: false }); + data.append(FP8x23 { mag: 58720256, sign: false }); + data.append(FP8x23 { mag: 67108864, sign: false }); + data.append(FP8x23 { mag: 75497472, sign: false }); + data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 92274688, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); + data.append(FP8x23 { mag: 117440512, sign: false }); + data.append(FP8x23 { mag: 125829120, sign: false }); + data.append(FP8x23 { mag: 134217728, sign: false }); + data.append(FP8x23 { mag: 142606336, sign: false }); + data.append(FP8x23 { mag: 150994944, sign: false }); + data.append(FP8x23 { mag: 159383552, sign: false }); + data.append(FP8x23 { mag: 167772160, sign: false }); + data.append(FP8x23 { mag: 176160768, sign: false }); + data.append(FP8x23 { mag: 184549376, sign: false }); + data.append(FP8x23 { mag: 192937984, sign: false }); + data.append(FP8x23 { mag: 201326592, sign: false }); + data.append(FP8x23 { mag: 209715200, sign: false }); + data.append(FP8x23 { mag: 218103808, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo new file mode 100644 index 000000000..a02020b98 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo new file mode 100644 index 000000000..8a13af67a --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP8x23Tensor; +use orion::numbers::{FixedTrait, FP8x23}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP8x23 { mag: 33554432, sign: false }); + data.append(FP8x23 { mag: 25165824, sign: false }); + data.append(FP8x23 { mag: 8388608, sign: false }); + data.append(FP8x23 { mag: 75497472, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 184549376, sign: false }); + data.append(FP8x23 { mag: 184549376, sign: false }); + data.append(FP8x23 { mag: 176160768, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo new file mode 100644 index 000000000..ab1ae82b3 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::FP8x23Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::FP8x23TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_fp8x23_3d_batch_dims2() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo new file mode 100644 index 000000000..a85fdd871 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo @@ -0,0 +1,69 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP8x23Tensor; +use orion::numbers::{FixedTrait, FP8x23}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 8388608, sign: false }); + data.append(FP8x23 { mag: 16777216, sign: false }); + data.append(FP8x23 { mag: 25165824, sign: false }); + data.append(FP8x23 { mag: 33554432, sign: false }); + data.append(FP8x23 { mag: 41943040, sign: false }); + data.append(FP8x23 { mag: 50331648, sign: false }); + data.append(FP8x23 { mag: 58720256, sign: false }); + data.append(FP8x23 { mag: 67108864, sign: false }); + data.append(FP8x23 { mag: 75497472, sign: false }); + data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 92274688, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); + data.append(FP8x23 { mag: 117440512, sign: false }); + data.append(FP8x23 { mag: 125829120, sign: false }); + data.append(FP8x23 { mag: 134217728, sign: false }); + data.append(FP8x23 { mag: 142606336, sign: false }); + data.append(FP8x23 { mag: 150994944, sign: false }); + data.append(FP8x23 { mag: 159383552, sign: false }); + data.append(FP8x23 { mag: 167772160, sign: false }); + data.append(FP8x23 { mag: 176160768, sign: false }); + data.append(FP8x23 { mag: 184549376, sign: false }); + data.append(FP8x23 { mag: 192937984, sign: false }); + data.append(FP8x23 { mag: 201326592, sign: false }); + data.append(FP8x23 { mag: 209715200, sign: false }); + data.append(FP8x23 { mag: 218103808, sign: false }); + data.append(FP8x23 { mag: 226492416, sign: false }); + data.append(FP8x23 { mag: 234881024, sign: false }); + data.append(FP8x23 { mag: 243269632, sign: false }); + data.append(FP8x23 { mag: 251658240, sign: false }); + data.append(FP8x23 { mag: 260046848, sign: false }); + data.append(FP8x23 { mag: 268435456, sign: false }); + data.append(FP8x23 { mag: 276824064, sign: false }); + data.append(FP8x23 { mag: 285212672, sign: false }); + data.append(FP8x23 { mag: 293601280, sign: false }); + data.append(FP8x23 { mag: 301989888, sign: false }); + data.append(FP8x23 { mag: 310378496, sign: false }); + data.append(FP8x23 { mag: 318767104, sign: false }); + data.append(FP8x23 { mag: 327155712, sign: false }); + data.append(FP8x23 { mag: 335544320, sign: false }); + data.append(FP8x23 { mag: 343932928, sign: false }); + data.append(FP8x23 { mag: 352321536, sign: false }); + data.append(FP8x23 { mag: 360710144, sign: false }); + data.append(FP8x23 { mag: 369098752, sign: false }); + data.append(FP8x23 { mag: 377487360, sign: false }); + data.append(FP8x23 { mag: 385875968, sign: false }); + data.append(FP8x23 { mag: 394264576, sign: false }); + data.append(FP8x23 { mag: 402653184, sign: false }); + data.append(FP8x23 { mag: 411041792, sign: false }); + data.append(FP8x23 { mag: 419430400, sign: false }); + data.append(FP8x23 { mag: 427819008, sign: false }); + data.append(FP8x23 { mag: 436207616, sign: false }); + data.append(FP8x23 { mag: 444596224, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo new file mode 100644 index 000000000..5ac309382 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo new file mode 100644 index 000000000..3beb1dc19 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP8x23Tensor; +use orion::numbers::{FixedTrait, FP8x23}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP8x23 { mag: 16777216, sign: false }); + data.append(FP8x23 { mag: 58720256, sign: false }); + data.append(FP8x23 { mag: 125829120, sign: false }); + data.append(FP8x23 { mag: 167772160, sign: false }); + data.append(FP8x23 { mag: 226492416, sign: false }); + data.append(FP8x23 { mag: 268435456, sign: false }); + data.append(FP8x23 { mag: 301989888, sign: false }); + data.append(FP8x23 { mag: 360710144, sign: false }); + data.append(FP8x23 { mag: 411041792, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_default.cairo b/tests/nodes/gather_nd_fp8x23_3d_default.cairo new file mode 100644 index 000000000..066a43e06 --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_default.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::FP8x23Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::FP8x23TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_fp8x23_3d_default() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo new file mode 100644 index 000000000..de5867b1f --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo @@ -0,0 +1,41 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP8x23Tensor; +use orion::numbers::{FixedTrait, FP8x23}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 8388608, sign: false }); + data.append(FP8x23 { mag: 16777216, sign: false }); + data.append(FP8x23 { mag: 25165824, sign: false }); + data.append(FP8x23 { mag: 33554432, sign: false }); + data.append(FP8x23 { mag: 41943040, sign: false }); + data.append(FP8x23 { mag: 50331648, sign: false }); + data.append(FP8x23 { mag: 58720256, sign: false }); + data.append(FP8x23 { mag: 67108864, sign: false }); + data.append(FP8x23 { mag: 75497472, sign: false }); + data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 92274688, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); + data.append(FP8x23 { mag: 117440512, sign: false }); + data.append(FP8x23 { mag: 125829120, sign: false }); + data.append(FP8x23 { mag: 134217728, sign: false }); + data.append(FP8x23 { mag: 142606336, sign: false }); + data.append(FP8x23 { mag: 150994944, sign: false }); + data.append(FP8x23 { mag: 159383552, sign: false }); + data.append(FP8x23 { mag: 167772160, sign: false }); + data.append(FP8x23 { mag: 176160768, sign: false }); + data.append(FP8x23 { mag: 184549376, sign: false }); + data.append(FP8x23 { mag: 192937984, sign: false }); + data.append(FP8x23 { mag: 201326592, sign: false }); + data.append(FP8x23 { mag: 209715200, sign: false }); + data.append(FP8x23 { mag: 218103808, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo b/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo new file mode 100644 index 000000000..2a874516f --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo @@ -0,0 +1,40 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo new file mode 100644 index 000000000..3677207fd --- /dev/null +++ b/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::FP8x23Tensor; +use orion::numbers::{FixedTrait, FP8x23}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); + data.append(FP8x23 { mag: 8388608, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 83886080, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo new file mode 100644 index 000000000..a07325f24 --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::I32TensorPartialEq; +use orion::operators::tensor::I32Tensor; +use orion::operators::tensor::U32TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_i32_3d_batch_dims1() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo new file mode 100644 index 000000000..3d9eabb85 --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo @@ -0,0 +1,123 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I32Tensor; +use orion::numbers::{IntegerTrait, i32}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(4); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i32 { mag: 0, sign: false }); + data.append(i32 { mag: 1, sign: false }); + data.append(i32 { mag: 2, sign: false }); + data.append(i32 { mag: 3, sign: false }); + data.append(i32 { mag: 4, sign: false }); + data.append(i32 { mag: 5, sign: false }); + data.append(i32 { mag: 6, sign: false }); + data.append(i32 { mag: 7, sign: false }); + data.append(i32 { mag: 8, sign: false }); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 10, sign: false }); + data.append(i32 { mag: 11, sign: false }); + data.append(i32 { mag: 12, sign: false }); + data.append(i32 { mag: 13, sign: false }); + data.append(i32 { mag: 14, sign: false }); + data.append(i32 { mag: 15, sign: false }); + data.append(i32 { mag: 16, sign: false }); + data.append(i32 { mag: 17, sign: false }); + data.append(i32 { mag: 18, sign: false }); + data.append(i32 { mag: 19, sign: false }); + data.append(i32 { mag: 20, sign: false }); + data.append(i32 { mag: 21, sign: false }); + data.append(i32 { mag: 22, sign: false }); + data.append(i32 { mag: 23, sign: false }); + data.append(i32 { mag: 24, sign: false }); + data.append(i32 { mag: 25, sign: false }); + data.append(i32 { mag: 26, sign: false }); + data.append(i32 { mag: 27, sign: false }); + data.append(i32 { mag: 28, sign: false }); + data.append(i32 { mag: 29, sign: false }); + data.append(i32 { mag: 30, sign: false }); + data.append(i32 { mag: 31, sign: false }); + data.append(i32 { mag: 32, sign: false }); + data.append(i32 { mag: 33, sign: false }); + data.append(i32 { mag: 34, sign: false }); + data.append(i32 { mag: 35, sign: false }); + data.append(i32 { mag: 36, sign: false }); + data.append(i32 { mag: 37, sign: false }); + data.append(i32 { mag: 38, sign: false }); + data.append(i32 { mag: 39, sign: false }); + data.append(i32 { mag: 40, sign: false }); + data.append(i32 { mag: 41, sign: false }); + data.append(i32 { mag: 42, sign: false }); + data.append(i32 { mag: 43, sign: false }); + data.append(i32 { mag: 44, sign: false }); + data.append(i32 { mag: 45, sign: false }); + data.append(i32 { mag: 46, sign: false }); + data.append(i32 { mag: 47, sign: false }); + data.append(i32 { mag: 48, sign: false }); + data.append(i32 { mag: 49, sign: false }); + data.append(i32 { mag: 50, sign: false }); + data.append(i32 { mag: 51, sign: false }); + data.append(i32 { mag: 52, sign: false }); + data.append(i32 { mag: 53, sign: false }); + data.append(i32 { mag: 54, sign: false }); + data.append(i32 { mag: 55, sign: false }); + data.append(i32 { mag: 56, sign: false }); + data.append(i32 { mag: 57, sign: false }); + data.append(i32 { mag: 58, sign: false }); + data.append(i32 { mag: 59, sign: false }); + data.append(i32 { mag: 60, sign: false }); + data.append(i32 { mag: 61, sign: false }); + data.append(i32 { mag: 62, sign: false }); + data.append(i32 { mag: 63, sign: false }); + data.append(i32 { mag: 64, sign: false }); + data.append(i32 { mag: 65, sign: false }); + data.append(i32 { mag: 66, sign: false }); + data.append(i32 { mag: 67, sign: false }); + data.append(i32 { mag: 68, sign: false }); + data.append(i32 { mag: 69, sign: false }); + data.append(i32 { mag: 70, sign: false }); + data.append(i32 { mag: 71, sign: false }); + data.append(i32 { mag: 72, sign: false }); + data.append(i32 { mag: 73, sign: false }); + data.append(i32 { mag: 74, sign: false }); + data.append(i32 { mag: 75, sign: false }); + data.append(i32 { mag: 76, sign: false }); + data.append(i32 { mag: 77, sign: false }); + data.append(i32 { mag: 78, sign: false }); + data.append(i32 { mag: 79, sign: false }); + data.append(i32 { mag: 80, sign: false }); + data.append(i32 { mag: 81, sign: false }); + data.append(i32 { mag: 82, sign: false }); + data.append(i32 { mag: 83, sign: false }); + data.append(i32 { mag: 84, sign: false }); + data.append(i32 { mag: 85, sign: false }); + data.append(i32 { mag: 86, sign: false }); + data.append(i32 { mag: 87, sign: false }); + data.append(i32 { mag: 88, sign: false }); + data.append(i32 { mag: 89, sign: false }); + data.append(i32 { mag: 90, sign: false }); + data.append(i32 { mag: 91, sign: false }); + data.append(i32 { mag: 92, sign: false }); + data.append(i32 { mag: 93, sign: false }); + data.append(i32 { mag: 94, sign: false }); + data.append(i32 { mag: 95, sign: false }); + data.append(i32 { mag: 96, sign: false }); + data.append(i32 { mag: 97, sign: false }); + data.append(i32 { mag: 98, sign: false }); + data.append(i32 { mag: 99, sign: false }); + data.append(i32 { mag: 100, sign: false }); + data.append(i32 { mag: 101, sign: false }); + data.append(i32 { mag: 102, sign: false }); + data.append(i32 { mag: 103, sign: false }); + data.append(i32 { mag: 104, sign: false }); + data.append(i32 { mag: 105, sign: false }); + data.append(i32 { mag: 106, sign: false }); + data.append(i32 { mag: 107, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo new file mode 100644 index 000000000..824761188 --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo @@ -0,0 +1,37 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(4); + shape.append(2); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(2); + data.append(2); + data.append(1); + data.append(0); + data.append(0); + data.append(2); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(2); + data.append(2); + data.append(1); + data.append(2); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(2); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo new file mode 100644 index 000000000..9aa97b9fb --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo @@ -0,0 +1,21 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I32Tensor; +use orion::numbers::{IntegerTrait, i32}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(4); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(i32 { mag: 8, sign: false }); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 48, sign: false }); + data.append(i32 { mag: 36, sign: false }); + data.append(i32 { mag: 62, sign: false }); + data.append(i32 { mag: 69, sign: false }); + data.append(i32 { mag: 90, sign: false }); + data.append(i32 { mag: 87, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo new file mode 100644 index 000000000..bd8621db5 --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::I32TensorPartialEq; +use orion::operators::tensor::I32Tensor; +use orion::operators::tensor::U32TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_i32_3d_batch_dims2() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo new file mode 100644 index 000000000..da4a9cdda --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo @@ -0,0 +1,69 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I32Tensor; +use orion::numbers::{IntegerTrait, i32}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(i32 { mag: 0, sign: false }); + data.append(i32 { mag: 1, sign: false }); + data.append(i32 { mag: 2, sign: false }); + data.append(i32 { mag: 3, sign: false }); + data.append(i32 { mag: 4, sign: false }); + data.append(i32 { mag: 5, sign: false }); + data.append(i32 { mag: 6, sign: false }); + data.append(i32 { mag: 7, sign: false }); + data.append(i32 { mag: 8, sign: false }); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 10, sign: false }); + data.append(i32 { mag: 11, sign: false }); + data.append(i32 { mag: 12, sign: false }); + data.append(i32 { mag: 13, sign: false }); + data.append(i32 { mag: 14, sign: false }); + data.append(i32 { mag: 15, sign: false }); + data.append(i32 { mag: 16, sign: false }); + data.append(i32 { mag: 17, sign: false }); + data.append(i32 { mag: 18, sign: false }); + data.append(i32 { mag: 19, sign: false }); + data.append(i32 { mag: 20, sign: false }); + data.append(i32 { mag: 21, sign: false }); + data.append(i32 { mag: 22, sign: false }); + data.append(i32 { mag: 23, sign: false }); + data.append(i32 { mag: 24, sign: false }); + data.append(i32 { mag: 25, sign: false }); + data.append(i32 { mag: 26, sign: false }); + data.append(i32 { mag: 27, sign: false }); + data.append(i32 { mag: 28, sign: false }); + data.append(i32 { mag: 29, sign: false }); + data.append(i32 { mag: 30, sign: false }); + data.append(i32 { mag: 31, sign: false }); + data.append(i32 { mag: 32, sign: false }); + data.append(i32 { mag: 33, sign: false }); + data.append(i32 { mag: 34, sign: false }); + data.append(i32 { mag: 35, sign: false }); + data.append(i32 { mag: 36, sign: false }); + data.append(i32 { mag: 37, sign: false }); + data.append(i32 { mag: 38, sign: false }); + data.append(i32 { mag: 39, sign: false }); + data.append(i32 { mag: 40, sign: false }); + data.append(i32 { mag: 41, sign: false }); + data.append(i32 { mag: 42, sign: false }); + data.append(i32 { mag: 43, sign: false }); + data.append(i32 { mag: 44, sign: false }); + data.append(i32 { mag: 45, sign: false }); + data.append(i32 { mag: 46, sign: false }); + data.append(i32 { mag: 47, sign: false }); + data.append(i32 { mag: 48, sign: false }); + data.append(i32 { mag: 49, sign: false }); + data.append(i32 { mag: 50, sign: false }); + data.append(i32 { mag: 51, sign: false }); + data.append(i32 { mag: 52, sign: false }); + data.append(i32 { mag: 53, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo new file mode 100644 index 000000000..f2fed8cce --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo new file mode 100644 index 000000000..dc9100d0b --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I32Tensor; +use orion::numbers::{IntegerTrait, i32}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i32 { mag: 1, sign: false }); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 12, sign: false }); + data.append(i32 { mag: 18, sign: false }); + data.append(i32 { mag: 24, sign: false }); + data.append(i32 { mag: 30, sign: false }); + data.append(i32 { mag: 36, sign: false }); + data.append(i32 { mag: 42, sign: false }); + data.append(i32 { mag: 48, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_default.cairo b/tests/nodes/gather_nd_i32_3d_default.cairo new file mode 100644 index 000000000..8f2af98a2 --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_default.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::I32TensorPartialEq; +use orion::operators::tensor::I32Tensor; +use orion::operators::tensor::U32TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_i32_3d_default() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_i32_3d_default/input_0.cairo b/tests/nodes/gather_nd_i32_3d_default/input_0.cairo new file mode 100644 index 000000000..e96796beb --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_default/input_0.cairo @@ -0,0 +1,38 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I32Tensor; +use orion::numbers::{IntegerTrait, i32}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(4); + shape.append(2); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i32 { mag: 0, sign: false }); + data.append(i32 { mag: 1, sign: false }); + data.append(i32 { mag: 2, sign: false }); + data.append(i32 { mag: 3, sign: false }); + data.append(i32 { mag: 4, sign: false }); + data.append(i32 { mag: 5, sign: false }); + data.append(i32 { mag: 6, sign: false }); + data.append(i32 { mag: 7, sign: false }); + data.append(i32 { mag: 8, sign: false }); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 10, sign: false }); + data.append(i32 { mag: 11, sign: false }); + data.append(i32 { mag: 12, sign: false }); + data.append(i32 { mag: 13, sign: false }); + data.append(i32 { mag: 14, sign: false }); + data.append(i32 { mag: 15, sign: false }); + data.append(i32 { mag: 16, sign: false }); + data.append(i32 { mag: 17, sign: false }); + data.append(i32 { mag: 18, sign: false }); + data.append(i32 { mag: 19, sign: false }); + data.append(i32 { mag: 20, sign: false }); + data.append(i32 { mag: 21, sign: false }); + data.append(i32 { mag: 22, sign: false }); + data.append(i32 { mag: 23, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_default/input_1.cairo b/tests/nodes/gather_nd_i32_3d_default/input_1.cairo new file mode 100644 index 000000000..684a6a094 --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_default/input_1.cairo @@ -0,0 +1,18 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i32_3d_default/output_0.cairo b/tests/nodes/gather_nd_i32_3d_default/output_0.cairo new file mode 100644 index 000000000..a8342bd9b --- /dev/null +++ b/tests/nodes/gather_nd_i32_3d_default/output_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I32Tensor; +use orion::numbers::{IntegerTrait, i32}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 10, sign: false }); + data.append(i32 { mag: 11, sign: false }); + data.append(i32 { mag: 3, sign: false }); + data.append(i32 { mag: 4, sign: false }); + data.append(i32 { mag: 5, sign: false }); + data.append(i32 { mag: 6, sign: false }); + data.append(i32 { mag: 7, sign: false }); + data.append(i32 { mag: 8, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo new file mode 100644 index 000000000..e733ee9db --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::I8Tensor; +use orion::operators::tensor::I8TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_i8_3d_batch_dims1() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo new file mode 100644 index 000000000..500932fc7 --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I8Tensor; +use orion::numbers::{IntegerTrait, i8}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i8 { mag: 0, sign: false }); + data.append(i8 { mag: 1, sign: false }); + data.append(i8 { mag: 2, sign: false }); + data.append(i8 { mag: 3, sign: false }); + data.append(i8 { mag: 4, sign: false }); + data.append(i8 { mag: 5, sign: false }); + data.append(i8 { mag: 6, sign: false }); + data.append(i8 { mag: 7, sign: false }); + data.append(i8 { mag: 8, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo new file mode 100644 index 000000000..8a43b62a1 --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo @@ -0,0 +1,15 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(1); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(0); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo new file mode 100644 index 000000000..6d19d1334 --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo @@ -0,0 +1,15 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I8Tensor; +use orion::numbers::{IntegerTrait, i8}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i8 { mag: 1, sign: false }); + data.append(i8 { mag: 3, sign: false }); + data.append(i8 { mag: 6, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i8_3d_default.cairo b/tests/nodes/gather_nd_i8_3d_default.cairo new file mode 100644 index 000000000..d4022ced4 --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_default.cairo @@ -0,0 +1,24 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; +use orion::operators::tensor::I8Tensor; +use orion::operators::tensor::I8TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_i8_3d_default() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_i8_3d_default/input_0.cairo b/tests/nodes/gather_nd_i8_3d_default/input_0.cairo new file mode 100644 index 000000000..500932fc7 --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_default/input_0.cairo @@ -0,0 +1,22 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I8Tensor; +use orion::numbers::{IntegerTrait, i8}; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i8 { mag: 0, sign: false }); + data.append(i8 { mag: 1, sign: false }); + data.append(i8 { mag: 2, sign: false }); + data.append(i8 { mag: 3, sign: false }); + data.append(i8 { mag: 4, sign: false }); + data.append(i8 { mag: 5, sign: false }); + data.append(i8 { mag: 6, sign: false }); + data.append(i8 { mag: 7, sign: false }); + data.append(i8 { mag: 8, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i8_3d_default/input_1.cairo b/tests/nodes/gather_nd_i8_3d_default/input_1.cairo new file mode 100644 index 000000000..f0cbc41aa --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_default/input_1.cairo @@ -0,0 +1,18 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_i8_3d_default/output_0.cairo b/tests/nodes/gather_nd_i8_3d_default/output_0.cairo new file mode 100644 index 000000000..6788630df --- /dev/null +++ b/tests/nodes/gather_nd_i8_3d_default/output_0.cairo @@ -0,0 +1,15 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::I8Tensor; +use orion::numbers::{IntegerTrait, i8}; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(i8 { mag: 0, sign: false }); + data.append(i8 { mag: 4, sign: false }); + data.append(i8 { mag: 4, sign: false }); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_batch_dims1.cairo b/tests/nodes/gather_nd_u32_batch_dims1.cairo new file mode 100644 index 000000000..94fea41f5 --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims1.cairo @@ -0,0 +1,22 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_u32_batch_dims1() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo new file mode 100644 index 000000000..409b07da6 --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo @@ -0,0 +1,122 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(4); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(24); + data.append(25); + data.append(26); + data.append(27); + data.append(28); + data.append(29); + data.append(30); + data.append(31); + data.append(32); + data.append(33); + data.append(34); + data.append(35); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(48); + data.append(49); + data.append(50); + data.append(51); + data.append(52); + data.append(53); + data.append(54); + data.append(55); + data.append(56); + data.append(57); + data.append(58); + data.append(59); + data.append(60); + data.append(61); + data.append(62); + data.append(63); + data.append(64); + data.append(65); + data.append(66); + data.append(67); + data.append(68); + data.append(69); + data.append(70); + data.append(71); + data.append(72); + data.append(73); + data.append(74); + data.append(75); + data.append(76); + data.append(77); + data.append(78); + data.append(79); + data.append(80); + data.append(81); + data.append(82); + data.append(83); + data.append(84); + data.append(85); + data.append(86); + data.append(87); + data.append(88); + data.append(89); + data.append(90); + data.append(91); + data.append(92); + data.append(93); + data.append(94); + data.append(95); + data.append(96); + data.append(97); + data.append(98); + data.append(99); + data.append(100); + data.append(101); + data.append(102); + data.append(103); + data.append(104); + data.append(105); + data.append(106); + data.append(107); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo new file mode 100644 index 000000000..fd21b5929 --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo new file mode 100644 index 000000000..9645e3d36 --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo @@ -0,0 +1,40 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(12); + data.append(13); + data.append(14); + data.append(3); + data.append(4); + data.append(5); + data.append(3); + data.append(4); + data.append(5); + data.append(36); + data.append(37); + data.append(38); + data.append(51); + data.append(52); + data.append(53); + data.append(39); + data.append(40); + data.append(41); + data.append(72); + data.append(73); + data.append(74); + data.append(72); + data.append(73); + data.append(74); + data.append(87); + data.append(88); + data.append(89); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_batch_dims2.cairo b/tests/nodes/gather_nd_u32_batch_dims2.cairo new file mode 100644 index 000000000..1ba85277e --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims2.cairo @@ -0,0 +1,22 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_u32_batch_dims2() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo new file mode 100644 index 000000000..409b07da6 --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo @@ -0,0 +1,122 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(4); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(24); + data.append(25); + data.append(26); + data.append(27); + data.append(28); + data.append(29); + data.append(30); + data.append(31); + data.append(32); + data.append(33); + data.append(34); + data.append(35); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(48); + data.append(49); + data.append(50); + data.append(51); + data.append(52); + data.append(53); + data.append(54); + data.append(55); + data.append(56); + data.append(57); + data.append(58); + data.append(59); + data.append(60); + data.append(61); + data.append(62); + data.append(63); + data.append(64); + data.append(65); + data.append(66); + data.append(67); + data.append(68); + data.append(69); + data.append(70); + data.append(71); + data.append(72); + data.append(73); + data.append(74); + data.append(75); + data.append(76); + data.append(77); + data.append(78); + data.append(79); + data.append(80); + data.append(81); + data.append(82); + data.append(83); + data.append(84); + data.append(85); + data.append(86); + data.append(87); + data.append(88); + data.append(89); + data.append(90); + data.append(91); + data.append(92); + data.append(93); + data.append(94); + data.append(95); + data.append(96); + data.append(97); + data.append(98); + data.append(99); + data.append(100); + data.append(101); + data.append(102); + data.append(103); + data.append(104); + data.append(105); + data.append(106); + data.append(107); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo new file mode 100644 index 000000000..3cacb4f5d --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo new file mode 100644 index 000000000..f7a59c5d0 --- /dev/null +++ b/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo @@ -0,0 +1,21 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(16); + data.append(27); + data.append(39); + data.append(51); + data.append(64); + data.append(73); + data.append(84); + data.append(97); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_default.cairo b/tests/nodes/gather_nd_u32_default.cairo new file mode 100644 index 000000000..3a1043ec9 --- /dev/null +++ b/tests/nodes/gather_nd_u32_default.cairo @@ -0,0 +1,22 @@ +mod input_0; +mod input_1; +mod output_0; + + +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::{TensorTrait, Tensor}; +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32TensorPartialEq; + +#[test] +#[available_gas(2000000000)] +fn test_gather_nd_u32_default() { + let input_0 = input_0::input_0(); + let input_1 = input_1::input_1(); + let z = output_0::output_0(); + + let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + + assert_eq(y, z); +} diff --git a/tests/nodes/gather_nd_u32_default/input_0.cairo b/tests/nodes/gather_nd_u32_default/input_0.cairo new file mode 100644 index 000000000..409b07da6 --- /dev/null +++ b/tests/nodes/gather_nd_u32_default/input_0.cairo @@ -0,0 +1,122 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(4); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(24); + data.append(25); + data.append(26); + data.append(27); + data.append(28); + data.append(29); + data.append(30); + data.append(31); + data.append(32); + data.append(33); + data.append(34); + data.append(35); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(48); + data.append(49); + data.append(50); + data.append(51); + data.append(52); + data.append(53); + data.append(54); + data.append(55); + data.append(56); + data.append(57); + data.append(58); + data.append(59); + data.append(60); + data.append(61); + data.append(62); + data.append(63); + data.append(64); + data.append(65); + data.append(66); + data.append(67); + data.append(68); + data.append(69); + data.append(70); + data.append(71); + data.append(72); + data.append(73); + data.append(74); + data.append(75); + data.append(76); + data.append(77); + data.append(78); + data.append(79); + data.append(80); + data.append(81); + data.append(82); + data.append(83); + data.append(84); + data.append(85); + data.append(86); + data.append(87); + data.append(88); + data.append(89); + data.append(90); + data.append(91); + data.append(92); + data.append(93); + data.append(94); + data.append(95); + data.append(96); + data.append(97); + data.append(98); + data.append(99); + data.append(100); + data.append(101); + data.append(102); + data.append(103); + data.append(104); + data.append(105); + data.append(106); + data.append(107); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_default/input_1.cairo b/tests/nodes/gather_nd_u32_default/input_1.cairo new file mode 100644 index 000000000..3a9f4b444 --- /dev/null +++ b/tests/nodes/gather_nd_u32_default/input_1.cairo @@ -0,0 +1,31 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn input_1() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(2); + + let mut data = ArrayTrait::new(); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + data.append(0); + data.append(1); + data.append(1); + data.append(0); + data.append(0); + data.append(0); + TensorTrait::new(shape.span(), data.span()) +} diff --git a/tests/nodes/gather_nd_u32_default/output_0.cairo b/tests/nodes/gather_nd_u32_default/output_0.cairo new file mode 100644 index 000000000..eda73aaae --- /dev/null +++ b/tests/nodes/gather_nd_u32_default/output_0.cairo @@ -0,0 +1,122 @@ +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{TensorTrait, Tensor}; +use orion::operators::tensor::U32Tensor; + +fn output_0() -> Tensor { + let mut shape = ArrayTrait::::new(); + shape.append(3); + shape.append(3); + shape.append(4); + shape.append(3); + + let mut data = ArrayTrait::new(); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(36); + data.append(37); + data.append(38); + data.append(39); + data.append(40); + data.append(41); + data.append(42); + data.append(43); + data.append(44); + data.append(45); + data.append(46); + data.append(47); + data.append(0); + data.append(1); + data.append(2); + data.append(3); + data.append(4); + data.append(5); + data.append(6); + data.append(7); + data.append(8); + data.append(9); + data.append(10); + data.append(11); + TensorTrait::new(shape.span(), data.span()) +} From 11c8bd085cc1ae367bf6e3a2e643032571749688 Mon Sep 17 00:00:00 2001 From: Hakeem Kazeem Date: Thu, 14 Dec 2023 17:04:05 +0100 Subject: [PATCH 03/16] readme, changelog, summary, removed in test --- docs/CHANGELOG.md | 6 + docs/SUMMARY.md | 1 + docs/framework/compatibility.md | 3 +- docs/framework/operators/tensor/README.md | 1 + .../operators/tensor/tensor.gather_nd.md | 51 + src/operators/tensor/core.cairo | 55 +- src/operators/tensor/math/gather_nd.cairo | 198 -- tests/nodes.cairo | 1649 ++++++++--------- 8 files changed, 937 insertions(+), 1027 deletions(-) create mode 100644 docs/framework/operators/tensor/tensor.gather_nd.md diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md index fa13bee87..bc2f3525d 100644 --- a/docs/CHANGELOG.md +++ b/docs/CHANGELOG.md @@ -4,6 +4,12 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). + +## [Unreleased] - 2023-12-14 + +## Added +- Gather ND Operator. + ## [Unreleased] - 2023-11-27 ## Added diff --git a/docs/SUMMARY.md b/docs/SUMMARY.md index cd345421c..54b1ed562 100644 --- a/docs/SUMMARY.md +++ b/docs/SUMMARY.md @@ -109,6 +109,7 @@ * [tensor.reduce\_l1](framework/operators/tensor/tensor.reduce\_l1.md) * [tensor.reduce_prod](framework/operators/tensor/tensor.reduce_prod.md) * [tensor.gather\_elements](framework/operators/tensor/tensor.gather\_elements.md) + * [tensor.gather\_nd](framework/operators/tensor/tensor.gather\_nd.md) * [tensor.sequence\_length](framework/operators/tensor/tensor.sequence\_length.md) * [tensor.sequence\_at](framework/operators/tensor/tensor.sequence\_at.md) * [tensor.reduce\_min](framework/operators/tensor/tensor.reduce\_min.md) diff --git a/docs/framework/compatibility.md b/docs/framework/compatibility.md index ac25bb642..b3663babf 100644 --- a/docs/framework/compatibility.md +++ b/docs/framework/compatibility.md @@ -101,6 +101,7 @@ You can see below the list of current supported ONNX Operators: | [IsNaN](operators/tensor/tensor.is\_nan.md) | :white\_check\_mark: | | [IsInf](operators/tensor/tensor.is\_inf.md) | :white\_check\_mark: | | [Not](operators/tensor/tensor.not.md) | :white\_check\_mark: | - +| [GatherND](operators/tensor/tensor.gather/_nd.md) | :white\_check\_mark: | + Current Operators support: **95/156 (60%)** diff --git a/docs/framework/operators/tensor/README.md b/docs/framework/operators/tensor/README.md index 0f0ed5513..127bda1ac 100644 --- a/docs/framework/operators/tensor/README.md +++ b/docs/framework/operators/tensor/README.md @@ -122,6 +122,7 @@ use orion::operators::tensor::TensorTrait; | [`tensor.is_nan`](tensor.is\_nan.md) | Returns which elements of the input are NaN. | | [`tensor.is_inf`](tensor.is\_inf.md) | Maps infinity to true and other values to false. | | [`tensor.not`](tensor.not.md) | Computes the logical negation of all elements in the input tensor. | +| [`tensor.gather_nd`](tensor.gather\_nd.md) | Given data tensor of rank r >= 1, indices tensor of rank q >= 1, and batch_dims integer b, this operator gathers slices of data into an output tensor of rank q + r - indices_shape[-1] - 1 - b. | ## Arithmetic Operations diff --git a/docs/framework/operators/tensor/tensor.gather_nd.md b/docs/framework/operators/tensor/tensor.gather_nd.md new file mode 100644 index 000000000..021d4f235 --- /dev/null +++ b/docs/framework/operators/tensor/tensor.gather_nd.md @@ -0,0 +1,51 @@ +# tensor.gather_nd + +```rust + fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor; +``` + +Given data tensor of rank r >= 1, indices tensor of rank q >= 1, and batch_dims integer b, this operator gathers slices of data into an output tensor of rank q + r - indices_shape[-1] - 1 - b. + +## Args + +* `self`(`@Tensor`) - The input tensor. +* `indices`(`Tensor`) - Tensor of indices. +* `batch_dims`(`Option`) - The number of batch dimensions. The gather of indexing starts from dimension of data[batch_dims:]. + +## Panics + +* Panics if index values are not within bounds [-s, s-1] along axis of size s. +* Panics if If indices_shape[-1] > r-b. +* Panics if first b dimensions of the shape of indices tensor and data tensor are not equal. + +## Returns + +A new `Tensor` . + +## Example + +```rust +use array::{ArrayTrait, SpanTrait}; + +use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor}; + +fn gather_nd_example() -> Tensor { + let tensor = TensorTrait::::new( + shape: array![2, 2].span(), + data: array![[0, 1], [2, 3]].span(), + ); + let indices = TensorTrait::::new( + shape: array![4, 1].span(), + data: array![[0], [0], [1], [1]].span(), + ); + + return tensor.gather_nd( + indices: indices, + axis: Option::None((0)), + ); +} +>>> [[0, 1], + [0, 1], + [2, 3], + [2, 3]] +``` diff --git a/src/operators/tensor/core.cairo b/src/operators/tensor/core.cairo index 0c01c476d..38696c69a 100644 --- a/src/operators/tensor/core.cairo +++ b/src/operators/tensor/core.cairo @@ -121,7 +121,7 @@ impl TensorSerde, impl TDrop: Drop> of Serde= 1, indices tensor of rank q >= 1, and batch_dims integer b, this operator gathers slices of data into an output tensor of rank q + r - indices_shape[-1] - 1 - b. trait TensorTrait { /// # tensor.new /// @@ -4854,7 +4854,58 @@ trait TensorTrait { /// ``` /// fn not(self: @Tensor) -> Tensor; - + /// # tensor.gather_nd + /// + /// ```rust + /// fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor; + /// ``` + /// + /// Given data tensor of rank r >= 1, indices tensor of rank q >= 1, and batch_dims integer b, this operator gathers slices of data into an output tensor of rank q + r - indices_shape[-1] - 1 - b. + /// + /// ## Args + /// + /// * `self`(`@Tensor`) - The input tensor. + /// * `indices`(`Tensor`) - Tensor of indices. + /// * `batch_dims`(`Option`) - The number of batch dimensions. The gather of indexing starts from dimension of data[batch_dims:]. + /// + /// ## Panics + /// + /// * Panics if index values are not within bounds [-s, s-1] along axis of size s. + /// * Panics if If indices_shape[-1] > r-b. + /// * Panics if first b dimensions of the shape of indices tensor and data tensor are not equal. + /// + /// ## Returns + /// + /// A new `Tensor` . + /// + /// ## Example + /// + /// ```rust + /// use array::{ArrayTrait, SpanTrait}; + /// + /// use orion::operators::tensor::{TensorTrait, Tensor, U32Tensor}; + /// + /// fn gather_nd_example() -> Tensor { + /// let tensor = TensorTrait::::new( + /// shape: array![2, 2].span(), + /// data: array![[0, 1], [2, 3]].span(), + /// ); + /// let indices = TensorTrait::::new( + /// shape: array![4, 1].span(), + /// data: array![[0], [0], [1], [1]].span(), + /// ); + /// + /// return tensor.gather_nd( + /// indices: indices, + /// axis: Option::None((0)), + /// ); + /// } + /// >>> [[0, 1], + /// [0, 1], + /// [2, 3], + /// [2, 3]] + /// ``` + /// fn gather_nd(self: @Tensor, indices: Tensor, batch_dims: Option) -> Tensor; } diff --git a/src/operators/tensor/math/gather_nd.cairo b/src/operators/tensor/math/gather_nd.cairo index 04dafe2c2..bb87e71dd 100644 --- a/src/operators/tensor/math/gather_nd.cairo +++ b/src/operators/tensor/math/gather_nd.cairo @@ -165,202 +165,4 @@ fn gather_nd< let mut output_tensor = TensorTrait::::new(output_shape.span(), output_data.span()); return output_tensor; -} - - -// Tests-------------------------------------------------------------------------------------------------------------- - - -use orion::utils::assert_eq; - - -fn indices() -> Tensor { - let mut sizes = ArrayTrait::new(); - sizes.append(4); - sizes.append(1); - - let mut data = ArrayTrait::new(); - data.append(0); - data.append(0); - data.append(1); - data.append(1); - let tensor = TensorTrait::::new(sizes.span(), data.span()); - - return tensor; -} - -fn indices1() -> Tensor { - let mut shape = ArrayTrait::::new(); - shape.append(3); - shape.append(3); - - let mut data = ArrayTrait::new(); - data.append(0); - data.append(1); - data.append(2); - data.append(1); - data.append(0); - data.append(1); - data.append(2); - data.append(0); - data.append(1); - - TensorTrait::new(shape.span(), data.span()) -} - -fn data() -> Tensor { - let mut sizes = ArrayTrait::new(); - sizes.append(2); - sizes.append(2); - - let mut data = ArrayTrait::new(); - data.append(0); - data.append(1); - data.append(2); - data.append(3); - let tensor = TensorTrait::::new(sizes.span(), data.span()); - - return tensor; -} - -fn data1() -> Tensor { - let mut sizes = ArrayTrait::new(); - sizes.append(3); - sizes.append(3); - - let mut data = ArrayTrait::new(); - data.append(1); - data.append(2); - data.append(3); - data.append(4); - data.append(5); - data.append(6); - data.append(7); - data.append(8); - data.append(9); - - - let tensor = TensorTrait::::new(sizes.span(), data.span()); - - return tensor; -} - -fn u32_tensor_3x3x3_helper() -> Tensor { - let mut sizes = ArrayTrait::new(); - sizes.append(2); - sizes.append(3); - sizes.append(2); - sizes.append(4); - - let mut data = ArrayTrait::new(); - data.append(0); - data.append(1); - data.append(2); - data.append(3); - data.append(4); - data.append(5); - data.append(6); - data.append(7); - data.append(8); - data.append(9); - data.append(10); - data.append(11); - data.append(12); - data.append(13); - data.append(14); - data.append(15); - data.append(16); - data.append(17); - data.append(18); - data.append(19); - data.append(20); - data.append(21); - data.append(22); - data.append(23); - data.append(24); - data.append(25); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - data.append(26); - - let tensor = TensorTrait::::new(sizes.span(), data.span()); - - return tensor; -} - -fn indices_333() -> Tensor { - let mut sizes = ArrayTrait::new(); - sizes.append(2); - sizes.append(3); - sizes.append(1); - sizes.append(3); - - let mut data = ArrayTrait::new(); - data.append(1); - data.append(0); - data.append(0); - - data.append(0); - data.append(0); - data.append(1); - - data.append(1); - data.append(0); - data.append(1); - - data.append(0); - data.append(0); - data.append(1); - - data.append(0); - data.append(0); - data.append(0); - - data.append(0); - data.append(1); - data.append(1); - - let tensor = TensorTrait::::new(sizes.span(), data.span()); - - return tensor; -} - - -#[test] -#[available_gas(20000000000)] -fn test_gather_elements_default() { - let data = data(); - let indices = indices(); - - let y = data.gather_nd(indices: indices, batch_dims:Option::Some(0)); - let mut output = y.data; - - // loop { - // match output.pop_front() { - // Option::Some(val) => { - // (*val).print(); - // }, - // Option::None(_) => { break; } - // }; - // }; - } \ No newline at end of file diff --git a/tests/nodes.cairo b/tests/nodes.cairo index 1c76be836..44003d48e 100644 --- a/tests/nodes.cairo +++ b/tests/nodes.cairo @@ -1,825 +1,825 @@ -// mod abs_fp16x16; -// mod abs_fp8x23; -// mod abs_i32; -// mod abs_i8; -// mod acos_fp16x16; -// mod acos_fp8x23; -// mod acosh_fp16x16; -// mod acosh_fp8x23; -// mod add_fp16x16; -// mod add_fp16x16_broadcast; -// mod add_fp8x23; -// mod add_fp8x23_broadcast; -// mod add_i32; -// mod add_i32_broadcast; -// mod add_i8; -// mod add_i8_broadcast; -// mod add_u32; -// mod add_u32_broadcast; -// mod argmax_fp16x16_1D_default; -// mod argmax_fp16x16_1D_keepdims_false; -// mod argmax_fp16x16_1D_last_index; -// mod argmax_fp16x16_2D_default; -// mod argmax_fp16x16_2D_keepdims_false; -// mod argmax_fp16x16_2D_last_index; -// mod argmax_fp16x16_3D_default; -// mod argmax_fp16x16_3D_keepdims_false; -// mod argmax_fp16x16_3D_last_index; -// mod argmax_fp8x23_1D_default; -// mod argmax_fp8x23_1D_keepdims_false; -// mod argmax_fp8x23_1D_last_index; -// mod argmax_fp8x23_2D_default; -// mod argmax_fp8x23_2D_keepdims_false; -// mod argmax_fp8x23_2D_last_index; -// mod argmax_fp8x23_3D_default; -// mod argmax_fp8x23_3D_keepdims_false; -// mod argmax_fp8x23_3D_last_index; -// mod argmax_i32_1D_default; -// mod argmax_i32_1D_keepdims_false; -// mod argmax_i32_1D_last_index; -// mod argmax_i32_2D_default; -// mod argmax_i32_2D_keepdims_false; -// mod argmax_i32_2D_last_index; -// mod argmax_i32_3D_default; -// mod argmax_i32_3D_keepdims_false; -// mod argmax_i32_3D_last_index; -// mod argmax_i8_1D_default; -// mod argmax_i8_1D_keepdims_false; -// mod argmax_i8_1D_last_index; -// mod argmax_i8_2D_default; -// mod argmax_i8_2D_keepdims_false; -// mod argmax_i8_2D_last_index; -// mod argmax_i8_3D_default; -// mod argmax_i8_3D_keepdims_false; -// mod argmax_i8_3D_last_index; -// mod argmax_u32_1D_default; -// mod argmax_u32_1D_keepdims_false; -// mod argmax_u32_1D_last_index; -// mod argmax_u32_2D_default; -// mod argmax_u32_2D_keepdims_false; -// mod argmax_u32_2D_last_index; -// mod argmax_u32_3D_default; -// mod argmax_u32_3D_keepdims_false; -// mod argmax_u32_3D_last_index; -// mod argmin_fp16x16_1D_default; -// mod argmin_fp16x16_1D_keepdims_false; -// mod argmin_fp16x16_1D_last_index; -// mod argmin_fp16x16_2D_default; -// mod argmin_fp16x16_2D_keepdims_false; -// mod argmin_fp16x16_2D_last_index; -// mod argmin_fp16x16_3D_default; -// mod argmin_fp16x16_3D_keepdims_false; -// mod argmin_fp16x16_3D_last_index; -// mod argmin_fp8x23_1D_default; -// mod argmin_fp8x23_1D_keepdims_false; -// mod argmin_fp8x23_1D_last_index; -// mod argmin_fp8x23_2D_default; -// mod argmin_fp8x23_2D_keepdims_false; -// mod argmin_fp8x23_2D_last_index; -// mod argmin_fp8x23_3D_default; -// mod argmin_fp8x23_3D_keepdims_false; -// mod argmin_fp8x23_3D_last_index; -// mod argmin_i32_1D_default; -// mod argmin_i32_1D_keepdims_false; -// mod argmin_i32_1D_last_index; -// mod argmin_i32_2D_default; -// mod argmin_i32_2D_keepdims_false; -// mod argmin_i32_2D_last_index; -// mod argmin_i32_3D_default; -// mod argmin_i32_3D_keepdims_false; -// mod argmin_i32_3D_last_index; -// mod argmin_i8_1D_default; -// mod argmin_i8_1D_keepdims_false; -// mod argmin_i8_1D_last_index; -// mod argmin_i8_2D_default; -// mod argmin_i8_2D_keepdims_false; -// mod argmin_i8_2D_last_index; -// mod argmin_i8_3D_default; -// mod argmin_i8_3D_keepdims_false; -// mod argmin_i8_3D_last_index; -// mod argmin_u32_1D_default; -// mod argmin_u32_1D_keepdims_false; -// mod argmin_u32_1D_last_index; -// mod argmin_u32_2D_default; -// mod argmin_u32_2D_keepdims_false; -// mod argmin_u32_2D_last_index; -// mod argmin_u32_3D_default; -// mod argmin_u32_3D_keepdims_false; -// mod argmin_u32_3D_last_index; -// mod asin_fp16x16; -// mod asin_fp8x23; -// mod asinh_fp16x16; -// mod asinh_fp8x23; -// mod atan_fp16x16; -// mod atan_fp8x23; -// mod ceil_fp16x16; -// mod ceil_fp8x23; -// mod concat_fp16x16_1d; -// mod concat_fp16x16_2d; -// mod concat_fp16x16_3d_default; -// mod concat_fp16x16_3d_axis_1; -// mod concat_fp16x16_3d_axis_2; -// mod concat_fp16x16_3d_three_tensors_axis_1; -// mod concat_fp16x16_3d_three_tensors_axis_2; -// mod concat_fp8x23_1d; -// mod concat_fp8x23_2d; -// mod concat_fp8x23_3d_default; -// mod concat_fp8x23_3d_axis_1; -// mod concat_fp8x23_3d_axis_2; -// mod concat_fp8x23_3d_three_tensors_axis_1; -// mod concat_fp8x23_3d_three_tensors_axis_2; -// mod concat_i32_1d; -// mod concat_i32_2d; -// mod concat_i32_3d_default; -// mod concat_i32_3d_axis_1; -// mod concat_i32_3d_axis_2; -// mod concat_i32_3d_three_tensors_axis_1; -// mod concat_i32_3d_three_tensors_axis_2; -// mod concat_i8_1d; -// mod concat_i8_2d; -// mod concat_i8_3d_default; -// mod concat_i8_3d_axis_1; -// mod concat_i8_3d_axis_2; -// mod concat_i8_3d_three_tensors_axis_1; -// mod concat_i8_3d_three_tensors_axis_2; -// mod concat_u32_1d; -// mod concat_u32_2d; -// mod concat_u32_3d_default; -// mod concat_u32_3d_axis_1; -// mod concat_u32_3d_axis_2; -// mod concat_u32_3d_three_tensors_axis_1; -// mod concat_u32_3d_three_tensors_axis_2; -// mod cos_fp16x16; -// mod cos_fp8x23; -// mod cosh_fp16x16; -// mod cosh_fp8x23; -// mod cumsum_fp16x16_1d_default; -// mod cumsum_fp16x16_1d_exclusive; -// mod cumsum_fp16x16_1d_reverse; -// mod cumsum_fp16x16_1d_reverse_exclusive; -// mod cumsum_fp16x16_2d_axis_0; -// mod cumsum_fp16x16_2d_axis_1; -// mod cumsum_fp8x23_1d_default; -// mod cumsum_fp8x23_1d_exclusive; -// mod cumsum_fp8x23_1d_reverse; -// mod cumsum_fp8x23_1d_reverse_exclusive; -// mod cumsum_fp8x23_2d_axis_0; -// mod cumsum_fp8x23_2d_axis_1; -// mod cumsum_i32_1d_default; -// mod cumsum_i32_1d_exclusive; -// mod cumsum_i32_1d_reverse; -// mod cumsum_i32_1d_reverse_exclusive; -// mod cumsum_i32_2d_axis_0; -// mod cumsum_i32_2d_axis_1; -// mod cumsum_i8_1d_default; -// mod cumsum_i8_1d_exclusive; -// mod cumsum_i8_1d_reverse; -// mod cumsum_i8_1d_reverse_exclusive; -// mod cumsum_i8_2d_axis_0; -// mod cumsum_i8_2d_axis_1; -// mod cumsum_u32_1d_default; -// mod cumsum_u32_1d_exclusive; -// mod cumsum_u32_1d_reverse; -// mod cumsum_u32_1d_reverse_exclusive; -// mod cumsum_u32_2d_axis_0; -// mod cumsum_u32_2d_axis_1; -// mod div_fp16x16; -// mod div_fp16x16_broadcast; -// mod div_fp8x23; -// mod div_fp8x23_broadcast; -// mod div_i32; -// mod div_i32_broadcast; -// mod div_i8; -// mod div_i8_broadcast; -// mod div_u32; -// mod div_u32_broadcast; -// mod equal_fp16x16; -// mod equal_fp16x16_broadcast; -// mod equal_fp8x23; -// mod equal_fp8x23_broadcast; -// mod equal_i32; -// mod equal_i32_broadcast; -// mod equal_i8; -// mod equal_i8_broadcast; -// mod equal_u32; -// mod equal_u32_broadcast; -// mod exp_fp16x16; -// mod exp_fp8x23; -// mod less_equal_fp16x16; -// mod less_equal_fp16x16_broadcast; -// mod less_equal_fp8x23; -// mod less_equal_fp8x23_broadcast; -// mod less_equal_i32; -// mod less_equal_i32_broadcast; -// mod less_equal_i8; -// mod less_equal_i8_broadcast; -// mod less_equal_u32; -// mod less_equal_u32_broadcast; -// mod greater_fp16x16; -// mod greater_fp16x16_broadcast; -// mod greater_fp8x23; -// mod greater_fp8x23_broadcast; -// mod greater_i32; -// mod greater_i32_broadcast; -// mod greater_i8; -// mod greater_i8_broadcast; -// mod greater_u32; -// mod greater_u32_broadcast; -// mod leaky_relu_fp16x16; -// mod leaky_relu_fp8x23; -// mod linear_fp16x16; -// mod linear_fp8x23; -// mod linear_i32; -// mod linear_i8; -// mod linear_u32; -// mod log_fp16x16; -// mod log_fp8x23; -// mod logsoftmax_fp16x16_axis_0; -// mod logsoftmax_fp16x16_axis_1; -// mod logsoftmax_fp8x23_axis_0; -// mod logsoftmax_fp8x23_axis_1; -// mod matmul_fp16x16_1d; -// mod matmul_fp16x16_2x2; -// mod matmul_fp16x16_2x1; -// mod matmul_fp16x16_1x2; -// mod matmul_fp8x23_1d; -// mod matmul_fp8x23_2x2; -// mod matmul_fp8x23_2x1; -// mod matmul_fp8x23_1x2; -// mod matmul_i32_1d; -// mod matmul_i32_2x2; -// mod matmul_i32_2x1; -// mod matmul_i32_1x2; -// mod matmul_i8_1d; -// mod matmul_i8_2x2; -// mod matmul_i8_2x1; -// mod matmul_i8_1x2; -// mod matmul_u32_1d; -// mod matmul_u32_2x2; -// mod matmul_u32_2x1; -// mod matmul_u32_1x2; -// mod mul_fp16x16; -// mod mul_fp16x16_broadcast; -// mod mul_fp8x23; -// mod mul_fp8x23_broadcast; -// mod mul_i32; -// mod mul_i32_broadcast; -// mod mul_i8; -// mod mul_i8_broadcast; -// mod mul_u32; -// mod mul_u32_broadcast; -// mod or_fp16x16; -// mod or_fp16x16_broadcast; -// mod or_fp8x23; -// mod or_fp8x23_broadcast; -// mod or_i32; -// mod or_i32_broadcast; -// mod or_i8; -// mod or_i8_broadcast; -// mod or_u32; -// mod or_u32_broadcast; -// mod reduce_sum_fp16x16_1D; -// mod reduce_sum_fp16x16_2D_default; -// mod reduce_sum_fp16x16_2D_keepdims; -// mod reduce_sum_fp16x16_2D_axis_1; -// mod reduce_sum_fp8x23_1D; -// mod reduce_sum_fp8x23_2D_default; -// mod reduce_sum_fp8x23_2D_keepdims; -// mod reduce_sum_fp8x23_2D_axis_1; -// mod reduce_sum_i32_1D; -// mod reduce_sum_i32_2D_default; -// mod reduce_sum_i32_2D_keepdims; -// mod reduce_sum_i32_2D_axis_1; -// mod reduce_sum_i8_1D; -// mod reduce_sum_i8_2D_default; -// mod reduce_sum_i8_2D_keepdims; -// mod reduce_sum_i8_2D_axis_1; -// mod reduce_sum_u32_1D; -// mod reduce_sum_u32_2D_default; -// mod reduce_sum_u32_2D_keepdims; -// mod reduce_sum_u32_2D_axis_1; -// mod relu_fp16x16; -// mod relu_fp8x23; -// mod relu_i32; -// mod relu_i8; -// mod sigmoid_fp16x16; -// mod sigmoid_fp8x23; -// mod sin_fp16x16; -// mod sin_fp8x23; -// mod sinh_fp16x16; -// mod sinh_fp8x23; -// mod softmax_fp16x16; -// mod softmax_fp8x23; -// mod softplus_fp8x23; -// mod softplus_fp16x16; -// mod softsign_fp8x23; -// mod softsign_fp16x16; -// mod sqrt_fp16x16; -// mod sqrt_fp8x23; -// mod sub_fp16x16; -// mod sub_fp16x16_broadcast; -// mod sub_fp8x23; -// mod sub_fp8x23_broadcast; -// mod sub_i32; -// mod sub_i32_broadcast; -// mod sub_i8; -// mod sub_i8_broadcast; -// mod sub_u32; -// mod sub_u32_broadcast; -// mod tanh_fp16x16; -// mod tanh_fp8x23; -// mod transpose_fp16x16_2d; -// mod transpose_fp16x16_3d; -// mod transpose_fp8x23_2d; -// mod transpose_fp8x23_3d; -// mod transpose_i32_2d; -// mod transpose_i32_3d; -// mod transpose_i8_2d; -// mod transpose_i8_3d; -// mod transpose_u32_2d; -// mod transpose_u32_3d; -// mod xor_fp16x16; -// mod xor_fp16x16_broadcast; -// mod xor_fp8x23; -// mod xor_fp8x23_broadcast; -// mod xor_i32; -// mod xor_i32_broadcast; -// mod xor_i8; -// mod xor_i8_broadcast; -// mod xor_u32; -// mod xor_u32_broadcast; -// mod less_fp16x16; -// mod less_fp16x16_broadcast; -// mod less_fp8x23; -// mod less_fp8x23_broadcast; -// mod less_i32; -// mod less_i32_broadcast; -// mod less_i8; -// mod less_i8_broadcast; -// mod less_u32; -// mod less_u32_broadcast; -// mod greater_equal_fp16x16; -// mod greater_equal_fp16x16_broadcast; -// mod greater_equal_fp8x23; -// mod greater_equal_fp8x23_broadcast; -// mod greater_equal_i32; -// mod greater_equal_i32_broadcast; -// mod greater_equal_i8; -// mod greater_equal_i8_broadcast; -// mod greater_equal_u32; -// mod greater_equal_u32_broadcast; -// mod slice_fp16x16_2d; -// mod slice_fp16x16_3d; -// mod slice_fp8x23_2d; -// mod slice_fp8x23_3d; -// mod slice_i32_2d; -// mod slice_i32_3d; -// mod slice_i8_2d; -// mod slice_i8_3d; -// mod slice_u32_2d; -// mod slice_u32_3d; -// mod gather_fp8x23_3d_default; -// mod gather_fp8x23_3d_axis1; -// mod gather_fp8x23_3d_axis2; -// mod gather_fp16x16_3d_default; -// mod gather_fp16x16_3d_axis1; -// mod gather_fp16x16_3d_axis2; -// mod gather_i8_3d_default; -// mod gather_i8_3d_axis1; -// mod gather_i8_3d_axis2; -// mod gather_i32_3d_default; -// mod gather_i32_3d_axis1; -// mod gather_i32_3d_axis2; -// mod gather_u32_3d_default; -// mod gather_u32_3d_axis1; -// mod gather_u32_3d_axis2; -// mod nonzero_fp16x16_2d; -// mod nonzero_fp16x16_3d; -// mod nonzero_fp8x23_2d; -// mod nonzero_fp8x23_3d; -// mod nonzero_i32_2d; -// mod nonzero_i32_3d; -// mod nonzero_i8_2d; -// mod nonzero_i8_3d; -// mod nonzero_u32_2d; -// mod nonzero_u32_3d; -// mod squeeze_fP16x16; -// mod squeeze_fP8x23; -// mod squeeze_i32; -// mod squeeze_i8; -// mod squeeze_u32; -// mod unsqueeze_fp16x16_2d; -// mod unsqueeze_fp16x16_3d; -// mod unsqueeze_fp8x23_2d; -// mod unsqueeze_fp8x23_3d; -// mod unsqueeze_i32_2d; -// mod unsqueeze_i32_3d; -// mod unsqueeze_i8_2d; -// mod unsqueeze_i8_3d; -// mod unsqueeze_u32_2d; -// mod unsqueeze_u32_3d; -// mod sign_fP16x16; -// mod sign_fP8x23; -// mod sign_fail; -// mod sign_i32; -// mod sign_i8; -// mod clip_fp16x16_2d; -// mod clip_fp16x16_3d; -// mod clip_fp8x23_2d; -// mod clip_fp8x23_3d; -// mod clip_i32_2d; -// mod clip_i32_3d; -// mod clip_i8_2d; -// mod clip_i8_3d; -// mod clip_u32_2d; -// mod clip_u32_3d; -// mod identity_fP16x16; -// mod identity_fP8x23; -// mod identity_i32; -// mod identity_i8; -// mod identity_u32; -// mod thresholded_relu_fp16x16; -// mod thresholded_relu_fp8x23; -// mod hard_sigmoid_fp8x23; -// mod hard_sigmoid_fp16x16; -// mod neg_fp16x16; -// mod neg_fp8x23; -// mod neg_i32; -// mod neg_i8; -// mod gemm_all_attributes; -// mod gemm_alpha; -// mod gemm_beta; -// mod gemm_default_matrix_bias; -// mod gemm_default_vector_bias; -// mod gemm_default_no_bias; -// mod gemm_transposeA; -// mod gemm_transposeB; -// mod min_fp16x16_three_tensors; -// mod min_fp16x16_broadcast_three_tensors; -// mod min_fp16x16_two_tensors; -// mod min_fp16x16_broadcast_two_tensors; -// mod min_fp8x23_three_tensors; -// mod min_fp8x23_broadcast_three_tensors; -// mod min_fp8x23_two_tensors; -// mod min_fp8x23_broadcast_two_tensors; -// mod min_i32_three_tensors; -// mod min_i32_broadcast_three_tensors; -// mod min_i32_two_tensors; -// mod min_i32_broadcast_two_tensors; -// mod min_i8_three_tensors; -// mod min_i8_broadcast_three_tensors; -// mod min_i8_two_tensors; -// mod min_i8_broadcast_two_tensors; -// mod min_u32_three_tensors; -// mod min_u32_broadcast_three_tensors; -// mod min_u32_two_tensors; -// mod min_u32_broadcast_two_tensors; -// mod where_fp16x16; -// mod where_fp16x16_broadcast; -// mod where_fp8x23; -// mod where_fp8x23_broadcast; -// mod where_i32; -// mod where_i32_broadcast; -// mod where_i8; -// mod where_i8_broadcast; -// mod where_u32; -// mod where_u32_broadcast; -// mod not_bool; -// mod round_fp16x16; -// mod round_fp8x23; -// mod max_fp16x16_three_tensors; -// mod max_fp16x16_broadcast_three_tensors; -// mod max_fp16x16_two_tensors; -// mod max_fp16x16_broadcast_two_tensors; -// mod max_fp8x23_three_tensors; -// mod max_fp8x23_broadcast_three_tensors; -// mod max_fp8x23_two_tensors; -// mod max_fp8x23_broadcast_two_tensors; -// mod max_i32_three_tensors; -// mod max_i32_broadcast_three_tensors; -// mod max_i32_two_tensors; -// mod max_i32_broadcast_two_tensors; -// mod max_i8_three_tensors; -// mod max_i8_broadcast_three_tensors; -// mod max_i8_two_tensors; -// mod max_i8_broadcast_two_tensors; -// mod max_u32_three_tensors; -// mod max_u32_broadcast_three_tensors; -// mod max_u32_two_tensors; -// mod max_u32_broadcast_two_tensors; -// mod scatter_fp16x16_3d_default; -// mod scatter_fp16x16_3d_axis1; -// mod scatter_fp16x16_3d_axis1_add; -// mod scatter_fp8x23_default; -// mod scatter_fp8x23_axis1; -// mod scatter_fp8x23_mul; -// mod scatter_i8_default; -// mod scatter_i8_axis1; -// mod scatter_i8_axis1_max; -// mod scatter_u32_default; -// mod scatter_u32_axis1; -// mod scatter_u32_add; -// mod array_feature_extractor_1D_i32; -// mod array_feature_extractor_1D_fp8x23; -// mod array_feature_extractor_1D_fp16x16; -// mod array_feature_extractor_2D_i32; -// mod array_feature_extractor_2D_fp8x23; -// mod array_feature_extractor_2D_fp16x16; -// mod array_feature_extractor_3D_i32; -// mod array_feature_extractor_3D_fp8x23; -// mod array_feature_extractor_3D_fp16x16; -// mod binarizer_fp16x16; -// mod binarizer_fp8x23; -// mod tril_fp16x16; -// mod tril_fp16x16_neg; -// mod tril_fp16x16_one_row; -// mod tril_fp16x16_out_neg; -// mod tril_fp16x16_out_pos; -// mod tril_fp16x16_pos; -// mod tril_fp16x16_square; -// mod tril_fp16x16_square_neg; -// mod tril_fp16x16_zero; -// mod triu_fp16x16; -// mod triu_fp16x16_neg; -// mod triu_fp16x16_one_row; -// mod triu_fp16x16_out_neg; -// mod triu_fp16x16_out_pos; -// mod triu_fp16x16_pos; -// mod triu_fp16x16_square; -// mod triu_fp16x16_square_neg; -// mod triu_fp16x16_zero; -// mod tril_fp8x23; -// mod tril_fp8x23_neg; -// mod tril_fp8x23_one_row; -// mod tril_fp8x23_out_neg; -// mod tril_fp8x23_out_pos; -// mod tril_fp8x23_pos; -// mod tril_fp8x23_square; -// mod tril_fp8x23_square_neg; -// mod tril_fp8x23_zero; -// mod triu_fp8x23; -// mod triu_fp8x23_neg; -// mod triu_fp8x23_one_row; -// mod triu_fp8x23_out_neg; -// mod triu_fp8x23_out_pos; -// mod triu_fp8x23_pos; -// mod triu_fp8x23_square; -// mod triu_fp8x23_square_neg; -// mod triu_fp8x23_zero; -// mod tril_i32; -// mod tril_neg_i32; -// mod tril_i32_one_row; -// mod tril_i32_out_neg; -// mod tril_i32_out_pos; -// mod tril_i32_pos; -// mod tril_i32_square; -// mod tril_i32_square_neg; -// mod tril_i32_zero; -// mod triu_i32; -// mod triu_i32_neg; -// mod triu_i32_one_row; -// mod triu_i32_out_neg; -// mod triu_i32_out_pos; -// mod triu_i32_pos; -// mod triu_i32_square; -// mod triu_i32_square_neg; -// mod triu_i32_zero; -// mod tril_i8; -// mod tril_i8_neg; -// mod tril_i8_one_row; -// mod tril_i8_out_neg; -// mod tril_i8_out_pos; -// mod tril_i8_pos; -// mod tril_i8_square; -// mod tril_i8_square_neg; -// mod tril_i8_zero; -// mod triu_i8; -// mod triu_i8_neg; -// mod triu_i8_one_row; -// mod triu_i8_out_neg; -// mod triu_i8_out_pos; -// mod triu_i8_pos; -// mod triu_i8_square; -// mod triu_i8_square_neg; -// mod triu_i8_zero; -// mod tril_u32; -// mod tril_u32_neg; -// mod tril_u32_one_row; -// mod tril_u32_out_neg; -// mod tril_u32_out_pos; -// mod tril_u32_pos; -// mod tril_u32_square; -// mod tril_u32_square_neg; -// mod tril_u32_zero; -// mod triu_u32; -// mod triu_u32_neg; -// mod triu_u32_one_row; -// mod triu_u32_out_neg; -// mod triu_u32_out_pos; -// mod triu_u32_pos; -// mod triu_u32_square; -// mod triu_u32_square_neg; -// mod triu_u32_zero; -// mod reduce_sum_square_fp16x16_export_do_not_keepdims; -// mod reduce_sum_square_fp16x16_export_keepdims; -// mod reduce_sum_square_fp16x16_export_negative_axes_keepdims; -// mod reduce_sum_square_fp8x23_export_do_not_keepdims; -// mod reduce_sum_square_fp8x23_export_keepdims; -// mod reduce_sum_square_fp8x23_export_negative_axes_keepdims; -// mod reduce_sum_square_i32_export_do_not_keepdims; -// mod reduce_sum_square_i32_export_keepdims; -// mod reduce_sum_square_i32_export_negative_axes_keepdims; -// mod reduce_sum_square_i8_export_do_not_keepdims; -// mod reduce_sum_square_i8_export_keepdims; -// mod reduce_sum_square_i8_export_negative_axes_keepdims; -// mod reduce_sum_square_u32_export_do_not_keepdims; -// mod reduce_sum_square_u32_export_keepdims; -// mod reduce_sum_square_u32_export_negative_axes_keepdims; -// mod reduce_l2_fp16x16_export_do_not_keepdims; -// mod reduce_l2_fp16x16_export_keepdims; -// mod reduce_l2_fp16x16_export_negative_axes_keepdims; -// mod reduce_l2_fp8x23_export_do_not_keepdims; -// mod reduce_l2_fp8x23_export_keepdims; -// mod reduce_l2_fp8x23_export_negative_axes_keepdims; -// mod reduce_l1_fp16x16_export_do_not_keepdims; -// mod reduce_l1_fp16x16_export_keepdims; -// mod reduce_l1_fp16x16_export_negative_axes_keepdims; -// mod reduce_l1_fp8x23_export_do_not_keepdims; -// mod reduce_l1_fp8x23_export_keepdims; -// mod reduce_l1_fp8x23_export_negative_axes_keepdims; -// mod reduce_l1_i32_export_do_not_keepdims; -// mod reduce_l1_i32_export_keepdims; -// mod reduce_l1_i32_export_negative_axes_keepdims; -// mod reduce_l1_i8_export_do_not_keepdims; -// mod reduce_l1_i8_export_keepdims; -// mod reduce_l1_i8_export_negative_axes_keepdims; -// mod reduce_l1_u32_export_do_not_keepdims; -// mod reduce_l1_u32_export_keepdims; -// mod reduce_l1_u32_export_negative_axes_keepdims; -// mod reduce_prod_fp16x16_1D; -// mod reduce_prod_fp16x16_2D_default; -// mod reduce_prod_fp16x16_2D_keepdims; -// mod reduce_prod_fp16x16_2D_axis_1; -// mod reduce_prod_fp8x23_1D; -// mod reduce_prod_fp8x23_2D_default; -// mod reduce_prod_fp8x23_2D_keepdims; -// mod reduce_prod_fp8x23_2D_axis_1; -// mod reduce_prod_i32_1D; -// mod reduce_prod_i32_2D_default; -// mod reduce_prod_i32_2D_keepdims; -// mod reduce_prod_i32_2D_axis_1; -// mod reduce_prod_i8_1D; -// mod reduce_prod_i8_2D_default; -// mod reduce_prod_i8_2D_keepdims; -// mod reduce_prod_i8_2D_axis_1; -// mod reduce_prod_u32_1D; -// mod reduce_prod_u32_2D_default; -// mod reduce_prod_u32_2D_keepdims; -// mod reduce_prod_u32_2D_axis_1; -// mod gather_elements_fp16x16_3d_default; -// mod gather_elements_fp16x16_3d_axis1; -// mod gather_elements_fp16x16_3d_axis2; -// mod gather_elements_fp8x23_3d_default; -// mod gather_elements_fp8x23_3d_axis1; -// mod gather_elements_fp8x23_3d_axis2; -// mod gather_elements_i8_3d_default; -// mod gather_elements_i8_3d_axis1; -// mod gather_elements_i32_3d_default; -// mod gather_elements_i32_3d_axis1; -// mod gather_elements_i32_3d_axis2; -// mod gather_elements_u32_default; -// mod gather_elements_u32_axis1; -// mod gather_elements_u32_axis2; -// mod gather_elements_u32_axis3; -// mod sequence_length_fp16x16; -// mod sequence_length_fp16x16_broadcast; -// mod sequence_length_fp8x23; -// mod sequence_length_fp8x23_broadcast; -// mod sequence_length_i32; -// mod sequence_length_i32_broadcast; -// mod sequence_length_i8; -// mod sequence_length_i8_broadcast; -// mod sequence_length_u32; -// mod sequence_length_u32_broadcast; -// mod sequence_at_u32_positive; -// mod sequence_at_u32_negative; -// mod sequence_at_fp16x16_positive; -// mod sequence_at_fp16x16_negative; -// mod sequence_at_fp8x23_positive; -// mod sequence_at_fp8x23_negative; -// mod sequence_at_i32_positive; -// mod sequence_at_i32_negative; -// mod sequence_at_i8_positive; -// mod sequence_at_i8_negative; -// mod reduce_min_fp16x16_1D; -// mod reduce_min_fp16x16_2D_default; -// mod reduce_min_fp16x16_2D_keepdims; -// mod reduce_min_fp16x16_2D_axis_1; -// mod reduce_min_fp8x23_1D; -// mod reduce_min_fp8x23_2D_default; -// mod reduce_min_fp8x23_2D_keepdims; -// mod reduce_min_fp8x23_2D_axis_1; -// mod reduce_min_i32_1D; -// mod reduce_min_i32_2D_default; -// mod reduce_min_i32_2D_keepdims; -// mod reduce_min_i32_2D_axis_1; -// mod reduce_min_i8_1D; -// mod reduce_min_i8_2D_default; -// mod reduce_min_i8_2D_keepdims; -// mod reduce_min_i8_2D_axis_1; -// mod reduce_min_u32_1D; -// mod reduce_min_u32_2D_default; -// mod reduce_min_u32_2D_keepdims; -// mod reduce_min_u32_2D_axis_1; -// mod sequence_construct_fp16x16; -// mod sequence_construct_fp8x23; -// mod sequence_construct_i32; -// mod sequence_construct_i8; -// mod sequence_construct_u32; -// mod shrink_hard_fp16x16; -// mod shrink_soft_fp16x16; -// mod shrink_hard_fp8x23; -// mod shrink_soft_fp8x23; -// mod sequence_empty_fp16x16; -// mod sequence_empty_fp8x23; -// mod sequence_empty_i32; -// mod sequence_empty_i8; -// mod sequence_empty_u32; -// mod reduce_mean_fp16x16_1D; -// mod reduce_mean_fp16x16_2D_default; -// mod reduce_mean_fp16x16_2D_keepdims; -// mod reduce_mean_fp16x16_2D_axis_1; -// mod reduce_mean_fp8x23_1D; -// mod reduce_mean_fp8x23_2D_default; -// mod reduce_mean_fp8x23_2D_keepdims; -// mod reduce_mean_fp8x23_2D_axis_1; -// mod reduce_mean_i32_1D; -// mod reduce_mean_i32_2D_default; -// mod reduce_mean_i32_2D_keepdims; -// mod reduce_mean_i32_2D_axis_1; -// mod reduce_mean_i8_1D; -// mod reduce_mean_i8_2D_default; -// mod reduce_mean_i8_2D_keepdims; -// mod reduce_mean_i8_2D_axis_1; -// mod reduce_mean_u32_1D; -// mod reduce_mean_u32_2D_default; -// mod reduce_mean_u32_2D_keepdims; -// mod reduce_mean_u32_2D_axis_1; -// mod pow_fp16x16; -// mod pow_fp16x16_broadcast; -// mod pow_fp8x23; -// mod pow_fp8x23_broadcast; -// mod sequence_erase_u32_positive; -// mod sequence_erase_u32_negative; -// mod sequence_erase_u32_empty; -// mod sequence_erase_fp16x16_positive; -// mod sequence_erase_fp16x16_negative; -// mod sequence_erase_fp16x16_empty; -// mod sequence_erase_fp8x23_positive; -// mod sequence_erase_fp8x23_negative; -// mod sequence_erase_fp8x23_empty; -// mod sequence_erase_i32_positive; -// mod sequence_erase_i32_negative; -// mod sequence_erase_i32_empty; -// mod sequence_erase_i8_positive; -// mod sequence_erase_i8_negative; -// mod sequence_erase_i8_empty; -// mod sequence_insert_fp16x16; -// mod sequence_insert_fp8x23; -// mod sequence_insert_i32; -// mod sequence_insert_i8; -// mod sequence_insert_u32; -// mod concat_from_sequence_fp8x23_new_axis_zero; -// mod concat_from_sequence_fp8x23_new_axis_one; -// mod concat_from_sequence_fp8x23_new_axis_default; -// mod concat_from_sequence_fp16x16_new_axis_zero; -// mod concat_from_sequence_fp16x16_new_axis_one; -// mod concat_from_sequence_fp16x16_new_axis_default; -// mod concat_from_sequence_i32_new_axis_zero; -// mod concat_from_sequence_i32_new_axis_one; -// mod concat_from_sequence_i32_new_axis_default; -// mod concat_from_sequence_i8_new_axis_zero; -// mod concat_from_sequence_i8_new_axis_one; -// mod concat_from_sequence_i8_new_axis_default; -// mod concat_from_sequence_u32_new_axis_zero; -// mod concat_from_sequence_u32_new_axis_one; -// mod concat_from_sequence_u32_new_axis_default; -// mod is_nan_fp16x16; -// mod is_nan_fp8x23; -// mod is_inf_fp16x16; -// mod is_inf_fp8x23; -// mod is_inf_i32; -// mod is_inf_i8; -// mod is_inf_u32; -// mod is_pos_inf_fp16x16; -// mod is_neg_inf_fp16x16; -// mod is_pos_inf_fp8x23; -// mod is_neg_inf_fp8x23; -// mod is_pos_inf_i32; -// mod is_neg_inf_i32; -// mod is_pos_inf_i8; -// mod is_neg_inf_i8; -// mod and_bool; +mod abs_fp16x16; +mod abs_fp8x23; +mod abs_i32; +mod abs_i8; +mod acos_fp16x16; +mod acos_fp8x23; +mod acosh_fp16x16; +mod acosh_fp8x23; +mod add_fp16x16; +mod add_fp16x16_broadcast; +mod add_fp8x23; +mod add_fp8x23_broadcast; +mod add_i32; +mod add_i32_broadcast; +mod add_i8; +mod add_i8_broadcast; +mod add_u32; +mod add_u32_broadcast; +mod argmax_fp16x16_1D_default; +mod argmax_fp16x16_1D_keepdims_false; +mod argmax_fp16x16_1D_last_index; +mod argmax_fp16x16_2D_default; +mod argmax_fp16x16_2D_keepdims_false; +mod argmax_fp16x16_2D_last_index; +mod argmax_fp16x16_3D_default; +mod argmax_fp16x16_3D_keepdims_false; +mod argmax_fp16x16_3D_last_index; +mod argmax_fp8x23_1D_default; +mod argmax_fp8x23_1D_keepdims_false; +mod argmax_fp8x23_1D_last_index; +mod argmax_fp8x23_2D_default; +mod argmax_fp8x23_2D_keepdims_false; +mod argmax_fp8x23_2D_last_index; +mod argmax_fp8x23_3D_default; +mod argmax_fp8x23_3D_keepdims_false; +mod argmax_fp8x23_3D_last_index; +mod argmax_i32_1D_default; +mod argmax_i32_1D_keepdims_false; +mod argmax_i32_1D_last_index; +mod argmax_i32_2D_default; +mod argmax_i32_2D_keepdims_false; +mod argmax_i32_2D_last_index; +mod argmax_i32_3D_default; +mod argmax_i32_3D_keepdims_false; +mod argmax_i32_3D_last_index; +mod argmax_i8_1D_default; +mod argmax_i8_1D_keepdims_false; +mod argmax_i8_1D_last_index; +mod argmax_i8_2D_default; +mod argmax_i8_2D_keepdims_false; +mod argmax_i8_2D_last_index; +mod argmax_i8_3D_default; +mod argmax_i8_3D_keepdims_false; +mod argmax_i8_3D_last_index; +mod argmax_u32_1D_default; +mod argmax_u32_1D_keepdims_false; +mod argmax_u32_1D_last_index; +mod argmax_u32_2D_default; +mod argmax_u32_2D_keepdims_false; +mod argmax_u32_2D_last_index; +mod argmax_u32_3D_default; +mod argmax_u32_3D_keepdims_false; +mod argmax_u32_3D_last_index; +mod argmin_fp16x16_1D_default; +mod argmin_fp16x16_1D_keepdims_false; +mod argmin_fp16x16_1D_last_index; +mod argmin_fp16x16_2D_default; +mod argmin_fp16x16_2D_keepdims_false; +mod argmin_fp16x16_2D_last_index; +mod argmin_fp16x16_3D_default; +mod argmin_fp16x16_3D_keepdims_false; +mod argmin_fp16x16_3D_last_index; +mod argmin_fp8x23_1D_default; +mod argmin_fp8x23_1D_keepdims_false; +mod argmin_fp8x23_1D_last_index; +mod argmin_fp8x23_2D_default; +mod argmin_fp8x23_2D_keepdims_false; +mod argmin_fp8x23_2D_last_index; +mod argmin_fp8x23_3D_default; +mod argmin_fp8x23_3D_keepdims_false; +mod argmin_fp8x23_3D_last_index; +mod argmin_i32_1D_default; +mod argmin_i32_1D_keepdims_false; +mod argmin_i32_1D_last_index; +mod argmin_i32_2D_default; +mod argmin_i32_2D_keepdims_false; +mod argmin_i32_2D_last_index; +mod argmin_i32_3D_default; +mod argmin_i32_3D_keepdims_false; +mod argmin_i32_3D_last_index; +mod argmin_i8_1D_default; +mod argmin_i8_1D_keepdims_false; +mod argmin_i8_1D_last_index; +mod argmin_i8_2D_default; +mod argmin_i8_2D_keepdims_false; +mod argmin_i8_2D_last_index; +mod argmin_i8_3D_default; +mod argmin_i8_3D_keepdims_false; +mod argmin_i8_3D_last_index; +mod argmin_u32_1D_default; +mod argmin_u32_1D_keepdims_false; +mod argmin_u32_1D_last_index; +mod argmin_u32_2D_default; +mod argmin_u32_2D_keepdims_false; +mod argmin_u32_2D_last_index; +mod argmin_u32_3D_default; +mod argmin_u32_3D_keepdims_false; +mod argmin_u32_3D_last_index; +mod asin_fp16x16; +mod asin_fp8x23; +mod asinh_fp16x16; +mod asinh_fp8x23; +mod atan_fp16x16; +mod atan_fp8x23; +mod ceil_fp16x16; +mod ceil_fp8x23; +mod concat_fp16x16_1d; +mod concat_fp16x16_2d; +mod concat_fp16x16_3d_default; +mod concat_fp16x16_3d_axis_1; +mod concat_fp16x16_3d_axis_2; +mod concat_fp16x16_3d_three_tensors_axis_1; +mod concat_fp16x16_3d_three_tensors_axis_2; +mod concat_fp8x23_1d; +mod concat_fp8x23_2d; +mod concat_fp8x23_3d_default; +mod concat_fp8x23_3d_axis_1; +mod concat_fp8x23_3d_axis_2; +mod concat_fp8x23_3d_three_tensors_axis_1; +mod concat_fp8x23_3d_three_tensors_axis_2; +mod concat_i32_1d; +mod concat_i32_2d; +mod concat_i32_3d_default; +mod concat_i32_3d_axis_1; +mod concat_i32_3d_axis_2; +mod concat_i32_3d_three_tensors_axis_1; +mod concat_i32_3d_three_tensors_axis_2; +mod concat_i8_1d; +mod concat_i8_2d; +mod concat_i8_3d_default; +mod concat_i8_3d_axis_1; +mod concat_i8_3d_axis_2; +mod concat_i8_3d_three_tensors_axis_1; +mod concat_i8_3d_three_tensors_axis_2; +mod concat_u32_1d; +mod concat_u32_2d; +mod concat_u32_3d_default; +mod concat_u32_3d_axis_1; +mod concat_u32_3d_axis_2; +mod concat_u32_3d_three_tensors_axis_1; +mod concat_u32_3d_three_tensors_axis_2; +mod cos_fp16x16; +mod cos_fp8x23; +mod cosh_fp16x16; +mod cosh_fp8x23; +mod cumsum_fp16x16_1d_default; +mod cumsum_fp16x16_1d_exclusive; +mod cumsum_fp16x16_1d_reverse; +mod cumsum_fp16x16_1d_reverse_exclusive; +mod cumsum_fp16x16_2d_axis_0; +mod cumsum_fp16x16_2d_axis_1; +mod cumsum_fp8x23_1d_default; +mod cumsum_fp8x23_1d_exclusive; +mod cumsum_fp8x23_1d_reverse; +mod cumsum_fp8x23_1d_reverse_exclusive; +mod cumsum_fp8x23_2d_axis_0; +mod cumsum_fp8x23_2d_axis_1; +mod cumsum_i32_1d_default; +mod cumsum_i32_1d_exclusive; +mod cumsum_i32_1d_reverse; +mod cumsum_i32_1d_reverse_exclusive; +mod cumsum_i32_2d_axis_0; +mod cumsum_i32_2d_axis_1; +mod cumsum_i8_1d_default; +mod cumsum_i8_1d_exclusive; +mod cumsum_i8_1d_reverse; +mod cumsum_i8_1d_reverse_exclusive; +mod cumsum_i8_2d_axis_0; +mod cumsum_i8_2d_axis_1; +mod cumsum_u32_1d_default; +mod cumsum_u32_1d_exclusive; +mod cumsum_u32_1d_reverse; +mod cumsum_u32_1d_reverse_exclusive; +mod cumsum_u32_2d_axis_0; +mod cumsum_u32_2d_axis_1; +mod div_fp16x16; +mod div_fp16x16_broadcast; +mod div_fp8x23; +mod div_fp8x23_broadcast; +mod div_i32; +mod div_i32_broadcast; +mod div_i8; +mod div_i8_broadcast; +mod div_u32; +mod div_u32_broadcast; +mod equal_fp16x16; +mod equal_fp16x16_broadcast; +mod equal_fp8x23; +mod equal_fp8x23_broadcast; +mod equal_i32; +mod equal_i32_broadcast; +mod equal_i8; +mod equal_i8_broadcast; +mod equal_u32; +mod equal_u32_broadcast; +mod exp_fp16x16; +mod exp_fp8x23; +mod less_equal_fp16x16; +mod less_equal_fp16x16_broadcast; +mod less_equal_fp8x23; +mod less_equal_fp8x23_broadcast; +mod less_equal_i32; +mod less_equal_i32_broadcast; +mod less_equal_i8; +mod less_equal_i8_broadcast; +mod less_equal_u32; +mod less_equal_u32_broadcast; +mod greater_fp16x16; +mod greater_fp16x16_broadcast; +mod greater_fp8x23; +mod greater_fp8x23_broadcast; +mod greater_i32; +mod greater_i32_broadcast; +mod greater_i8; +mod greater_i8_broadcast; +mod greater_u32; +mod greater_u32_broadcast; +mod leaky_relu_fp16x16; +mod leaky_relu_fp8x23; +mod linear_fp16x16; +mod linear_fp8x23; +mod linear_i32; +mod linear_i8; +mod linear_u32; +mod log_fp16x16; +mod log_fp8x23; +mod logsoftmax_fp16x16_axis_0; +mod logsoftmax_fp16x16_axis_1; +mod logsoftmax_fp8x23_axis_0; +mod logsoftmax_fp8x23_axis_1; +mod matmul_fp16x16_1d; +mod matmul_fp16x16_2x2; +mod matmul_fp16x16_2x1; +mod matmul_fp16x16_1x2; +mod matmul_fp8x23_1d; +mod matmul_fp8x23_2x2; +mod matmul_fp8x23_2x1; +mod matmul_fp8x23_1x2; +mod matmul_i32_1d; +mod matmul_i32_2x2; +mod matmul_i32_2x1; +mod matmul_i32_1x2; +mod matmul_i8_1d; +mod matmul_i8_2x2; +mod matmul_i8_2x1; +mod matmul_i8_1x2; +mod matmul_u32_1d; +mod matmul_u32_2x2; +mod matmul_u32_2x1; +mod matmul_u32_1x2; +mod mul_fp16x16; +mod mul_fp16x16_broadcast; +mod mul_fp8x23; +mod mul_fp8x23_broadcast; +mod mul_i32; +mod mul_i32_broadcast; +mod mul_i8; +mod mul_i8_broadcast; +mod mul_u32; +mod mul_u32_broadcast; +mod or_fp16x16; +mod or_fp16x16_broadcast; +mod or_fp8x23; +mod or_fp8x23_broadcast; +mod or_i32; +mod or_i32_broadcast; +mod or_i8; +mod or_i8_broadcast; +mod or_u32; +mod or_u32_broadcast; +mod reduce_sum_fp16x16_1D; +mod reduce_sum_fp16x16_2D_default; +mod reduce_sum_fp16x16_2D_keepdims; +mod reduce_sum_fp16x16_2D_axis_1; +mod reduce_sum_fp8x23_1D; +mod reduce_sum_fp8x23_2D_default; +mod reduce_sum_fp8x23_2D_keepdims; +mod reduce_sum_fp8x23_2D_axis_1; +mod reduce_sum_i32_1D; +mod reduce_sum_i32_2D_default; +mod reduce_sum_i32_2D_keepdims; +mod reduce_sum_i32_2D_axis_1; +mod reduce_sum_i8_1D; +mod reduce_sum_i8_2D_default; +mod reduce_sum_i8_2D_keepdims; +mod reduce_sum_i8_2D_axis_1; +mod reduce_sum_u32_1D; +mod reduce_sum_u32_2D_default; +mod reduce_sum_u32_2D_keepdims; +mod reduce_sum_u32_2D_axis_1; +mod relu_fp16x16; +mod relu_fp8x23; +mod relu_i32; +mod relu_i8; +mod sigmoid_fp16x16; +mod sigmoid_fp8x23; +mod sin_fp16x16; +mod sin_fp8x23; +mod sinh_fp16x16; +mod sinh_fp8x23; +mod softmax_fp16x16; +mod softmax_fp8x23; +mod softplus_fp8x23; +mod softplus_fp16x16; +mod softsign_fp8x23; +mod softsign_fp16x16; +mod sqrt_fp16x16; +mod sqrt_fp8x23; +mod sub_fp16x16; +mod sub_fp16x16_broadcast; +mod sub_fp8x23; +mod sub_fp8x23_broadcast; +mod sub_i32; +mod sub_i32_broadcast; +mod sub_i8; +mod sub_i8_broadcast; +mod sub_u32; +mod sub_u32_broadcast; +mod tanh_fp16x16; +mod tanh_fp8x23; +mod transpose_fp16x16_2d; +mod transpose_fp16x16_3d; +mod transpose_fp8x23_2d; +mod transpose_fp8x23_3d; +mod transpose_i32_2d; +mod transpose_i32_3d; +mod transpose_i8_2d; +mod transpose_i8_3d; +mod transpose_u32_2d; +mod transpose_u32_3d; +mod xor_fp16x16; +mod xor_fp16x16_broadcast; +mod xor_fp8x23; +mod xor_fp8x23_broadcast; +mod xor_i32; +mod xor_i32_broadcast; +mod xor_i8; +mod xor_i8_broadcast; +mod xor_u32; +mod xor_u32_broadcast; +mod less_fp16x16; +mod less_fp16x16_broadcast; +mod less_fp8x23; +mod less_fp8x23_broadcast; +mod less_i32; +mod less_i32_broadcast; +mod less_i8; +mod less_i8_broadcast; +mod less_u32; +mod less_u32_broadcast; +mod greater_equal_fp16x16; +mod greater_equal_fp16x16_broadcast; +mod greater_equal_fp8x23; +mod greater_equal_fp8x23_broadcast; +mod greater_equal_i32; +mod greater_equal_i32_broadcast; +mod greater_equal_i8; +mod greater_equal_i8_broadcast; +mod greater_equal_u32; +mod greater_equal_u32_broadcast; +mod slice_fp16x16_2d; +mod slice_fp16x16_3d; +mod slice_fp8x23_2d; +mod slice_fp8x23_3d; +mod slice_i32_2d; +mod slice_i32_3d; +mod slice_i8_2d; +mod slice_i8_3d; +mod slice_u32_2d; +mod slice_u32_3d; +mod gather_fp8x23_3d_default; +mod gather_fp8x23_3d_axis1; +mod gather_fp8x23_3d_axis2; +mod gather_fp16x16_3d_default; +mod gather_fp16x16_3d_axis1; +mod gather_fp16x16_3d_axis2; +mod gather_i8_3d_default; +mod gather_i8_3d_axis1; +mod gather_i8_3d_axis2; +mod gather_i32_3d_default; +mod gather_i32_3d_axis1; +mod gather_i32_3d_axis2; +mod gather_u32_3d_default; +mod gather_u32_3d_axis1; +mod gather_u32_3d_axis2; +mod nonzero_fp16x16_2d; +mod nonzero_fp16x16_3d; +mod nonzero_fp8x23_2d; +mod nonzero_fp8x23_3d; +mod nonzero_i32_2d; +mod nonzero_i32_3d; +mod nonzero_i8_2d; +mod nonzero_i8_3d; +mod nonzero_u32_2d; +mod nonzero_u32_3d; +mod squeeze_fP16x16; +mod squeeze_fP8x23; +mod squeeze_i32; +mod squeeze_i8; +mod squeeze_u32; +mod unsqueeze_fp16x16_2d; +mod unsqueeze_fp16x16_3d; +mod unsqueeze_fp8x23_2d; +mod unsqueeze_fp8x23_3d; +mod unsqueeze_i32_2d; +mod unsqueeze_i32_3d; +mod unsqueeze_i8_2d; +mod unsqueeze_i8_3d; +mod unsqueeze_u32_2d; +mod unsqueeze_u32_3d; +mod sign_fP16x16; +mod sign_fP8x23; +mod sign_fail; +mod sign_i32; +mod sign_i8; +mod clip_fp16x16_2d; +mod clip_fp16x16_3d; +mod clip_fp8x23_2d; +mod clip_fp8x23_3d; +mod clip_i32_2d; +mod clip_i32_3d; +mod clip_i8_2d; +mod clip_i8_3d; +mod clip_u32_2d; +mod clip_u32_3d; +mod identity_fP16x16; +mod identity_fP8x23; +mod identity_i32; +mod identity_i8; +mod identity_u32; +mod thresholded_relu_fp16x16; +mod thresholded_relu_fp8x23; +mod hard_sigmoid_fp8x23; +mod hard_sigmoid_fp16x16; +mod neg_fp16x16; +mod neg_fp8x23; +mod neg_i32; +mod neg_i8; +mod gemm_all_attributes; +mod gemm_alpha; +mod gemm_beta; +mod gemm_default_matrix_bias; +mod gemm_default_vector_bias; +mod gemm_default_no_bias; +mod gemm_transposeA; +mod gemm_transposeB; +mod min_fp16x16_three_tensors; +mod min_fp16x16_broadcast_three_tensors; +mod min_fp16x16_two_tensors; +mod min_fp16x16_broadcast_two_tensors; +mod min_fp8x23_three_tensors; +mod min_fp8x23_broadcast_three_tensors; +mod min_fp8x23_two_tensors; +mod min_fp8x23_broadcast_two_tensors; +mod min_i32_three_tensors; +mod min_i32_broadcast_three_tensors; +mod min_i32_two_tensors; +mod min_i32_broadcast_two_tensors; +mod min_i8_three_tensors; +mod min_i8_broadcast_three_tensors; +mod min_i8_two_tensors; +mod min_i8_broadcast_two_tensors; +mod min_u32_three_tensors; +mod min_u32_broadcast_three_tensors; +mod min_u32_two_tensors; +mod min_u32_broadcast_two_tensors; +mod where_fp16x16; +mod where_fp16x16_broadcast; +mod where_fp8x23; +mod where_fp8x23_broadcast; +mod where_i32; +mod where_i32_broadcast; +mod where_i8; +mod where_i8_broadcast; +mod where_u32; +mod where_u32_broadcast; +mod not_bool; +mod round_fp16x16; +mod round_fp8x23; +mod max_fp16x16_three_tensors; +mod max_fp16x16_broadcast_three_tensors; +mod max_fp16x16_two_tensors; +mod max_fp16x16_broadcast_two_tensors; +mod max_fp8x23_three_tensors; +mod max_fp8x23_broadcast_three_tensors; +mod max_fp8x23_two_tensors; +mod max_fp8x23_broadcast_two_tensors; +mod max_i32_three_tensors; +mod max_i32_broadcast_three_tensors; +mod max_i32_two_tensors; +mod max_i32_broadcast_two_tensors; +mod max_i8_three_tensors; +mod max_i8_broadcast_three_tensors; +mod max_i8_two_tensors; +mod max_i8_broadcast_two_tensors; +mod max_u32_three_tensors; +mod max_u32_broadcast_three_tensors; +mod max_u32_two_tensors; +mod max_u32_broadcast_two_tensors; +mod scatter_fp16x16_3d_default; +mod scatter_fp16x16_3d_axis1; +mod scatter_fp16x16_3d_axis1_add; +mod scatter_fp8x23_default; +mod scatter_fp8x23_axis1; +mod scatter_fp8x23_mul; +mod scatter_i8_default; +mod scatter_i8_axis1; +mod scatter_i8_axis1_max; +mod scatter_u32_default; +mod scatter_u32_axis1; +mod scatter_u32_add; +mod array_feature_extractor_1D_i32; +mod array_feature_extractor_1D_fp8x23; +mod array_feature_extractor_1D_fp16x16; +mod array_feature_extractor_2D_i32; +mod array_feature_extractor_2D_fp8x23; +mod array_feature_extractor_2D_fp16x16; +mod array_feature_extractor_3D_i32; +mod array_feature_extractor_3D_fp8x23; +mod array_feature_extractor_3D_fp16x16; +mod binarizer_fp16x16; +mod binarizer_fp8x23; +mod tril_fp16x16; +mod tril_fp16x16_neg; +mod tril_fp16x16_one_row; +mod tril_fp16x16_out_neg; +mod tril_fp16x16_out_pos; +mod tril_fp16x16_pos; +mod tril_fp16x16_square; +mod tril_fp16x16_square_neg; +mod tril_fp16x16_zero; +mod triu_fp16x16; +mod triu_fp16x16_neg; +mod triu_fp16x16_one_row; +mod triu_fp16x16_out_neg; +mod triu_fp16x16_out_pos; +mod triu_fp16x16_pos; +mod triu_fp16x16_square; +mod triu_fp16x16_square_neg; +mod triu_fp16x16_zero; +mod tril_fp8x23; +mod tril_fp8x23_neg; +mod tril_fp8x23_one_row; +mod tril_fp8x23_out_neg; +mod tril_fp8x23_out_pos; +mod tril_fp8x23_pos; +mod tril_fp8x23_square; +mod tril_fp8x23_square_neg; +mod tril_fp8x23_zero; +mod triu_fp8x23; +mod triu_fp8x23_neg; +mod triu_fp8x23_one_row; +mod triu_fp8x23_out_neg; +mod triu_fp8x23_out_pos; +mod triu_fp8x23_pos; +mod triu_fp8x23_square; +mod triu_fp8x23_square_neg; +mod triu_fp8x23_zero; +mod tril_i32; +mod tril_neg_i32; +mod tril_i32_one_row; +mod tril_i32_out_neg; +mod tril_i32_out_pos; +mod tril_i32_pos; +mod tril_i32_square; +mod tril_i32_square_neg; +mod tril_i32_zero; +mod triu_i32; +mod triu_i32_neg; +mod triu_i32_one_row; +mod triu_i32_out_neg; +mod triu_i32_out_pos; +mod triu_i32_pos; +mod triu_i32_square; +mod triu_i32_square_neg; +mod triu_i32_zero; +mod tril_i8; +mod tril_i8_neg; +mod tril_i8_one_row; +mod tril_i8_out_neg; +mod tril_i8_out_pos; +mod tril_i8_pos; +mod tril_i8_square; +mod tril_i8_square_neg; +mod tril_i8_zero; +mod triu_i8; +mod triu_i8_neg; +mod triu_i8_one_row; +mod triu_i8_out_neg; +mod triu_i8_out_pos; +mod triu_i8_pos; +mod triu_i8_square; +mod triu_i8_square_neg; +mod triu_i8_zero; +mod tril_u32; +mod tril_u32_neg; +mod tril_u32_one_row; +mod tril_u32_out_neg; +mod tril_u32_out_pos; +mod tril_u32_pos; +mod tril_u32_square; +mod tril_u32_square_neg; +mod tril_u32_zero; +mod triu_u32; +mod triu_u32_neg; +mod triu_u32_one_row; +mod triu_u32_out_neg; +mod triu_u32_out_pos; +mod triu_u32_pos; +mod triu_u32_square; +mod triu_u32_square_neg; +mod triu_u32_zero; +mod reduce_sum_square_fp16x16_export_do_not_keepdims; +mod reduce_sum_square_fp16x16_export_keepdims; +mod reduce_sum_square_fp16x16_export_negative_axes_keepdims; +mod reduce_sum_square_fp8x23_export_do_not_keepdims; +mod reduce_sum_square_fp8x23_export_keepdims; +mod reduce_sum_square_fp8x23_export_negative_axes_keepdims; +mod reduce_sum_square_i32_export_do_not_keepdims; +mod reduce_sum_square_i32_export_keepdims; +mod reduce_sum_square_i32_export_negative_axes_keepdims; +mod reduce_sum_square_i8_export_do_not_keepdims; +mod reduce_sum_square_i8_export_keepdims; +mod reduce_sum_square_i8_export_negative_axes_keepdims; +mod reduce_sum_square_u32_export_do_not_keepdims; +mod reduce_sum_square_u32_export_keepdims; +mod reduce_sum_square_u32_export_negative_axes_keepdims; +mod reduce_l2_fp16x16_export_do_not_keepdims; +mod reduce_l2_fp16x16_export_keepdims; +mod reduce_l2_fp16x16_export_negative_axes_keepdims; +mod reduce_l2_fp8x23_export_do_not_keepdims; +mod reduce_l2_fp8x23_export_keepdims; +mod reduce_l2_fp8x23_export_negative_axes_keepdims; +mod reduce_l1_fp16x16_export_do_not_keepdims; +mod reduce_l1_fp16x16_export_keepdims; +mod reduce_l1_fp16x16_export_negative_axes_keepdims; +mod reduce_l1_fp8x23_export_do_not_keepdims; +mod reduce_l1_fp8x23_export_keepdims; +mod reduce_l1_fp8x23_export_negative_axes_keepdims; +mod reduce_l1_i32_export_do_not_keepdims; +mod reduce_l1_i32_export_keepdims; +mod reduce_l1_i32_export_negative_axes_keepdims; +mod reduce_l1_i8_export_do_not_keepdims; +mod reduce_l1_i8_export_keepdims; +mod reduce_l1_i8_export_negative_axes_keepdims; +mod reduce_l1_u32_export_do_not_keepdims; +mod reduce_l1_u32_export_keepdims; +mod reduce_l1_u32_export_negative_axes_keepdims; +mod reduce_prod_fp16x16_1D; +mod reduce_prod_fp16x16_2D_default; +mod reduce_prod_fp16x16_2D_keepdims; +mod reduce_prod_fp16x16_2D_axis_1; +mod reduce_prod_fp8x23_1D; +mod reduce_prod_fp8x23_2D_default; +mod reduce_prod_fp8x23_2D_keepdims; +mod reduce_prod_fp8x23_2D_axis_1; +mod reduce_prod_i32_1D; +mod reduce_prod_i32_2D_default; +mod reduce_prod_i32_2D_keepdims; +mod reduce_prod_i32_2D_axis_1; +mod reduce_prod_i8_1D; +mod reduce_prod_i8_2D_default; +mod reduce_prod_i8_2D_keepdims; +mod reduce_prod_i8_2D_axis_1; +mod reduce_prod_u32_1D; +mod reduce_prod_u32_2D_default; +mod reduce_prod_u32_2D_keepdims; +mod reduce_prod_u32_2D_axis_1; +mod gather_elements_fp16x16_3d_default; +mod gather_elements_fp16x16_3d_axis1; +mod gather_elements_fp16x16_3d_axis2; +mod gather_elements_fp8x23_3d_default; +mod gather_elements_fp8x23_3d_axis1; +mod gather_elements_fp8x23_3d_axis2; +mod gather_elements_i8_3d_default; +mod gather_elements_i8_3d_axis1; +mod gather_elements_i32_3d_default; +mod gather_elements_i32_3d_axis1; +mod gather_elements_i32_3d_axis2; +mod gather_elements_u32_default; +mod gather_elements_u32_axis1; +mod gather_elements_u32_axis2; +mod gather_elements_u32_axis3; +mod sequence_length_fp16x16; +mod sequence_length_fp16x16_broadcast; +mod sequence_length_fp8x23; +mod sequence_length_fp8x23_broadcast; +mod sequence_length_i32; +mod sequence_length_i32_broadcast; +mod sequence_length_i8; +mod sequence_length_i8_broadcast; +mod sequence_length_u32; +mod sequence_length_u32_broadcast; +mod sequence_at_u32_positive; +mod sequence_at_u32_negative; +mod sequence_at_fp16x16_positive; +mod sequence_at_fp16x16_negative; +mod sequence_at_fp8x23_positive; +mod sequence_at_fp8x23_negative; +mod sequence_at_i32_positive; +mod sequence_at_i32_negative; +mod sequence_at_i8_positive; +mod sequence_at_i8_negative; +mod reduce_min_fp16x16_1D; +mod reduce_min_fp16x16_2D_default; +mod reduce_min_fp16x16_2D_keepdims; +mod reduce_min_fp16x16_2D_axis_1; +mod reduce_min_fp8x23_1D; +mod reduce_min_fp8x23_2D_default; +mod reduce_min_fp8x23_2D_keepdims; +mod reduce_min_fp8x23_2D_axis_1; +mod reduce_min_i32_1D; +mod reduce_min_i32_2D_default; +mod reduce_min_i32_2D_keepdims; +mod reduce_min_i32_2D_axis_1; +mod reduce_min_i8_1D; +mod reduce_min_i8_2D_default; +mod reduce_min_i8_2D_keepdims; +mod reduce_min_i8_2D_axis_1; +mod reduce_min_u32_1D; +mod reduce_min_u32_2D_default; +mod reduce_min_u32_2D_keepdims; +mod reduce_min_u32_2D_axis_1; +mod sequence_construct_fp16x16; +mod sequence_construct_fp8x23; +mod sequence_construct_i32; +mod sequence_construct_i8; +mod sequence_construct_u32; +mod shrink_hard_fp16x16; +mod shrink_soft_fp16x16; +mod shrink_hard_fp8x23; +mod shrink_soft_fp8x23; +mod sequence_empty_fp16x16; +mod sequence_empty_fp8x23; +mod sequence_empty_i32; +mod sequence_empty_i8; +mod sequence_empty_u32; +mod reduce_mean_fp16x16_1D; +mod reduce_mean_fp16x16_2D_default; +mod reduce_mean_fp16x16_2D_keepdims; +mod reduce_mean_fp16x16_2D_axis_1; +mod reduce_mean_fp8x23_1D; +mod reduce_mean_fp8x23_2D_default; +mod reduce_mean_fp8x23_2D_keepdims; +mod reduce_mean_fp8x23_2D_axis_1; +mod reduce_mean_i32_1D; +mod reduce_mean_i32_2D_default; +mod reduce_mean_i32_2D_keepdims; +mod reduce_mean_i32_2D_axis_1; +mod reduce_mean_i8_1D; +mod reduce_mean_i8_2D_default; +mod reduce_mean_i8_2D_keepdims; +mod reduce_mean_i8_2D_axis_1; +mod reduce_mean_u32_1D; +mod reduce_mean_u32_2D_default; +mod reduce_mean_u32_2D_keepdims; +mod reduce_mean_u32_2D_axis_1; +mod pow_fp16x16; +mod pow_fp16x16_broadcast; +mod pow_fp8x23; +mod pow_fp8x23_broadcast; +mod sequence_erase_u32_positive; +mod sequence_erase_u32_negative; +mod sequence_erase_u32_empty; +mod sequence_erase_fp16x16_positive; +mod sequence_erase_fp16x16_negative; +mod sequence_erase_fp16x16_empty; +mod sequence_erase_fp8x23_positive; +mod sequence_erase_fp8x23_negative; +mod sequence_erase_fp8x23_empty; +mod sequence_erase_i32_positive; +mod sequence_erase_i32_negative; +mod sequence_erase_i32_empty; +mod sequence_erase_i8_positive; +mod sequence_erase_i8_negative; +mod sequence_erase_i8_empty; +mod sequence_insert_fp16x16; +mod sequence_insert_fp8x23; +mod sequence_insert_i32; +mod sequence_insert_i8; +mod sequence_insert_u32; +mod concat_from_sequence_fp8x23_new_axis_zero; +mod concat_from_sequence_fp8x23_new_axis_one; +mod concat_from_sequence_fp8x23_new_axis_default; +mod concat_from_sequence_fp16x16_new_axis_zero; +mod concat_from_sequence_fp16x16_new_axis_one; +mod concat_from_sequence_fp16x16_new_axis_default; +mod concat_from_sequence_i32_new_axis_zero; +mod concat_from_sequence_i32_new_axis_one; +mod concat_from_sequence_i32_new_axis_default; +mod concat_from_sequence_i8_new_axis_zero; +mod concat_from_sequence_i8_new_axis_one; +mod concat_from_sequence_i8_new_axis_default; +mod concat_from_sequence_u32_new_axis_zero; +mod concat_from_sequence_u32_new_axis_one; +mod concat_from_sequence_u32_new_axis_default; +mod is_nan_fp16x16; +mod is_nan_fp8x23; +mod is_inf_fp16x16; +mod is_inf_fp8x23; +mod is_inf_i32; +mod is_inf_i8; +mod is_inf_u32; +mod is_pos_inf_fp16x16; +mod is_neg_inf_fp16x16; +mod is_pos_inf_fp8x23; +mod is_neg_inf_fp8x23; +mod is_pos_inf_i32; +mod is_neg_inf_i32; +mod is_pos_inf_i8; +mod is_neg_inf_i8; +mod and_bool; mod gather_nd_fp16x16_3d_default; mod gather_nd_fp16x16_3d_batch_dims1; mod gather_nd_fp16x16_3d_batch_dims2; @@ -830,7 +830,4 @@ mod gather_nd_i8_3d_default; mod gather_nd_i8_3d_batch_dims1; mod gather_nd_i32_3d_default; mod gather_nd_i32_3d_batch_dims1; -mod gather_nd_i32_3d_batch_dims2; -mod gather_nd_u32_default; -mod gather_nd_u32_batch_dims1; -mod gather_nd_u32_batch_dims2; +mod gather_nd_i32_3d_batch_dims2; \ No newline at end of file From 12e54464dbc2cdfb25ae68c652b16a1acc89a970 Mon Sep 17 00:00:00 2001 From: Hakeem Kazeem Date: Thu, 14 Dec 2023 17:35:42 +0100 Subject: [PATCH 04/16] added use core:: --- src/operators/tensor/math/gather_nd.cairo | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/operators/tensor/math/gather_nd.cairo b/src/operators/tensor/math/gather_nd.cairo index bb87e71dd..120eff5be 100644 --- a/src/operators/tensor/math/gather_nd.cairo +++ b/src/operators/tensor/math/gather_nd.cairo @@ -1,13 +1,13 @@ use alexandria_data_structures::array_ext::SpanTraitExt; -use array::ArrayTrait; -use array::SpanTrait; +use core::array::ArrayTrait; +use core::array::SpanTrait; +use core::option::OptionTrait; use core::traits::Into; -use debug::PrintTrait; +use core::debug::PrintTrait; use core::traits::TryInto; use core::serde::Serde; use core::traits::Destruct; -use option::OptionTrait; use orion::numbers::NumberTrait; use orion::operators::tensor::U32TensorPartialEq; From 363f0d88ec1f510bd51a856ffe8fbbff93923710 Mon Sep 17 00:00:00 2001 From: Hakeem Kazeem Date: Thu, 14 Dec 2023 18:04:18 +0100 Subject: [PATCH 05/16] solved is not a tuple in generated test file --- nodegen/node/gather_nd.py | 4 +- tests/nodes.cairo | 25 ++--- .../gather_nd_fp16x16_3d_batch_dims1.cairo | 14 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 6 +- .../output_0.cairo | 8 +- .../gather_nd_fp16x16_3d_batch_dims2.cairo | 14 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 18 ++-- .../output_0.cairo | 20 ++-- .../nodes/gather_nd_fp16x16_3d_default.cairo | 14 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 18 ++-- .../output_0.cairo | 16 +-- .../gather_nd_fp8x23_3d_batch_dims1.cairo | 16 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 12 +-- .../output_0.cairo | 14 +-- .../gather_nd_fp8x23_3d_batch_dims2.cairo | 16 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 14 +-- .../output_0.cairo | 14 +-- tests/nodes/gather_nd_fp8x23_3d_default.cairo | 16 +-- .../gather_nd_fp8x23_3d_default/input_0.cairo | 2 +- .../gather_nd_fp8x23_3d_default/input_1.cairo | 12 +-- .../output_0.cairo | 12 +-- .../nodes/gather_nd_i32_3d_batch_dims1.cairo | 14 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 20 ++-- .../output_0.cairo | 18 ++-- .../nodes/gather_nd_i32_3d_batch_dims2.cairo | 14 +-- .../input_0.cairo | 2 +- .../input_1.cairo | 18 ++-- .../output_0.cairo | 16 +-- tests/nodes/gather_nd_i32_3d_default.cairo | 14 +-- .../gather_nd_i32_3d_default/input_0.cairo | 2 +- .../gather_nd_i32_3d_default/input_1.cairo | 8 +- .../gather_nd_i32_3d_default/output_0.cairo | 14 +-- tests/nodes/gather_nd_i8_3d_batch_dims1.cairo | 14 +-- .../gather_nd_i8_3d_batch_dims1/input_0.cairo | 2 +- .../gather_nd_i8_3d_batch_dims1/input_1.cairo | 4 +- .../output_0.cairo | 6 +- tests/nodes/gather_nd_i8_3d_default.cairo | 14 +-- .../gather_nd_i8_3d_default/input_0.cairo | 2 +- .../gather_nd_i8_3d_default/input_1.cairo | 6 +- .../gather_nd_i8_3d_default/output_0.cairo | 4 +- tests/nodes/gather_nd_u32_batch_dims1.cairo | 12 +-- .../gather_nd_u32_batch_dims1/input_0.cairo | 2 +- .../gather_nd_u32_batch_dims1/input_1.cairo | 10 +- .../gather_nd_u32_batch_dims1/output_0.cairo | 38 +++---- tests/nodes/gather_nd_u32_batch_dims2.cairo | 12 +-- .../gather_nd_u32_batch_dims2/input_0.cairo | 2 +- .../gather_nd_u32_batch_dims2/input_1.cairo | 10 +- .../gather_nd_u32_batch_dims2/output_0.cairo | 16 +-- tests/nodes/gather_nd_u32_default.cairo | 12 +-- .../nodes/gather_nd_u32_default/input_0.cairo | 2 +- .../nodes/gather_nd_u32_default/input_1.cairo | 12 +-- .../gather_nd_u32_default/output_0.cairo | 98 +++++++++---------- 58 files changed, 359 insertions(+), 356 deletions(-) diff --git a/nodegen/node/gather_nd.py b/nodegen/node/gather_nd.py index 7ba5d937f..da38fd908 100644 --- a/nodegen/node/gather_nd.py +++ b/nodegen/node/gather_nd.py @@ -1,6 +1,6 @@ import numpy as np from nodegen.node import RunAll -from ..helpers import make_test, to_fp, Tensor, Dtype, FixedImpl, Trait +from ..helpers import make_test, to_fp, Tensor, Dtype, FixedImpl def gather_nd_impl( data: np.ndarray, indices: np.ndarray, batch_dims: int @@ -49,7 +49,7 @@ def gather_nd_impl( output_data_buffer.append(reshaped_data[(batch_dim, *gather_index)]) return np.asarray(output_data_buffer, dtype=data.dtype).reshape(output_shape) - + class Gather_nd(RunAll): @staticmethod diff --git a/tests/nodes.cairo b/tests/nodes.cairo index 80ee9245a..c7155e942 100644 --- a/tests/nodes.cairo +++ b/tests/nodes.cairo @@ -826,17 +826,6 @@ mod reduce_log_sum_fp16x16_export_do_not_keepdims; mod reduce_log_sum_fp16x16_export_keepdims; mod reduce_log_sum_fp16x16_export_negative_axes_keepdims; mod and_bool; -mod gather_nd_fp16x16_3d_default; -mod gather_nd_fp16x16_3d_batch_dims1; -mod gather_nd_fp16x16_3d_batch_dims2; -mod gather_nd_fp8x23_3d_default; -mod gather_nd_fp8x23_3d_batch_dims1; -mod gather_nd_fp8x23_3d_batch_dims2; -mod gather_nd_i8_3d_default; -mod gather_nd_i8_3d_batch_dims1; -mod gather_nd_i32_3d_default; -mod gather_nd_i32_3d_batch_dims1; -mod gather_nd_i32_3d_batch_dims2; mod erf_fp16x16; mod erf_fp8x23; mod unique_fp16x16_without_axis_sorted; @@ -847,3 +836,17 @@ mod unique_u32_with_axis_zero_sorted; mod unique_u32_with_axis_zero_not_sorted; mod unique_u32_with_axis_one_sorted; mod unique_u32_with_axis_one_not_sorted; +mod gather_nd_fp16x16_3d_default; +mod gather_nd_fp16x16_3d_batch_dims1; +mod gather_nd_fp16x16_3d_batch_dims2; +mod gather_nd_fp8x23_3d_default; +mod gather_nd_fp8x23_3d_batch_dims1; +mod gather_nd_fp8x23_3d_batch_dims2; +mod gather_nd_i32_3d_default; +mod gather_nd_i32_3d_batch_dims1; +mod gather_nd_i32_3d_batch_dims2; +mod gather_nd_i8_3d_default; +mod gather_nd_i8_3d_batch_dims1; +mod gather_nd_u32_default; +mod gather_nd_u32_batch_dims1; +mod gather_nd_u32_batch_dims2; diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo index f0d927960..d2c0b80dd 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; -use orion::operators::tensor::FP16x16Tensor; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; use orion::operators::tensor::FP16x16TensorPartialEq; +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::FP16x16Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_fp16x16_3d_batch_dims1() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo index e6f14fe6d..22bb148eb 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP16x16Tensor; use orion::numbers::{FixedTrait, FP16x16}; diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo index a7a5c0d1f..c70e2eba5 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -14,6 +14,8 @@ fn input_1() -> Tensor { data.append(0); data.append(1); data.append(1); + data.append(1); + data.append(1); data.append(0); data.append(0); data.append(0); @@ -21,11 +23,9 @@ fn input_1() -> Tensor { data.append(1); data.append(0); data.append(1); - data.append(0); data.append(1); data.append(0); data.append(1); - data.append(1); data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo index 8a0d2745f..ebab95024 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims1/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP16x16Tensor; use orion::numbers::{FixedTrait, FP16x16}; @@ -11,12 +11,12 @@ fn output_0() -> Tensor { let mut data = ArrayTrait::new(); data.append(FP16x16 { mag: 196608, sign: false }); data.append(FP16x16 { mag: 65536, sign: false }); - data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 262144, sign: false }); + data.append(FP16x16 { mag: 786432, sign: false }); data.append(FP16x16 { mag: 589824, sign: false }); data.append(FP16x16 { mag: 655360, sign: false }); - data.append(FP16x16 { mag: 655360, sign: false }); - data.append(FP16x16 { mag: 1245184, sign: false }); data.append(FP16x16 { mag: 1245184, sign: false }); data.append(FP16x16 { mag: 1376256, sign: false }); + data.append(FP16x16 { mag: 1376256, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo index 38abba404..507847851 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; -use orion::operators::tensor::FP16x16Tensor; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; use orion::operators::tensor::FP16x16TensorPartialEq; +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::FP16x16Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_fp16x16_3d_batch_dims2() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo index 369c90734..aebdffdfc 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP16x16Tensor; use orion::numbers::{FixedTrait, FP16x16}; diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo index 705a6bb4c..a90e5344a 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -10,22 +10,22 @@ fn input_1() -> Tensor { let mut data = ArrayTrait::new(); data.append(1); - data.append(1); - data.append(1); data.append(0); - data.append(1); data.append(0); - data.append(1); data.append(0); - data.append(1); data.append(0); data.append(1); data.append(0); - data.append(0); data.append(1); data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); data.append(0); - data.append(0); - data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo index 0e228d8fc..cd6b1b690 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_batch_dims2/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP16x16Tensor; use orion::numbers::{FixedTrait, FP16x16}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(FP16x16 { mag: 196608, sign: false }); - data.append(FP16x16 { mag: 524288, sign: false }); - data.append(FP16x16 { mag: 917504, sign: false }); - data.append(FP16x16 { mag: 1310720, sign: false }); - data.append(FP16x16 { mag: 1703936, sign: false }); - data.append(FP16x16 { mag: 2097152, sign: false }); - data.append(FP16x16 { mag: 2424832, sign: false }); - data.append(FP16x16 { mag: 2752512, sign: false }); - data.append(FP16x16 { mag: 3145728, sign: false }); + data.append(FP16x16 { mag: 131072, sign: false }); + data.append(FP16x16 { mag: 393216, sign: false }); + data.append(FP16x16 { mag: 851968, sign: false }); + data.append(FP16x16 { mag: 1245184, sign: false }); + data.append(FP16x16 { mag: 1638400, sign: false }); + data.append(FP16x16 { mag: 2162688, sign: false }); + data.append(FP16x16 { mag: 2490368, sign: false }); + data.append(FP16x16 { mag: 2949120, sign: false }); + data.append(FP16x16 { mag: 3342336, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp16x16_3d_default.cairo b/tests/nodes/gather_nd_fp16x16_3d_default.cairo index 563fa2ebd..ae4609a66 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_default.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_default.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; -use orion::operators::tensor::FP16x16Tensor; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; use orion::operators::tensor::FP16x16TensorPartialEq; +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::FP16x16Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_fp16x16_3d_default() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo index e6f14fe6d..22bb148eb 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_default/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP16x16Tensor; use orion::numbers::{FixedTrait, FP16x16}; diff --git a/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo b/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo index 3e1010521..e9225fef4 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_default/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -9,32 +9,32 @@ fn input_1() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(0); - data.append(0); data.append(1); data.append(1); - data.append(1); - data.append(0); - data.append(0); - data.append(0); - data.append(0); data.append(0); data.append(1); + data.append(0); data.append(1); data.append(1); + data.append(0); data.append(1); data.append(1); data.append(0); data.append(1); + data.append(1); data.append(0); data.append(0); + data.append(1); data.append(0); + data.append(1); data.append(0); data.append(0); - data.append(0); + data.append(1); data.append(0); data.append(1); data.append(0); + data.append(0); data.append(1); + data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo b/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo index 0e047d322..613de79f3 100644 --- a/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo +++ b/tests/nodes/gather_nd_fp16x16_3d_default/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP16x16Tensor; use orion::numbers::{FixedTrait, FP16x16}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(FP16x16 { mag: 65536, sign: false }); data.append(FP16x16 { mag: 786432, sign: false }); - data.append(FP16x16 { mag: 0, sign: false }); - data.append(FP16x16 { mag: 262144, sign: false }); - data.append(FP16x16 { mag: 851968, sign: false }); - data.append(FP16x16 { mag: 196608, sign: false }); - data.append(FP16x16 { mag: 0, sign: false }); - data.append(FP16x16 { mag: 0, sign: false }); data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 589824, sign: false }); + data.append(FP16x16 { mag: 655360, sign: false }); + data.append(FP16x16 { mag: 65536, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); + data.append(FP16x16 { mag: 196608, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo index bd1c34722..b9a083796 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; -use orion::operators::tensor::FP8x23Tensor; +use orion::operators::tensor::FP8x23TensorPartialEq; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; -use orion::operators::tensor::FP8x23TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::FP8x23Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_fp8x23_3d_batch_dims1() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo index de5867b1f..158782e65 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP8x23Tensor; use orion::numbers::{FixedTrait, FP8x23}; diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo index a02020b98..d450f8bee 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -9,23 +9,23 @@ fn input_1() -> Tensor { shape.append(2); let mut data = ArrayTrait::new(); - data.append(1); - data.append(1); - data.append(1); data.append(0); data.append(0); - data.append(1); data.append(0); data.append(0); data.append(1); data.append(0); data.append(0); data.append(1); + data.append(0); + data.append(1); data.append(1); + data.append(0); + data.append(0); data.append(1); + data.append(0); data.append(1); data.append(1); data.append(1); - data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo index 8a13af67a..85015897d 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims1/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP8x23Tensor; use orion::numbers::{FixedTrait, FP8x23}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(FP8x23 { mag: 33554432, sign: false }); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 0, sign: false }); data.append(FP8x23 { mag: 25165824, sign: false }); - data.append(FP8x23 { mag: 8388608, sign: false }); - data.append(FP8x23 { mag: 75497472, sign: false }); - data.append(FP8x23 { mag: 100663296, sign: false }); data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); + data.append(FP8x23 { mag: 159383552, sign: false }); + data.append(FP8x23 { mag: 159383552, sign: false }); data.append(FP8x23 { mag: 184549376, sign: false }); - data.append(FP8x23 { mag: 184549376, sign: false }); - data.append(FP8x23 { mag: 176160768, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo index ab1ae82b3..5e42ca893 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; -use orion::operators::tensor::FP8x23Tensor; +use orion::operators::tensor::FP8x23TensorPartialEq; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; -use orion::operators::tensor::FP8x23TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::FP8x23Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_fp8x23_3d_batch_dims2() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo index a85fdd871..49374ed1e 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP8x23Tensor; use orion::numbers::{FixedTrait, FP8x23}; diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo index 5ac309382..a7e92e9ab 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -9,11 +9,11 @@ fn input_1() -> Tensor { shape.append(2); let mut data = ArrayTrait::new(); - data.append(1); data.append(0); data.append(0); - data.append(1); - data.append(1); + data.append(0); + data.append(0); + data.append(0); data.append(1); data.append(1); data.append(0); @@ -21,11 +21,11 @@ fn input_1() -> Tensor { data.append(1); data.append(1); data.append(0); - data.append(0); - data.append(0); - data.append(0); data.append(1); data.append(0); data.append(1); + data.append(1); + data.append(1); + data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo index 3beb1dc19..4879e0041 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_batch_dims2/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP8x23Tensor; use orion::numbers::{FixedTrait, FP8x23}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(FP8x23 { mag: 16777216, sign: false }); - data.append(FP8x23 { mag: 58720256, sign: false }); - data.append(FP8x23 { mag: 125829120, sign: false }); + data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 50331648, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); data.append(FP8x23 { mag: 167772160, sign: false }); data.append(FP8x23 { mag: 226492416, sign: false }); data.append(FP8x23 { mag: 268435456, sign: false }); - data.append(FP8x23 { mag: 301989888, sign: false }); - data.append(FP8x23 { mag: 360710144, sign: false }); - data.append(FP8x23 { mag: 411041792, sign: false }); + data.append(FP8x23 { mag: 318767104, sign: false }); + data.append(FP8x23 { mag: 377487360, sign: false }); + data.append(FP8x23 { mag: 419430400, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp8x23_3d_default.cairo b/tests/nodes/gather_nd_fp8x23_3d_default.cairo index 066a43e06..12b6408e0 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_default.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_default.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; -use orion::operators::tensor::FP8x23Tensor; +use orion::operators::tensor::FP8x23TensorPartialEq; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; -use orion::operators::tensor::FP8x23TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; +use orion::operators::tensor::FP8x23Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_fp8x23_3d_default() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo index de5867b1f..158782e65 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_default/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP8x23Tensor; use orion::numbers::{FixedTrait, FP8x23}; diff --git a/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo b/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo index 2a874516f..e4b366d62 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_default/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -11,17 +11,21 @@ fn input_1() -> Tensor { let mut data = ArrayTrait::new(); data.append(1); data.append(1); + data.append(1); data.append(0); data.append(1); data.append(1); data.append(1); + data.append(1); data.append(0); + data.append(1); data.append(0); data.append(0); data.append(1); data.append(1); data.append(0); data.append(1); + data.append(0); data.append(1); data.append(1); data.append(0); @@ -29,12 +33,8 @@ fn input_1() -> Tensor { data.append(1); data.append(1); data.append(1); - data.append(0); - data.append(0); - data.append(0); - data.append(0); data.append(1); - data.append(0); data.append(1); + data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo b/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo index 3677207fd..258e4cf9d 100644 --- a/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo +++ b/tests/nodes/gather_nd_fp8x23_3d_default/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::FP8x23Tensor; use orion::numbers::{FixedTrait, FP8x23}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(FP8x23 { mag: 100663296, sign: false }); data.append(FP8x23 { mag: 109051904, sign: false }); - data.append(FP8x23 { mag: 0, sign: false }); + data.append(FP8x23 { mag: 33554432, sign: false }); data.append(FP8x23 { mag: 100663296, sign: false }); - data.append(FP8x23 { mag: 109051904, sign: false }); - data.append(FP8x23 { mag: 8388608, sign: false }); + data.append(FP8x23 { mag: 75497472, sign: false }); data.append(FP8x23 { mag: 100663296, sign: false }); - data.append(FP8x23 { mag: 0, sign: false }); data.append(FP8x23 { mag: 83886080, sign: false }); + data.append(FP8x23 { mag: 75497472, sign: false }); + data.append(FP8x23 { mag: 109051904, sign: false }); + data.append(FP8x23 { mag: 100663296, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo index a07325f24..243b0ca16 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::I32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::I32TensorPartialEq; -use orion::operators::tensor::I32Tensor; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; #[test] #[available_gas(2000000000)] fn test_gather_nd_i32_3d_batch_dims1() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo index 3d9eabb85..f42791598 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I32Tensor; use orion::numbers::{IntegerTrait, i32}; diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo index 824761188..8df363a36 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -9,29 +9,29 @@ fn input_1() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(0); - data.append(2); data.append(2); data.append(1); data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); data.append(0); data.append(2); - data.append(1); + data.append(2); data.append(0); + data.append(2); data.append(1); data.append(0); + data.append(1); data.append(0); + data.append(1); data.append(0); data.append(2); data.append(2); - data.append(1); data.append(2); - data.append(0); + data.append(2); data.append(1); - data.append(0); - data.append(0); - data.append(0); data.append(2); - data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo index 9aa97b9fb..ef56be874 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims1/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I32Tensor; use orion::numbers::{IntegerTrait, i32}; @@ -9,13 +9,13 @@ fn output_0() -> Tensor { shape.append(2); let mut data = ArrayTrait::new(); - data.append(i32 { mag: 8, sign: false }); - data.append(i32 { mag: 9, sign: false }); - data.append(i32 { mag: 48, sign: false }); - data.append(i32 { mag: 36, sign: false }); - data.append(i32 { mag: 62, sign: false }); - data.append(i32 { mag: 69, sign: false }); - data.append(i32 { mag: 90, sign: false }); - data.append(i32 { mag: 87, sign: false }); + data.append(i32 { mag: 21, sign: false }); + data.append(i32 { mag: 13, sign: false }); + data.append(i32 { mag: 38, sign: false }); + data.append(i32 { mag: 47, sign: false }); + data.append(i32 { mag: 64, sign: false }); + data.append(i32 { mag: 57, sign: false }); + data.append(i32 { mag: 107, sign: false }); + data.append(i32 { mag: 104, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo index bd8621db5..d11370b94 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::I32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::I32TensorPartialEq; -use orion::operators::tensor::I32Tensor; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; #[test] #[available_gas(2000000000)] fn test_gather_nd_i32_3d_batch_dims2() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo index da4a9cdda..b41149fc7 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I32Tensor; use orion::numbers::{IntegerTrait, i32}; diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo index f2fed8cce..16995ef86 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -9,23 +9,23 @@ fn input_1() -> Tensor { shape.append(2); let mut data = ArrayTrait::new(); - data.append(0); - data.append(1); data.append(1); data.append(1); data.append(0); data.append(0); + data.append(1); data.append(0); + data.append(1); + data.append(1); data.append(0); data.append(0); + data.append(1); + data.append(1); + data.append(1); + data.append(1); data.append(0); data.append(0); data.append(0); - data.append(0); - data.append(0); - data.append(0); - data.append(0); - data.append(0); - data.append(0); + data.append(1); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo index dc9100d0b..06dab541d 100644 --- a/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo +++ b/tests/nodes/gather_nd_i32_3d_batch_dims2/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I32Tensor; use orion::numbers::{IntegerTrait, i32}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(i32 { mag: 1, sign: false }); - data.append(i32 { mag: 9, sign: false }); - data.append(i32 { mag: 12, sign: false }); - data.append(i32 { mag: 18, sign: false }); + data.append(i32 { mag: 3, sign: false }); + data.append(i32 { mag: 6, sign: false }); + data.append(i32 { mag: 14, sign: false }); + data.append(i32 { mag: 21, sign: false }); data.append(i32 { mag: 24, sign: false }); - data.append(i32 { mag: 30, sign: false }); - data.append(i32 { mag: 36, sign: false }); + data.append(i32 { mag: 33, sign: false }); + data.append(i32 { mag: 39, sign: false }); data.append(i32 { mag: 42, sign: false }); - data.append(i32 { mag: 48, sign: false }); + data.append(i32 { mag: 49, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i32_3d_default.cairo b/tests/nodes/gather_nd_i32_3d_default.cairo index 8f2af98a2..35c054093 100644 --- a/tests/nodes/gather_nd_i32_3d_default.cairo +++ b/tests/nodes/gather_nd_i32_3d_default.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; +use orion::operators::tensor::I32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::I32TensorPartialEq; -use orion::operators::tensor::I32Tensor; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; #[test] #[available_gas(2000000000)] fn test_gather_nd_i32_3d_default() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_i32_3d_default/input_0.cairo b/tests/nodes/gather_nd_i32_3d_default/input_0.cairo index e96796beb..230c76bfc 100644 --- a/tests/nodes/gather_nd_i32_3d_default/input_0.cairo +++ b/tests/nodes/gather_nd_i32_3d_default/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I32Tensor; use orion::numbers::{IntegerTrait, i32}; diff --git a/tests/nodes/gather_nd_i32_3d_default/input_1.cairo b/tests/nodes/gather_nd_i32_3d_default/input_1.cairo index 684a6a094..9ad554f08 100644 --- a/tests/nodes/gather_nd_i32_3d_default/input_1.cairo +++ b/tests/nodes/gather_nd_i32_3d_default/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -8,11 +8,11 @@ fn input_1() -> Tensor { shape.append(2); let mut data = ArrayTrait::new(); - data.append(1); - data.append(1); + data.append(0); + data.append(0); data.append(0); data.append(1); data.append(1); - data.append(0); + data.append(1); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i32_3d_default/output_0.cairo b/tests/nodes/gather_nd_i32_3d_default/output_0.cairo index a8342bd9b..41aa85477 100644 --- a/tests/nodes/gather_nd_i32_3d_default/output_0.cairo +++ b/tests/nodes/gather_nd_i32_3d_default/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I32Tensor; use orion::numbers::{IntegerTrait, i32}; @@ -9,14 +9,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(i32 { mag: 9, sign: false }); - data.append(i32 { mag: 10, sign: false }); - data.append(i32 { mag: 11, sign: false }); + data.append(i32 { mag: 0, sign: false }); + data.append(i32 { mag: 1, sign: false }); + data.append(i32 { mag: 2, sign: false }); data.append(i32 { mag: 3, sign: false }); data.append(i32 { mag: 4, sign: false }); data.append(i32 { mag: 5, sign: false }); - data.append(i32 { mag: 6, sign: false }); - data.append(i32 { mag: 7, sign: false }); - data.append(i32 { mag: 8, sign: false }); + data.append(i32 { mag: 9, sign: false }); + data.append(i32 { mag: 10, sign: false }); + data.append(i32 { mag: 11, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo index e733ee9db..ae83a8c7d 100644 --- a/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; -use orion::operators::tensor::I8Tensor; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; use orion::operators::tensor::I8TensorPartialEq; +use orion::operators::tensor::I8Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_i8_3d_batch_dims1() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo index 500932fc7..069bade56 100644 --- a/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I8Tensor; use orion::numbers::{IntegerTrait, i8}; diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo index 8a43b62a1..9d317b808 100644 --- a/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -8,8 +8,8 @@ fn input_1() -> Tensor { shape.append(1); let mut data = ArrayTrait::new(); - data.append(1); data.append(0); data.append(0); + data.append(1); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo index 6d19d1334..8d432b7ba 100644 --- a/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo +++ b/tests/nodes/gather_nd_i8_3d_batch_dims1/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I8Tensor; use orion::numbers::{IntegerTrait, i8}; @@ -8,8 +8,8 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(i8 { mag: 1, sign: false }); + data.append(i8 { mag: 0, sign: false }); data.append(i8 { mag: 3, sign: false }); - data.append(i8 { mag: 6, sign: false }); + data.append(i8 { mag: 7, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i8_3d_default.cairo b/tests/nodes/gather_nd_i8_3d_default.cairo index d4022ced4..73e1d91b2 100644 --- a/tests/nodes/gather_nd_i8_3d_default.cairo +++ b/tests/nodes/gather_nd_i8_3d_default.cairo @@ -3,22 +3,22 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; -use orion::operators::tensor::I8Tensor; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; use orion::operators::tensor::I8TensorPartialEq; +use orion::operators::tensor::I8Tensor; #[test] #[available_gas(2000000000)] fn test_gather_nd_i8_3d_default() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_i8_3d_default/input_0.cairo b/tests/nodes/gather_nd_i8_3d_default/input_0.cairo index 500932fc7..069bade56 100644 --- a/tests/nodes/gather_nd_i8_3d_default/input_0.cairo +++ b/tests/nodes/gather_nd_i8_3d_default/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I8Tensor; use orion::numbers::{IntegerTrait, i8}; diff --git a/tests/nodes/gather_nd_i8_3d_default/input_1.cairo b/tests/nodes/gather_nd_i8_3d_default/input_1.cairo index f0cbc41aa..b38bfc539 100644 --- a/tests/nodes/gather_nd_i8_3d_default/input_1.cairo +++ b/tests/nodes/gather_nd_i8_3d_default/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -8,11 +8,11 @@ fn input_1() -> Tensor { shape.append(2); let mut data = ArrayTrait::new(); - data.append(0); - data.append(0); data.append(1); data.append(1); data.append(1); data.append(1); + data.append(1); + data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_i8_3d_default/output_0.cairo b/tests/nodes/gather_nd_i8_3d_default/output_0.cairo index 6788630df..05eebd0f6 100644 --- a/tests/nodes/gather_nd_i8_3d_default/output_0.cairo +++ b/tests/nodes/gather_nd_i8_3d_default/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::I8Tensor; use orion::numbers::{IntegerTrait, i8}; @@ -8,8 +8,8 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(i8 { mag: 0, sign: false }); data.append(i8 { mag: 4, sign: false }); data.append(i8 { mag: 4, sign: false }); + data.append(i8 { mag: 3, sign: false }); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_u32_batch_dims1.cairo b/tests/nodes/gather_nd_u32_batch_dims1.cairo index 94fea41f5..0428ec1d5 100644 --- a/tests/nodes/gather_nd_u32_batch_dims1.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims1.cairo @@ -3,20 +3,20 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; #[test] #[available_gas(2000000000)] fn test_gather_nd_u32_batch_dims1() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(1)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo b/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo index 409b07da6..f0f05cab0 100644 --- a/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims1/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; diff --git a/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo b/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo index fd21b5929..4d79fe1e8 100644 --- a/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims1/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -10,20 +10,20 @@ fn input_1() -> Tensor { let mut data = ArrayTrait::new(); data.append(1); - data.append(0); - data.append(0); data.append(1); data.append(0); + data.append(0); data.append(1); data.append(0); data.append(0); data.append(1); - data.append(1); data.append(0); data.append(1); data.append(0); + data.append(1); data.append(0); - data.append(0); + data.append(1); + data.append(1); data.append(0); data.append(1); data.append(1); diff --git a/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo b/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo index 9645e3d36..020780226 100644 --- a/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims1/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -9,30 +9,30 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); + data.append(15); + data.append(16); + data.append(17); + data.append(0); + data.append(1); + data.append(2); data.append(12); data.append(13); data.append(14); - data.append(3); - data.append(4); - data.append(5); - data.append(3); - data.append(4); - data.append(5); - data.append(36); - data.append(37); - data.append(38); - data.append(51); - data.append(52); - data.append(53); data.append(39); data.append(40); data.append(41); - data.append(72); - data.append(73); - data.append(74); - data.append(72); - data.append(73); - data.append(74); + data.append(39); + data.append(40); + data.append(41); + data.append(39); + data.append(40); + data.append(41); + data.append(75); + data.append(76); + data.append(77); + data.append(84); + data.append(85); + data.append(86); data.append(87); data.append(88); data.append(89); diff --git a/tests/nodes/gather_nd_u32_batch_dims2.cairo b/tests/nodes/gather_nd_u32_batch_dims2.cairo index 1ba85277e..39857ef1d 100644 --- a/tests/nodes/gather_nd_u32_batch_dims2.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims2.cairo @@ -3,20 +3,20 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; #[test] #[available_gas(2000000000)] fn test_gather_nd_u32_batch_dims2() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(2)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo b/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo index 409b07da6..f0f05cab0 100644 --- a/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims2/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; diff --git a/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo b/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo index 3cacb4f5d..198a57be6 100644 --- a/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims2/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -10,9 +10,6 @@ fn input_1() -> Tensor { let mut data = ArrayTrait::new(); data.append(0); - data.append(0); - data.append(1); - data.append(1); data.append(1); data.append(0); data.append(1); @@ -23,9 +20,12 @@ fn input_1() -> Tensor { data.append(1); data.append(0); data.append(1); - data.append(0); + data.append(1); + data.append(1); data.append(0); data.append(0); data.append(1); + data.append(0); + data.append(0); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo b/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo index f7a59c5d0..a80c37449 100644 --- a/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo +++ b/tests/nodes/gather_nd_u32_batch_dims2/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -8,14 +8,14 @@ fn output_0() -> Tensor { shape.append(3); let mut data = ArrayTrait::new(); - data.append(0); - data.append(16); - data.append(27); - data.append(39); + data.append(1); + data.append(13); + data.append(25); + data.append(37); data.append(51); data.append(64); - data.append(73); - data.append(84); - data.append(97); + data.append(75); + data.append(85); + data.append(96); TensorTrait::new(shape.span(), data.span()) } diff --git a/tests/nodes/gather_nd_u32_default.cairo b/tests/nodes/gather_nd_u32_default.cairo index 3a1043ec9..f55b49d5e 100644 --- a/tests/nodes/gather_nd_u32_default.cairo +++ b/tests/nodes/gather_nd_u32_default.cairo @@ -3,20 +3,20 @@ mod input_1; mod output_0; -use orion::utils::{assert_eq, assert_seq_eq}; -use orion::operators::tensor::U32Tensor; use orion::operators::tensor::{TensorTrait, Tensor}; -use array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::U32TensorPartialEq; +use core::array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::U32Tensor; +use orion::utils::{assert_eq, assert_seq_eq}; #[test] #[available_gas(2000000000)] fn test_gather_nd_u32_default() { let input_0 = input_0::input_0(); let input_1 = input_1::input_1(); - let z = output_0::output_0(); + let z_0 = output_0::output_0(); - let y = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); + let y_0 = input_0.gather_nd(indices:input_1, batch_dims:Option::Some(0)); - assert_eq(y, z); + assert_eq(y_0, z_0); } diff --git a/tests/nodes/gather_nd_u32_default/input_0.cairo b/tests/nodes/gather_nd_u32_default/input_0.cairo index 409b07da6..f0f05cab0 100644 --- a/tests/nodes/gather_nd_u32_default/input_0.cairo +++ b/tests/nodes/gather_nd_u32_default/input_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; diff --git a/tests/nodes/gather_nd_u32_default/input_1.cairo b/tests/nodes/gather_nd_u32_default/input_1.cairo index 3a9f4b444..bb54a8189 100644 --- a/tests/nodes/gather_nd_u32_default/input_1.cairo +++ b/tests/nodes/gather_nd_u32_default/input_1.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -11,20 +11,20 @@ fn input_1() -> Tensor { let mut data = ArrayTrait::new(); data.append(0); data.append(1); - data.append(0); - data.append(0); data.append(1); data.append(0); - data.append(1); data.append(0); data.append(1); + data.append(1); data.append(0); data.append(0); - data.append(0); - data.append(0); + data.append(1); data.append(1); data.append(1); data.append(0); + data.append(1); + data.append(1); + data.append(1); data.append(0); data.append(0); TensorTrait::new(shape.span(), data.span()) diff --git a/tests/nodes/gather_nd_u32_default/output_0.cairo b/tests/nodes/gather_nd_u32_default/output_0.cairo index eda73aaae..f54097ea6 100644 --- a/tests/nodes/gather_nd_u32_default/output_0.cairo +++ b/tests/nodes/gather_nd_u32_default/output_0.cairo @@ -1,4 +1,4 @@ -use array::{ArrayTrait, SpanTrait}; +use core::array::{ArrayTrait, SpanTrait}; use orion::operators::tensor::{TensorTrait, Tensor}; use orion::operators::tensor::U32Tensor; @@ -22,42 +22,6 @@ fn output_0() -> Tensor { data.append(21); data.append(22); data.append(23); - data.append(0); - data.append(1); - data.append(2); - data.append(3); - data.append(4); - data.append(5); - data.append(6); - data.append(7); - data.append(8); - data.append(9); - data.append(10); - data.append(11); - data.append(36); - data.append(37); - data.append(38); - data.append(39); - data.append(40); - data.append(41); - data.append(42); - data.append(43); - data.append(44); - data.append(45); - data.append(46); - data.append(47); - data.append(36); - data.append(37); - data.append(38); - data.append(39); - data.append(40); - data.append(41); - data.append(42); - data.append(43); - data.append(44); - data.append(45); - data.append(46); - data.append(47); data.append(36); data.append(37); data.append(38); @@ -70,18 +34,6 @@ fn output_0() -> Tensor { data.append(45); data.append(46); data.append(47); - data.append(0); - data.append(1); - data.append(2); - data.append(3); - data.append(4); - data.append(5); - data.append(6); - data.append(7); - data.append(8); - data.append(9); - data.append(10); - data.append(11); data.append(12); data.append(13); data.append(14); @@ -106,6 +58,54 @@ fn output_0() -> Tensor { data.append(45); data.append(46); data.append(47); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(48); + data.append(49); + data.append(50); + data.append(51); + data.append(52); + data.append(53); + data.append(54); + data.append(55); + data.append(56); + data.append(57); + data.append(58); + data.append(59); + data.append(12); + data.append(13); + data.append(14); + data.append(15); + data.append(16); + data.append(17); + data.append(18); + data.append(19); + data.append(20); + data.append(21); + data.append(22); + data.append(23); + data.append(48); + data.append(49); + data.append(50); + data.append(51); + data.append(52); + data.append(53); + data.append(54); + data.append(55); + data.append(56); + data.append(57); + data.append(58); + data.append(59); data.append(0); data.append(1); data.append(2); From 70b6408bffe32b3c4bc85696b51b1b76c2f17fde Mon Sep 17 00:00:00 2001 From: chachaleo Date: Thu, 14 Dec 2023 15:55:09 +0700 Subject: [PATCH 06/16] verifiable lagrange tuto --- docs/academy/tutorials/README.md | 7 + .../verifiable-Lagrange-interpolation.md | 350 ++++++++++++++++++ 2 files changed, 357 insertions(+) create mode 100755 docs/academy/tutorials/verifiable-Lagrange-interpolation.md diff --git a/docs/academy/tutorials/README.md b/docs/academy/tutorials/README.md index 37cbcc767..2a2b57f42 100644 --- a/docs/academy/tutorials/README.md +++ b/docs/academy/tutorials/README.md @@ -2,6 +2,13 @@ Learn how to use Orion with tutorials. We encourage you to contribute by sharing your own tutorial. +## [Verifiable Lagrange Interpolation](verifiable-Lagrange-interpolation.md) + +Lagrange interpolation is a mathematical technique used to approximate a function that passes through a given set of points. It takes an input set of data points and computes a polynomial that passes through all of them. + +_December 14, 2023 chachaleo_ + + ## [Verifiable Principal Components Analysis](verifiable-principal-components-analysis.md) The Principal Component Analysis (PCA) method is an unsupervised learning algorithm that aims to reduce the dimensionality of a dataset consisting of a large number of interrelated variables, while at the same time preserving as much of the variation present in the original dataset as possible. diff --git a/docs/academy/tutorials/verifiable-Lagrange-interpolation.md b/docs/academy/tutorials/verifiable-Lagrange-interpolation.md new file mode 100755 index 000000000..38f887406 --- /dev/null +++ b/docs/academy/tutorials/verifiable-Lagrange-interpolation.md @@ -0,0 +1,350 @@ +# **Verifiable Lagrange interpolation** + +Lagrange interpolation is a mathematical technique used to approximate a function that passes through a given set of points. It takes an input set of data points and computes a polynomial that passes through all of them. + +Given a set of $n+1$ data points (or interpolation nodes) $X_0, X_1, ..., X_n$ with corresponding function values $Y_0, Y_1, ..., Y_n$, Lagrange interpolation seeks to find a polynomial of degree at most $n$ that passes through all these points. + +Below, we provide a brief review of the implementation of a Lagrange interpolation in Python, which we will then convert to Cairo to transform it into a verifiable ZKML (Lagrange interpolation), using the Orion library. + +Content overview: + +1. [Lagrange interpolation with Python:](LagrangeInterpolationTutorial.md#used-dataset) We start with the basic implementation of Lagrange interpolation using Python. +2. [Convert your model to Cairo:](LagrangeInterpolationTutorial.md#convert-your-model-to-cairo) In the subsequent stage, we will create a new scarb project and replicate our model to Cairo which is a language for creating STARK-provable programs. +3. [Implementing Lagrange interpolation using Orion:](LagrangeInterpolationTutorial.md#implementing-lagrange-using-orion) To catalyze our development process, we will use the Orion Framework to construct the key functions to build our verifiable Lagrange interpolation. + +### Used DataSet + +In this tutorial, we will interpolate the Runge function, that we will define $f$ and uses the Chebyshev node as interpolation nodes. + +```python +import numpy as np +import math +import matplotlib.pyplot as plt + +# Runge function +def f(x): + return 1 / (x**2 + 1) + +# Chebyshev nodes +X = np.array( [5*math.cos(k*math.pi/10) for k in range(0,11)] ) + +Y = f(X) + +``` + + +### Implementation of Lagrange interpolating polynomial + +Now we will implement Lagrange interpolation function in python. + +Given a set of $n+1$ data points $X_0, X_1, ..., X_n$ with corresponding function values $Y_0, Y_1, ..., Y_n$, the Lagrange interpolating polynomial is + +$$ + L(x) = \sum_{i=0}^n Y_i \phi_i(x), +$$ + +where $\phi_i(x)$ is the $i$-th Lagrange polynomial defined by +$$ + \phi_i(x) = \frac{(x - X_0)\ldots (x - X_{i-1})(x - X_{i+1})\ldots(x - X_n)}{(X_i - X_0)\ldots (X_i - X_{i-1})(X_i - X_{i+1})\ldots(X_i - X_n)} + +$$ + +```python +def lagrange(x,X,Y): + + n = min(len(X),len(Y)) + m = len(x) + yh = np.zeros(m) + phi = np.zeros(n) + for j in range(m): + yh[j] = 0 + for i in range(n): + phi[i] = 1.0 + for k in range(n): + if i != k: + phi[i] = phi[i]*(x[j]-X[k])/(X[i]-X[k]) + yh[j] = yh[j] + Y[i] * phi[i] + return yh +``` + + + + +## Visualization of the interpolation + + +```python +x = np.linspace(-5,5,num=100) +fx = f(x) +y = lagrange(x,X,Y) + +fig, ax = plt.subplots() +ax.set_title('Lagrange interpolation of Runge function', fontsize = 15) +ax.plot(x,fx,label='Runge function') +ax.plot(x,y,label='Lagrange interpolation') +plt.legend() +plt.show() +``` + +
+ + +## Convert your model to Cairo + +Now that we have a good understanding of the Lagrange interpolation, we will replicate the entire algorithm in Cairo to make it fully verifiable. Since we will be rebuilding the algorithm from scratch, this will be a good opportunity to get acquainted with Orion's built-in functions and the operators that make the transition to Cairo seamless. + +### Create a new Scarb project + +Scarb is the Cairo package manager specifically created to streamline our Cairo and Starknet development process. Scarb will typically manage project dependencies, the compilation process (both pure Cairo and Starknet contracts), downloading and building external libraries to accelerate our development with Orion.You can find all information about Scarb and Cairo installation [here](https://orion.gizatech.xyz/v/develop/framework/get-started#installations). + +To create a new Scarb project, open your terminal and run: + +``` +scarb new verifiable_Lagrange_interpolation +``` + +A new project folder will be created for you and make sure to replace the content in Scarb.toml file with the following code: + +```toml +[package] +name = "scarb new verifiable_Lagrange_interpolation" +version = "0.1.0" + +[dependencies] +orion = { git = "https://github.com/gizatechxyz/orion.git", rev = "v0.1.9" } +``` + +### Gerating the dataset in Cairo + +Now let's generate the necessary files to begin our transition to Cairo. In our Jupyter Notebook, we will run the necessary code to convert our interpolation nodes and the interpolation result as fixed point tensors in Orion. + +```python +import os +``` + +```python +os.makedirs("src/generated", exist_ok=True) +``` + +```python +tensor_name = ["X","Y","x","y"] + +def generate_cairo_files(data, name): + + with open(os.path.join('src', 'generated', f"{name}.cairo"), "w") as f: + f.write( + "use array::{ArrayTrait, SpanTrait};\n" + + "use orion::operators::tensor::{core::{Tensor, TensorTrait}};\n" + + "use orion::operators::tensor::FP16x16Tensor;\n" + + "use orion::numbers::fixed_point::implementations::fp16x16::core::{FP16x16, FixedTrait};\n" + + "\n" + f"fn {name}() -> Tensor" + "{\n\n" + + "let mut shape = ArrayTrait::new();\n" + ) + for dim in data.shape: + f.write(f"shape.append({dim});\n") + + f.write("let mut data = ArrayTrait::new();\n") + for val in np.nditer(data.flatten()): + f.write(f"data.append(FixedTrait::new({abs(int(decimal_to_fp16x16(val)))}, {str(val < 0).lower()}));\n") + f.write( + "let tensor = TensorTrait::::new(shape.span(), data.span());\n" + + "return tensor;\n}" + ) + +with open(f"src/generated.cairo", "w") as f: + for n in tensor_name: + f.write(f"mod {n};\n") + +generate_cairo_files(X, "X") +generate_cairo_files(Y, "Y") + +generate_cairo_files(x, "x") +generate_cairo_files(y, "y") +``` + +The X, Y, x, y tensor values will now be generated under `src/generated` directory. + +In `src/lib.cairo` replace the content with the following code: + +```rust +mod generated; +mod helper; +mod test; +``` + +This will tell our compiler to include the separate modules listed above during the compilation of our code. We will be covering each module in detail in the following section, but let’s first review the generated folder files. + +```rust +use array::{ArrayTrait, SpanTrait}; +use orion::operators::tensor::{core::{Tensor, TensorTrait}}; +use orion::operators::tensor::FP16x16Tensor; +use orion::numbers::fixed_point::implementations::fp16x16::core::{FP16x16, FixedTrait}; + +fn X() -> Tensor{ + +let mut shape = ArrayTrait::new(); +shape.append(11); +let mut data = ArrayTrait::new(); +data.append(FixedTrait::new(327680, false)); +data.append(FixedTrait::new(311642, false)); +data.append(FixedTrait::new(265098, false)); +data.append(FixedTrait::new(192605, false)); +data.append(FixedTrait::new(101258, false)); +data.append(FixedTrait::new(0, false)); +data.append(FixedTrait::new(101258, true)); +data.append(FixedTrait::new(192605, true)); +data.append(FixedTrait::new(265098, true)); +data.append(FixedTrait::new(311642, true)); +data.append(FixedTrait::new(327680, true)); +let tensor = TensorTrait::::new(shape.span(), data.span()); +return tensor; +} +``` + +Since Cairo does not come with built-in fixed points we have to explicitly define it for our X, Y, x, y values. Luckily, this is already implemented in Orion for us as a struct as shown below: + + +```rust +// Example of a FP16x16. +struct FP16x16 { + mag: u32, + sign: bool +} +``` + +For this tutorial, we will use fixed point numbers FP16x16 where the magnitude represents the absolute value and the boolean indicates whether the number is negative or positive. In a 16x16 fixed-point format, there are 16 bits dedicated to the integer part of the number and 16 bits for the fractional part of the number. This format allows us to work with a wide range of values and a high degree of precision for conducting the Tensor operations. To replicate the Lagrange interpolation function, we will conduct our operations using FP16x16 Tensors which are also represented as a structs in Orion. + +```rust +struct Tensor { + shape: Span, + data: Span +} +``` + +A `Tensor` in Orion takes a shape and a span array of the data. + +## Implementing Lagrange interpolation using Orion + +At this stage, we will be reproducing the Lagrange interpolation function now that we have generated our X, Y, x, y Fixedpoint Tensors. We will begin by creating a separate file for our Lagrange interpolation function file named `helper.cairo` to host all of our core functions. + +### Lagrange interpolation function + +```rust +fn lagrange_interpolation(x_interpolated: @Tensor, X: @Tensor, Y: @Tensor) -> Tensor { + + let n = ((*X).data.len()); + let m = ((*x_interpolated).data.len()); + + let mut y_data = ArrayTrait::::new(); + let mut phi = ArrayTrait::::new(); + let mut j = 0; + + loop { + if j == m { + break; + } + let mut y_j = FixedTrait::new(0,true); + let mut i = 0; + loop { + if i == n { + break; + } + let mut phi_i = FixedTrait::::new(65536,true); + let mut k = 0; + loop { + if k == n { + break; + } + if i != k { + phi_i = phi_i * (*(*x_interpolated).data.at(j) - *(*X).data.at(k))/( *(*X).data.at(i) - *(*X).data.at(k)) + } + k += 1; + }; + y_j = y_j + *(*Y).data.at(i) * phi_i; + i += 1; + }; + y_data.append(y_j); + j += 1; + + }; + + return TensorTrait::new((*x_interpolated).shape, y_data.span()); + +} + +``` + + +### Testing the model + +Now that we have implemented the Lagrange interpolation function, we can finally test it. We begin by creating a new separate test file named `test.cairo` and import all the necessary Orion libraries, including our X, Y, x and y values found in the generated folder. We also import the Lagrange function from the `helper.cairo` file, as we will rely on them to construct the model. + +```rust +#[cfg(test)] +mod tests { + use traits::TryInto; + use alexandria_data_structures::array_ext::{SpanTraitExt}; + use array::{ArrayTrait, SpanTrait}; + use orion::operators::tensor::{Tensor, TensorTrait}; + use orion::numbers::fixed_point::{core::{FixedTrait}}; + + use orion::operators::tensor::{FP16x16Tensor, FP16x16TensorDiv, FP16x16TensorSub}; + + use orion::numbers::fixed_point::implementations::fp16x16::core::{ + FP16x16, FP16x16Impl, FP16x16Add, FP16x16AddEq, FP16x16Sub, FP16x16Mul, FP16x16MulEq, + FP16x16TryIntoU128, FP16x16PartialEq, FP16x16PartialOrd, FP16x16SubEq, FP16x16Neg, + FP16x16Div, FP16x16IntoFelt252, FP16x16Print + }; + + use lagrange::helper::lagrange_interpolation; + use lagrange::generated::{X::X, Y::Y, x::x, y::y}; + + #[test] + #[available_gas(99999999999999999)] + fn lagrange_test() { + let tol = FixedTrait::::new(655, false); // 655 is 0.01 = 1e-2 + let max_iter = 500_usize; + + // Nodes : + let X = X(); + let Y = Y(); + + let x = x(); + let y_expected = y(); + + let y_actual = lagrange_interpolation(@x, @X, @Y); + + let mut i = 0; + loop { + if i == y_expected.data.len() { + break; + } + + assert(*y_expected.data.at(i) - *y_actual.data.at(i) < tol, 'difference below threshold'); + i += 1; + } + } +} + +``` + +Our model will be tested using the `lagrange_test()` function, which will follow these steps: + +1. Data retrieval: The function starts by obtaining the X, Y nodes values and x, y test values coming from the generated folder. +2. Lagrange computation : computation of the y-values from the x-axis test values using the lagrange interpolation function on the nodes X and Y. + +Finally, we can execute the test file by running `scarb test` + +```shell +scarb test +testing lagrange ... +running 1 tests +test lagrange::test::tests::lagrange_test ... ok (gas usage est.: 672062330) +test result: ok. 1 passed; 0 failed; 0 ignored; 0 filtered out; +``` + +And as we can see our test cases have passed! 👏 + +If you've made it this far, well done! You are now capable of building verifiable ML models, making them ever more reliable and transparent than ever before. + +We invite the community to join us in forging a future in making AI transparent and reliable resource for all. From 86548d6c0424cbe351b7c632644dc7d2022e5fbc Mon Sep 17 00:00:00 2001 From: chachaleo Date: Sun, 17 Dec 2023 12:15:03 +0700 Subject: [PATCH 07/16] feat : LinearRegressor --- docgen/src/main.rs | 8 + .../complex-number/complex.to_polar.md | 5 - .../linear-regressor/README.md | 23 ++ .../linear_regressor.predict.md | 130 +++++++++++ src/operators/ml.cairo | 2 + src/operators/ml/linear.cairo | 1 + .../ml/linear/linear_regressor.cairo | 221 ++++++++++++++++++ tests/ml.cairo | 1 + tests/ml/linear_regressor_test.cairo | 114 +++++++++ 9 files changed, 500 insertions(+), 5 deletions(-) create mode 100644 docs/framework/operators/machine-learning/linear-regressor/README.md create mode 100644 docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md create mode 100644 src/operators/ml/linear.cairo create mode 100644 src/operators/ml/linear/linear_regressor.cairo create mode 100644 tests/ml/linear_regressor_test.cairo diff --git a/docgen/src/main.rs b/docgen/src/main.rs index 0e961599a..20426c832 100644 --- a/docgen/src/main.rs +++ b/docgen/src/main.rs @@ -58,6 +58,14 @@ fn main() { let trait_name: &str = "TreeEnsembleRegressorTrait"; doc_trait(trait_path, doc_path, label); doc_functions(trait_path, doc_path, trait_name, label); + + // LINEAR REGRESSOR DOC + let trait_path = "src/operators/ml/linear/linear_regressor.cairo"; + let doc_path = "docs/framework/operators/machine-learning/linear-regressor"; + let label = "linear_regressor"; + let trait_name: &str = "LinearRegressorTrait"; + doc_trait(trait_path, doc_path, label); + doc_functions(trait_path, doc_path, trait_name, label); } fn doc_trait(trait_path: &str, doc_path: &str, label: &str) { diff --git a/docs/framework/numbers/complex-number/complex.to_polar.md b/docs/framework/numbers/complex-number/complex.to_polar.md index 923387090..206c2e586 100644 --- a/docs/framework/numbers/complex-number/complex.to_polar.md +++ b/docs/framework/numbers/complex-number/complex.to_polar.md @@ -1,8 +1,3 @@ - -//fn log2(self: T) -> T; - -//fn log10(self: T) -> T; - # ComplexTrait::to_polar ```rust diff --git a/docs/framework/operators/machine-learning/linear-regressor/README.md b/docs/framework/operators/machine-learning/linear-regressor/README.md new file mode 100644 index 000000000..e67dd2fe8 --- /dev/null +++ b/docs/framework/operators/machine-learning/linear-regressor/README.md @@ -0,0 +1,23 @@ +# Linear Regressor + +`LinearRegressorTrait` provides a trait definition for linear regression problem. + +```rust +use orion::operators::ml::LinearRegressorTrait; +``` + +### Data types + +Orion supports currently only fixed point data types for `LinearRegressorTrait`. + +| Data type | dtype | +| -------------------- | ------------------------------------------------------------- | +| Fixed point (signed) | `LinearRegressorTrait` | + + +*** + +| function | description | +| --- | --- | +| [`linear_regressor.predict`](linear_regressor.predict.md) | Performs the generalized linear regression evaluation. | + diff --git a/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md b/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md new file mode 100644 index 000000000..dca7b5082 --- /dev/null +++ b/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md @@ -0,0 +1,130 @@ +# LinearRegressorTrait::predict + +```rust + fn predict(ref self: LinearRegressor, X: Tensor) -> Tensor; +``` + +Linear Regressor. Performs the generalized linear regression evaluation. + +## Args + +* `self`: LinearRegressor - A LinearRegressor object. +* `X`: Input 2D tensor. + +## Returns + +* Tensor containing the generalized linear regression evaluation of the input X. + +## Type Constraints + +`LinearRegressor` and `X` must be fixed points + +## Examples + +```rust +use orion::operators::tensor::{Tensor, TensorTrait, FP16x16Tensor, FP16x16TensorAdd}; +use orion::operators::ml::linear::linear_regressor::{ + LinearRegressorTrait, POST_TRANSFORM, LinearRegressor +}; +use orion::numbers::{FP16x16, FixedTrait}; + +fn example_linear_regressor() -> Tensor { + + let mut X: Tensor = TensorTrait::new( + array![3, 2].span(), + array![ + FP16x16 { mag: 0, sign: false }, + FP16x16 { mag: 65536, sign: false }, + FP16x16 { mag: 131072, sign: false }, + FP16x16 { mag: 196608, sign: false }, + FP16x16 { mag: 262144, sign: false }, + FP16x16 { mag: 327680, sign: false }, + ] + .span() + ); + + let coefficients: Span = array![ + FP16x16 { mag: 19661, sign: false }, + FP16x16 { mag: 50463, sign: true }, + + ] + .span(); + + let intercepts: Span = array![ + FP16x16 { mag: 32768, sign: false }, + + ] + .span(); + let intercepts = Option::Some(intercepts); + + let target : usize = 1; + let post_transform = POST_TRANSFORM::NONE; + + let mut regressor: LinearRegressor = LinearRegressor { + coefficients, + intercepts, + target, + post_transform + }; + + let scores = LinearRegressorTrait::predict(ref regressor, X); + + scores +} + +>>> +[[-0.27], [-1.21], [-2.15]] + + + +fn example_linear_regressor_2() -> Tensor { + + let mut X: Tensor = TensorTrait::new( + array![3, 2].span(), + array![ + FP16x16 { mag: 0, sign: false }, + FP16x16 { mag: 65536, sign: false }, + FP16x16 { mag: 131072, sign: false }, + FP16x16 { mag: 196608, sign: false }, + FP16x16 { mag: 262144, sign: false }, + FP16x16 { mag: 327680, sign: false }, + ] + .span() + ); + + let coefficients: Span = array![ + FP16x16 { mag: 19661, sign: false }, + FP16x16 { mag: 50463, sign: true }, + FP16x16 { mag: 19661, sign: false }, + FP16x16 { mag: 50463, sign: true }, + + ] + .span(); + + let intercepts: Span = array![ + FP16x16 { mag: 32768, sign: false }, + FP16x16 { mag: 45875, sign: false }, + + ] + .span(); + let intercepts = Option::Some(intercepts); + + let target = 2; + let post_transform = POST_TRANSFORM::NONE; + + let mut regressor: LinearRegressor = LinearRegressor { + coefficients, + intercepts, + target, + post_transform + }; + + let scores = LinearRegressorTrait::predict(ref regressor, X); + + scores +} + +>>> +[[-0.27, -0.07], [-1.21, -1.01], [-2.15, -1.95]] +``` + diff --git a/src/operators/ml.cairo b/src/operators/ml.cairo index 840375d07..4bfd10060 100644 --- a/src/operators/ml.cairo +++ b/src/operators/ml.cairo @@ -1,4 +1,5 @@ mod tree_ensemble; +mod linear; use orion::operators::ml::tree_ensemble::core::{ TreeEnsemble, TreeEnsembleAttributes, TreeEnsembleImpl, NODE_MODES @@ -10,3 +11,4 @@ use orion::operators::ml::tree_ensemble::tree_ensemble_classifier::{ use orion::operators::ml::tree_ensemble::tree_ensemble_regressor::{ TreeEnsembleRegressor, TreeEnsembleRegressorImpl, TreeEnsembleRegressorTrait, AGGREGATE_FUNCTION }; +use orion::operators::ml::linear::linear_regressor::{LinearRegressorTrait, LinearRegressorImpl, LinearRegressor}; diff --git a/src/operators/ml/linear.cairo b/src/operators/ml/linear.cairo new file mode 100644 index 000000000..bc8062bd1 --- /dev/null +++ b/src/operators/ml/linear.cairo @@ -0,0 +1 @@ +mod linear_regressor; diff --git a/src/operators/ml/linear/linear_regressor.cairo b/src/operators/ml/linear/linear_regressor.cairo new file mode 100644 index 000000000..1b7035e99 --- /dev/null +++ b/src/operators/ml/linear/linear_regressor.cairo @@ -0,0 +1,221 @@ +use core::array::ArrayTrait; +use core::clone::Clone; +use core::traits::Into; +use core::array::SpanTrait; +use core::dict::Felt252DictTrait; +use core::dict::Felt252DictEntryTrait; +use orion::numbers::FP16x16; + +use orion::operators::tensor::{Tensor, TensorTrait}; +use orion::numbers::NumberTrait; +use orion::operators::tensor::{I8Tensor, I32Tensor, U32Tensor, FP16x16Tensor, FP16x16TensorAdd}; +use orion::numbers::{FP32x32, FP32x32Impl, FixedTrait}; + +use core::debug::PrintTrait; + +#[derive(Destruct)] +struct LinearRegressor { + coefficients: Span, + intercepts: Option>, + target: usize, + post_transform: POST_TRANSFORM, +} + +#[derive(Copy, Drop)] +enum POST_TRANSFORM { + NONE, + SOFTMAX, + LOGISTIC, + SOFTMAXZERO, + PROBIT, +} + +/// Trait +/// +/// predict - Performs the generalized linear regression evaluation. +trait LinearRegressorTrait { + /// # LinearRegressorTrait::predict + /// + /// ```rust + /// fn predict(ref self: LinearRegressor, X: Tensor) -> Tensor; + /// ``` + /// + /// Linear Regressor. Performs the generalized linear regression evaluation. + /// + /// ## Args + /// + /// * `self`: LinearRegressor - A LinearRegressor object. + /// * `X`: Input 2D tensor. + /// + /// ## Returns + /// + /// * Tensor containing the generalized linear regression evaluation of the input X. + /// + /// ## Type Constraints + /// + /// `LinearRegressor` and `X` must be fixed points + /// + /// ## Examples + /// + /// ```rust + /// use orion::operators::tensor::{Tensor, TensorTrait, FP16x16Tensor, U32Tensor, FP16x16TensorAdd}; + /// use orion::operators::ml::linear::linear_regressor::{ + /// LinearRegressorTrait, POST_TRANSFORM, LinearRegressor + /// }; + /// use orion::numbers::{FP16x16, FixedTrait}; + /// + /// fn example_linear_regressor() -> Tensor { + /// + /// let mut X: Tensor = TensorTrait::new( + /// array![3, 2].span(), + /// array![ + /// FP16x16 { mag: 0, sign: false }, + /// FP16x16 { mag: 65536, sign: false }, + /// FP16x16 { mag: 131072, sign: false }, + /// FP16x16 { mag: 196608, sign: false }, + /// FP16x16 { mag: 262144, sign: false }, + /// FP16x16 { mag: 327680, sign: false }, + /// ] + /// .span() + /// ); + /// + /// let coefficients: Span = array![ + /// FP16x16 { mag: 19661, sign: false }, + /// FP16x16 { mag: 50463, sign: true }, + /// + /// ] + /// .span(); + /// + /// let intercepts: Span = array![ + /// FP16x16 { mag: 32768, sign: false }, + /// + /// ] + /// .span(); + /// let intercepts = Option::Some(intercepts); + /// + /// let target : usize = 1; + /// let post_transform = POST_TRANSFORM::NONE; + /// + /// let mut regressor: LinearRegressor = LinearRegressor { + /// coefficients, + /// intercepts, + /// target, + /// post_transform + /// }; + /// + /// let scores = LinearRegressorTrait::predict(ref regressor, X); + /// + /// scores + /// } + /// + /// >>> + /// [[-0.27], [-1.21], [-2.15]] + /// + /// + /// + /// fn example_linear_regressor_2() -> Tensor { + /// + /// let mut X: Tensor = TensorTrait::new( + /// array![3, 2].span(), + /// array![ + /// FP16x16 { mag: 0, sign: false }, + /// FP16x16 { mag: 65536, sign: false }, + /// FP16x16 { mag: 131072, sign: false }, + /// FP16x16 { mag: 196608, sign: false }, + /// FP16x16 { mag: 262144, sign: false }, + /// FP16x16 { mag: 327680, sign: false }, + /// ] + /// .span() + /// ); + /// + /// let coefficients: Span = array![ + /// FP16x16 { mag: 19661, sign: false }, + /// FP16x16 { mag: 50463, sign: true }, + /// FP16x16 { mag: 19661, sign: false }, + /// FP16x16 { mag: 50463, sign: true }, + /// + /// ] + /// .span(); + /// + /// let intercepts: Span = array![ + /// FP16x16 { mag: 32768, sign: false }, + /// FP16x16 { mag: 45875, sign: false }, + /// + /// ] + /// .span(); + /// let intercepts = Option::Some(intercepts); + /// + /// let target = 2; + /// let post_transform = POST_TRANSFORM::NONE; + /// + /// let mut regressor: LinearRegressor = LinearRegressor { + /// coefficients, + /// intercepts, + /// target, + /// post_transform + /// }; + /// + /// let scores = LinearRegressorTrait::predict(ref regressor, X); + /// + /// scores + /// } + /// + /// >>> + /// [[-0.27, -0.07], [-1.21, -1.01], [-2.15, -1.95]] + /// ``` + /// + /// + + fn predict(ref self: LinearRegressor, X: Tensor) -> Tensor; +} + +impl LinearRegressorImpl< + T, + MAG, + +Drop, + +Copy, + +NumberTrait, + +PartialOrd, + +PartialEq, + +Add, + +TensorTrait, + +TensorTrait, + +PrintTrait, + +AddEq, + +Div, + +Mul, + +Add>, +> of LinearRegressorTrait { + fn predict(ref self: LinearRegressor, X: Tensor) -> Tensor { + let n: usize = self.coefficients.len() / self.target; + let mut shape = ArrayTrait::::new(); + shape.append(self.target); + shape.append(n); + let mut coefficients = TensorTrait::new(shape.span(), self.coefficients); + + let coefficients = coefficients.transpose(array![1, 0].span()); + let mut score = X.matmul(@coefficients); + + match self.intercepts { + Option::Some(intercepts) => { + let mut shape = ArrayTrait::::new(); + shape.append(1); + shape.append(intercepts.len()); + let intercepts = TensorTrait::new(shape.span(), intercepts); + score = TensorTrait::add(score, intercepts); + }, + Option::None(_) => {}, + }; + + // Post Transform + let mut new_scores = match self.post_transform { + POST_TRANSFORM::NONE => {}, + POST_TRANSFORM::SOFTMAX => core::panic_with_felt252('SOFTMAX not implemented'), + POST_TRANSFORM::LOGISTIC => core::panic_with_felt252('LOGISTIC not implemented'), + POST_TRANSFORM::SOFTMAXZERO => core::panic_with_felt252('SOFTMAXZERO implemented'), + POST_TRANSFORM::PROBIT => core::panic_with_felt252('PROBIT not implemented'), + }; + + score + } +} diff --git a/tests/ml.cairo b/tests/ml.cairo index cc226c161..bb54ef56f 100644 --- a/tests/ml.cairo +++ b/tests/ml.cairo @@ -1,3 +1,4 @@ mod tree_ensemble_classifier; mod tree_ensemble_regressor; +mod linear_regressor_test; diff --git a/tests/ml/linear_regressor_test.cairo b/tests/ml/linear_regressor_test.cairo new file mode 100644 index 000000000..2465ec99a --- /dev/null +++ b/tests/ml/linear_regressor_test.cairo @@ -0,0 +1,114 @@ +use orion::operators::tensor::{Tensor, TensorTrait, FP16x16Tensor, U32Tensor, FP16x16TensorAdd}; +use orion::operators::ml::linear::linear_regressor::{ + LinearRegressorTrait, POST_TRANSFORM, LinearRegressor +}; +use orion::numbers::{FP16x16, FixedTrait}; + +use core::debug::PrintTrait; + + +#[test] +#[available_gas(200000000000)] +fn test_linear_regressor() { + + let mut X: Tensor = TensorTrait::new( + array![3, 2].span(), + array![ + FP16x16 { mag: 0, sign: false }, + FP16x16 { mag: 65536, sign: false }, + FP16x16 { mag: 131072, sign: false }, + FP16x16 { mag: 196608, sign: false }, + FP16x16 { mag: 262144, sign: false }, + FP16x16 { mag: 327680, sign: false }, + ] + .span() + ); + + let coefficients: Span = array![ + FP16x16 { mag: 19661, sign: false }, + FP16x16 { mag: 50463, sign: true }, + + ] + .span(); + + let intercepts: Span = array![ + FP16x16 { mag: 32768, sign: false }, + + ] + .span(); + let intercepts = Option::Some(intercepts); + + let target : usize = 1; + let post_transform = POST_TRANSFORM::NONE; + + let mut regressor: LinearRegressor = LinearRegressor { + coefficients, + intercepts, + target, + post_transform + }; + + let scores = LinearRegressorTrait::predict(ref regressor, X); + + assert(*scores.data[0] == FP16x16 { mag: 17695, sign: true }, '*scores[0] == -0.27'); + assert(*scores.data[1] == FP16x16 { mag: 79299, sign: true }, '*scores[1] == -1.21'); + assert(*scores.data[2] == FP16x16 { mag: 140903, sign: true }, '*scores[2] == -2.15'); + + +} + +#[test] +#[available_gas(200000000000)] +fn test_linear_regressor_2() { + + let mut X: Tensor = TensorTrait::new( + array![3, 2].span(), + array![ + FP16x16 { mag: 0, sign: false }, + FP16x16 { mag: 65536, sign: false }, + FP16x16 { mag: 131072, sign: false }, + FP16x16 { mag: 196608, sign: false }, + FP16x16 { mag: 262144, sign: false }, + FP16x16 { mag: 327680, sign: false }, + ] + .span() + ); + + let coefficients: Span = array![ + FP16x16 { mag: 19661, sign: false }, + FP16x16 { mag: 50463, sign: true }, + FP16x16 { mag: 19661, sign: false }, + FP16x16 { mag: 50463, sign: true }, + + ] + .span(); + + let intercepts: Span = array![ + FP16x16 { mag: 32768, sign: false }, + FP16x16 { mag: 45875, sign: false }, + + ] + .span(); + let intercepts = Option::Some(intercepts); + + let target = 2; + let post_transform = POST_TRANSFORM::NONE; + + let mut regressor: LinearRegressor = LinearRegressor { + coefficients, + intercepts, + target, + post_transform + }; + + let scores = LinearRegressorTrait::predict(ref regressor, X); + + + assert(*scores.data[0] == FP16x16 { mag: 17695, sign: true }, '*scores[0] == -0.27'); + assert(*scores.data[1] == FP16x16 { mag: 4588, sign: true }, '*scores[1] == -0.07'); + assert(*scores.data[2] == FP16x16 { mag: 79299, sign: true }, '*scores[2] == -1.21'); + assert(*scores.data[3] == FP16x16 { mag: 66192, sign: true }, '*scores[3] == -1.01'); + assert(*scores.data[4] == FP16x16 { mag: 140903, sign: true },'*scores[4] == -2.15'); + assert(*scores.data[5] == FP16x16 { mag: 127796, sign: true },'*scores[5] == -1.95'); + +} From 3b2f5468fb654c2d3ad68379df677ee9b081d8e3 Mon Sep 17 00:00:00 2001 From: chachaleo Date: Sun, 17 Dec 2023 12:35:57 +0700 Subject: [PATCH 08/16] remove tuto --- docs/academy/tutorials/README.md | 6 - .../verifiable-Lagrange-interpolation.md | 350 ------------------ 2 files changed, 356 deletions(-) delete mode 100755 docs/academy/tutorials/verifiable-Lagrange-interpolation.md diff --git a/docs/academy/tutorials/README.md b/docs/academy/tutorials/README.md index 2a2b57f42..a5d0f4694 100644 --- a/docs/academy/tutorials/README.md +++ b/docs/academy/tutorials/README.md @@ -2,12 +2,6 @@ Learn how to use Orion with tutorials. We encourage you to contribute by sharing your own tutorial. -## [Verifiable Lagrange Interpolation](verifiable-Lagrange-interpolation.md) - -Lagrange interpolation is a mathematical technique used to approximate a function that passes through a given set of points. It takes an input set of data points and computes a polynomial that passes through all of them. - -_December 14, 2023 chachaleo_ - ## [Verifiable Principal Components Analysis](verifiable-principal-components-analysis.md) diff --git a/docs/academy/tutorials/verifiable-Lagrange-interpolation.md b/docs/academy/tutorials/verifiable-Lagrange-interpolation.md deleted file mode 100755 index 38f887406..000000000 --- a/docs/academy/tutorials/verifiable-Lagrange-interpolation.md +++ /dev/null @@ -1,350 +0,0 @@ -# **Verifiable Lagrange interpolation** - -Lagrange interpolation is a mathematical technique used to approximate a function that passes through a given set of points. It takes an input set of data points and computes a polynomial that passes through all of them. - -Given a set of $n+1$ data points (or interpolation nodes) $X_0, X_1, ..., X_n$ with corresponding function values $Y_0, Y_1, ..., Y_n$, Lagrange interpolation seeks to find a polynomial of degree at most $n$ that passes through all these points. - -Below, we provide a brief review of the implementation of a Lagrange interpolation in Python, which we will then convert to Cairo to transform it into a verifiable ZKML (Lagrange interpolation), using the Orion library. - -Content overview: - -1. [Lagrange interpolation with Python:](LagrangeInterpolationTutorial.md#used-dataset) We start with the basic implementation of Lagrange interpolation using Python. -2. [Convert your model to Cairo:](LagrangeInterpolationTutorial.md#convert-your-model-to-cairo) In the subsequent stage, we will create a new scarb project and replicate our model to Cairo which is a language for creating STARK-provable programs. -3. [Implementing Lagrange interpolation using Orion:](LagrangeInterpolationTutorial.md#implementing-lagrange-using-orion) To catalyze our development process, we will use the Orion Framework to construct the key functions to build our verifiable Lagrange interpolation. - -### Used DataSet - -In this tutorial, we will interpolate the Runge function, that we will define $f$ and uses the Chebyshev node as interpolation nodes. - -```python -import numpy as np -import math -import matplotlib.pyplot as plt - -# Runge function -def f(x): - return 1 / (x**2 + 1) - -# Chebyshev nodes -X = np.array( [5*math.cos(k*math.pi/10) for k in range(0,11)] ) - -Y = f(X) - -``` - - -### Implementation of Lagrange interpolating polynomial - -Now we will implement Lagrange interpolation function in python. - -Given a set of $n+1$ data points $X_0, X_1, ..., X_n$ with corresponding function values $Y_0, Y_1, ..., Y_n$, the Lagrange interpolating polynomial is - -$$ - L(x) = \sum_{i=0}^n Y_i \phi_i(x), -$$ - -where $\phi_i(x)$ is the $i$-th Lagrange polynomial defined by -$$ - \phi_i(x) = \frac{(x - X_0)\ldots (x - X_{i-1})(x - X_{i+1})\ldots(x - X_n)}{(X_i - X_0)\ldots (X_i - X_{i-1})(X_i - X_{i+1})\ldots(X_i - X_n)} - -$$ - -```python -def lagrange(x,X,Y): - - n = min(len(X),len(Y)) - m = len(x) - yh = np.zeros(m) - phi = np.zeros(n) - for j in range(m): - yh[j] = 0 - for i in range(n): - phi[i] = 1.0 - for k in range(n): - if i != k: - phi[i] = phi[i]*(x[j]-X[k])/(X[i]-X[k]) - yh[j] = yh[j] + Y[i] * phi[i] - return yh -``` - - - - -## Visualization of the interpolation - - -```python -x = np.linspace(-5,5,num=100) -fx = f(x) -y = lagrange(x,X,Y) - -fig, ax = plt.subplots() -ax.set_title('Lagrange interpolation of Runge function', fontsize = 15) -ax.plot(x,fx,label='Runge function') -ax.plot(x,y,label='Lagrange interpolation') -plt.legend() -plt.show() -``` - -
- - -## Convert your model to Cairo - -Now that we have a good understanding of the Lagrange interpolation, we will replicate the entire algorithm in Cairo to make it fully verifiable. Since we will be rebuilding the algorithm from scratch, this will be a good opportunity to get acquainted with Orion's built-in functions and the operators that make the transition to Cairo seamless. - -### Create a new Scarb project - -Scarb is the Cairo package manager specifically created to streamline our Cairo and Starknet development process. Scarb will typically manage project dependencies, the compilation process (both pure Cairo and Starknet contracts), downloading and building external libraries to accelerate our development with Orion.You can find all information about Scarb and Cairo installation [here](https://orion.gizatech.xyz/v/develop/framework/get-started#installations). - -To create a new Scarb project, open your terminal and run: - -``` -scarb new verifiable_Lagrange_interpolation -``` - -A new project folder will be created for you and make sure to replace the content in Scarb.toml file with the following code: - -```toml -[package] -name = "scarb new verifiable_Lagrange_interpolation" -version = "0.1.0" - -[dependencies] -orion = { git = "https://github.com/gizatechxyz/orion.git", rev = "v0.1.9" } -``` - -### Gerating the dataset in Cairo - -Now let's generate the necessary files to begin our transition to Cairo. In our Jupyter Notebook, we will run the necessary code to convert our interpolation nodes and the interpolation result as fixed point tensors in Orion. - -```python -import os -``` - -```python -os.makedirs("src/generated", exist_ok=True) -``` - -```python -tensor_name = ["X","Y","x","y"] - -def generate_cairo_files(data, name): - - with open(os.path.join('src', 'generated', f"{name}.cairo"), "w") as f: - f.write( - "use array::{ArrayTrait, SpanTrait};\n" + - "use orion::operators::tensor::{core::{Tensor, TensorTrait}};\n" + - "use orion::operators::tensor::FP16x16Tensor;\n" + - "use orion::numbers::fixed_point::implementations::fp16x16::core::{FP16x16, FixedTrait};\n" + - "\n" + f"fn {name}() -> Tensor" + "{\n\n" + - "let mut shape = ArrayTrait::new();\n" - ) - for dim in data.shape: - f.write(f"shape.append({dim});\n") - - f.write("let mut data = ArrayTrait::new();\n") - for val in np.nditer(data.flatten()): - f.write(f"data.append(FixedTrait::new({abs(int(decimal_to_fp16x16(val)))}, {str(val < 0).lower()}));\n") - f.write( - "let tensor = TensorTrait::::new(shape.span(), data.span());\n" + - "return tensor;\n}" - ) - -with open(f"src/generated.cairo", "w") as f: - for n in tensor_name: - f.write(f"mod {n};\n") - -generate_cairo_files(X, "X") -generate_cairo_files(Y, "Y") - -generate_cairo_files(x, "x") -generate_cairo_files(y, "y") -``` - -The X, Y, x, y tensor values will now be generated under `src/generated` directory. - -In `src/lib.cairo` replace the content with the following code: - -```rust -mod generated; -mod helper; -mod test; -``` - -This will tell our compiler to include the separate modules listed above during the compilation of our code. We will be covering each module in detail in the following section, but let’s first review the generated folder files. - -```rust -use array::{ArrayTrait, SpanTrait}; -use orion::operators::tensor::{core::{Tensor, TensorTrait}}; -use orion::operators::tensor::FP16x16Tensor; -use orion::numbers::fixed_point::implementations::fp16x16::core::{FP16x16, FixedTrait}; - -fn X() -> Tensor{ - -let mut shape = ArrayTrait::new(); -shape.append(11); -let mut data = ArrayTrait::new(); -data.append(FixedTrait::new(327680, false)); -data.append(FixedTrait::new(311642, false)); -data.append(FixedTrait::new(265098, false)); -data.append(FixedTrait::new(192605, false)); -data.append(FixedTrait::new(101258, false)); -data.append(FixedTrait::new(0, false)); -data.append(FixedTrait::new(101258, true)); -data.append(FixedTrait::new(192605, true)); -data.append(FixedTrait::new(265098, true)); -data.append(FixedTrait::new(311642, true)); -data.append(FixedTrait::new(327680, true)); -let tensor = TensorTrait::::new(shape.span(), data.span()); -return tensor; -} -``` - -Since Cairo does not come with built-in fixed points we have to explicitly define it for our X, Y, x, y values. Luckily, this is already implemented in Orion for us as a struct as shown below: - - -```rust -// Example of a FP16x16. -struct FP16x16 { - mag: u32, - sign: bool -} -``` - -For this tutorial, we will use fixed point numbers FP16x16 where the magnitude represents the absolute value and the boolean indicates whether the number is negative or positive. In a 16x16 fixed-point format, there are 16 bits dedicated to the integer part of the number and 16 bits for the fractional part of the number. This format allows us to work with a wide range of values and a high degree of precision for conducting the Tensor operations. To replicate the Lagrange interpolation function, we will conduct our operations using FP16x16 Tensors which are also represented as a structs in Orion. - -```rust -struct Tensor { - shape: Span, - data: Span -} -``` - -A `Tensor` in Orion takes a shape and a span array of the data. - -## Implementing Lagrange interpolation using Orion - -At this stage, we will be reproducing the Lagrange interpolation function now that we have generated our X, Y, x, y Fixedpoint Tensors. We will begin by creating a separate file for our Lagrange interpolation function file named `helper.cairo` to host all of our core functions. - -### Lagrange interpolation function - -```rust -fn lagrange_interpolation(x_interpolated: @Tensor, X: @Tensor, Y: @Tensor) -> Tensor { - - let n = ((*X).data.len()); - let m = ((*x_interpolated).data.len()); - - let mut y_data = ArrayTrait::::new(); - let mut phi = ArrayTrait::::new(); - let mut j = 0; - - loop { - if j == m { - break; - } - let mut y_j = FixedTrait::new(0,true); - let mut i = 0; - loop { - if i == n { - break; - } - let mut phi_i = FixedTrait::::new(65536,true); - let mut k = 0; - loop { - if k == n { - break; - } - if i != k { - phi_i = phi_i * (*(*x_interpolated).data.at(j) - *(*X).data.at(k))/( *(*X).data.at(i) - *(*X).data.at(k)) - } - k += 1; - }; - y_j = y_j + *(*Y).data.at(i) * phi_i; - i += 1; - }; - y_data.append(y_j); - j += 1; - - }; - - return TensorTrait::new((*x_interpolated).shape, y_data.span()); - -} - -``` - - -### Testing the model - -Now that we have implemented the Lagrange interpolation function, we can finally test it. We begin by creating a new separate test file named `test.cairo` and import all the necessary Orion libraries, including our X, Y, x and y values found in the generated folder. We also import the Lagrange function from the `helper.cairo` file, as we will rely on them to construct the model. - -```rust -#[cfg(test)] -mod tests { - use traits::TryInto; - use alexandria_data_structures::array_ext::{SpanTraitExt}; - use array::{ArrayTrait, SpanTrait}; - use orion::operators::tensor::{Tensor, TensorTrait}; - use orion::numbers::fixed_point::{core::{FixedTrait}}; - - use orion::operators::tensor::{FP16x16Tensor, FP16x16TensorDiv, FP16x16TensorSub}; - - use orion::numbers::fixed_point::implementations::fp16x16::core::{ - FP16x16, FP16x16Impl, FP16x16Add, FP16x16AddEq, FP16x16Sub, FP16x16Mul, FP16x16MulEq, - FP16x16TryIntoU128, FP16x16PartialEq, FP16x16PartialOrd, FP16x16SubEq, FP16x16Neg, - FP16x16Div, FP16x16IntoFelt252, FP16x16Print - }; - - use lagrange::helper::lagrange_interpolation; - use lagrange::generated::{X::X, Y::Y, x::x, y::y}; - - #[test] - #[available_gas(99999999999999999)] - fn lagrange_test() { - let tol = FixedTrait::::new(655, false); // 655 is 0.01 = 1e-2 - let max_iter = 500_usize; - - // Nodes : - let X = X(); - let Y = Y(); - - let x = x(); - let y_expected = y(); - - let y_actual = lagrange_interpolation(@x, @X, @Y); - - let mut i = 0; - loop { - if i == y_expected.data.len() { - break; - } - - assert(*y_expected.data.at(i) - *y_actual.data.at(i) < tol, 'difference below threshold'); - i += 1; - } - } -} - -``` - -Our model will be tested using the `lagrange_test()` function, which will follow these steps: - -1. Data retrieval: The function starts by obtaining the X, Y nodes values and x, y test values coming from the generated folder. -2. Lagrange computation : computation of the y-values from the x-axis test values using the lagrange interpolation function on the nodes X and Y. - -Finally, we can execute the test file by running `scarb test` - -```shell -scarb test -testing lagrange ... -running 1 tests -test lagrange::test::tests::lagrange_test ... ok (gas usage est.: 672062330) -test result: ok. 1 passed; 0 failed; 0 ignored; 0 filtered out; -``` - -And as we can see our test cases have passed! 👏 - -If you've made it this far, well done! You are now capable of building verifiable ML models, making them ever more reliable and transparent than ever before. - -We invite the community to join us in forging a future in making AI transparent and reliable resource for all. From e11201ac5da986cbc4907c899bc39dc6052871e7 Mon Sep 17 00:00:00 2001 From: chachaleo Date: Mon, 18 Dec 2023 17:00:15 +0700 Subject: [PATCH 09/16] post transform --- .../linear_regressor.predict.md | 3 +- src/operators/ml.cairo | 3 ++ .../ml/linear/linear_regressor.cairo | 17 ++++--- tests/ml/linear_regressor_test.cairo | 45 ++++++------------- 4 files changed, 29 insertions(+), 39 deletions(-) diff --git a/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md b/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md index dca7b5082..f1bd38831 100644 --- a/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md +++ b/docs/framework/operators/machine-learning/linear-regressor/linear_regressor.predict.md @@ -22,11 +22,12 @@ Linear Regressor. Performs the generalized linear regression evaluation. ## Examples ```rust -use orion::operators::tensor::{Tensor, TensorTrait, FP16x16Tensor, FP16x16TensorAdd}; +use orion::operators::tensor::{Tensor, TensorTrait, FP16x16Tensor, U32Tensor, FP16x16TensorAdd}; use orion::operators::ml::linear::linear_regressor::{ LinearRegressorTrait, POST_TRANSFORM, LinearRegressor }; use orion::numbers::{FP16x16, FixedTrait}; +use orion::operators::nn::{NNTrait, FP16x16NN}; fn example_linear_regressor() -> Tensor { diff --git a/src/operators/ml.cairo b/src/operators/ml.cairo index 4bfd10060..311287115 100644 --- a/src/operators/ml.cairo +++ b/src/operators/ml.cairo @@ -12,3 +12,6 @@ use orion::operators::ml::tree_ensemble::tree_ensemble_regressor::{ TreeEnsembleRegressor, TreeEnsembleRegressorImpl, TreeEnsembleRegressorTrait, AGGREGATE_FUNCTION }; use orion::operators::ml::linear::linear_regressor::{LinearRegressorTrait, LinearRegressorImpl, LinearRegressor}; +use orion::operators::ml::linear::linear_regressor::{ + LinearRegressorTrait, LinearRegressorImpl, LinearRegressor +}; diff --git a/src/operators/ml/linear/linear_regressor.cairo b/src/operators/ml/linear/linear_regressor.cairo index 1b7035e99..c9374a4cd 100644 --- a/src/operators/ml/linear/linear_regressor.cairo +++ b/src/operators/ml/linear/linear_regressor.cairo @@ -12,6 +12,7 @@ use orion::operators::tensor::{I8Tensor, I32Tensor, U32Tensor, FP16x16Tensor, FP use orion::numbers::{FP32x32, FP32x32Impl, FixedTrait}; use core::debug::PrintTrait; +use orion::operators::nn::{NNTrait, FP16x16NN}; #[derive(Destruct)] struct LinearRegressor { @@ -63,6 +64,7 @@ trait LinearRegressorTrait { /// LinearRegressorTrait, POST_TRANSFORM, LinearRegressor /// }; /// use orion::numbers::{FP16x16, FixedTrait}; + /// use orion::operators::nn::{NNTrait, FP16x16NN}; /// /// fn example_linear_regressor() -> Tensor { /// @@ -185,6 +187,7 @@ impl LinearRegressorImpl< +Div, +Mul, +Add>, + +NNTrait, > of LinearRegressorTrait { fn predict(ref self: LinearRegressor, X: Tensor) -> Tensor { let n: usize = self.coefficients.len() / self.target; @@ -208,12 +211,14 @@ impl LinearRegressorImpl< }; // Post Transform - let mut new_scores = match self.post_transform { - POST_TRANSFORM::NONE => {}, - POST_TRANSFORM::SOFTMAX => core::panic_with_felt252('SOFTMAX not implemented'), - POST_TRANSFORM::LOGISTIC => core::panic_with_felt252('LOGISTIC not implemented'), - POST_TRANSFORM::SOFTMAXZERO => core::panic_with_felt252('SOFTMAXZERO implemented'), - POST_TRANSFORM::PROBIT => core::panic_with_felt252('PROBIT not implemented'), + let score = match self.post_transform { + POST_TRANSFORM::NONE => score, // No action required + POST_TRANSFORM::SOFTMAX => NNTrait::softmax(@score, 1), + POST_TRANSFORM::LOGISTIC => NNTrait::sigmoid(@score), + POST_TRANSFORM::SOFTMAXZERO => core::panic_with_felt252( + 'Softmax_zero not supported yet' + ), + POST_TRANSFORM::PROBIT => core::panic_with_felt252('Probit not supported yet'), }; score diff --git a/tests/ml/linear_regressor_test.cairo b/tests/ml/linear_regressor_test.cairo index 2465ec99a..1aa7a4211 100644 --- a/tests/ml/linear_regressor_test.cairo +++ b/tests/ml/linear_regressor_test.cairo @@ -6,11 +6,12 @@ use orion::numbers::{FP16x16, FixedTrait}; use core::debug::PrintTrait; +use orion::operators::nn::{NNTrait, FP16x16NN}; + #[test] #[available_gas(200000000000)] fn test_linear_regressor() { - let mut X: Tensor = TensorTrait::new( array![3, 2].span(), array![ @@ -25,27 +26,18 @@ fn test_linear_regressor() { ); let coefficients: Span = array![ - FP16x16 { mag: 19661, sign: false }, - FP16x16 { mag: 50463, sign: true }, - + FP16x16 { mag: 19661, sign: false }, FP16x16 { mag: 50463, sign: true }, ] .span(); - let intercepts: Span = array![ - FP16x16 { mag: 32768, sign: false }, - - ] - .span(); - let intercepts = Option::Some(intercepts); + let intercepts: Span = array![FP16x16 { mag: 32768, sign: false },].span(); + let intercepts = Option::Some(intercepts); - let target : usize = 1; + let target: usize = 1; let post_transform = POST_TRANSFORM::NONE; let mut regressor: LinearRegressor = LinearRegressor { - coefficients, - intercepts, - target, - post_transform + coefficients, intercepts, target, post_transform }; let scores = LinearRegressorTrait::predict(ref regressor, X); @@ -53,14 +45,11 @@ fn test_linear_regressor() { assert(*scores.data[0] == FP16x16 { mag: 17695, sign: true }, '*scores[0] == -0.27'); assert(*scores.data[1] == FP16x16 { mag: 79299, sign: true }, '*scores[1] == -1.21'); assert(*scores.data[2] == FP16x16 { mag: 140903, sign: true }, '*scores[2] == -2.15'); - - } #[test] #[available_gas(200000000000)] fn test_linear_regressor_2() { - let mut X: Tensor = TensorTrait::new( array![3, 2].span(), array![ @@ -79,36 +68,28 @@ fn test_linear_regressor_2() { FP16x16 { mag: 50463, sign: true }, FP16x16 { mag: 19661, sign: false }, FP16x16 { mag: 50463, sign: true }, - ] .span(); let intercepts: Span = array![ - FP16x16 { mag: 32768, sign: false }, - FP16x16 { mag: 45875, sign: false }, - + FP16x16 { mag: 32768, sign: false }, FP16x16 { mag: 45875, sign: false }, ] .span(); - let intercepts = Option::Some(intercepts); + let intercepts = Option::Some(intercepts); let target = 2; let post_transform = POST_TRANSFORM::NONE; let mut regressor: LinearRegressor = LinearRegressor { - coefficients, - intercepts, - target, - post_transform + coefficients, intercepts, target, post_transform }; let scores = LinearRegressorTrait::predict(ref regressor, X); - assert(*scores.data[0] == FP16x16 { mag: 17695, sign: true }, '*scores[0] == -0.27'); - assert(*scores.data[1] == FP16x16 { mag: 4588, sign: true }, '*scores[1] == -0.07'); + assert(*scores.data[1] == FP16x16 { mag: 4588, sign: true }, '*scores[1] == -0.07'); assert(*scores.data[2] == FP16x16 { mag: 79299, sign: true }, '*scores[2] == -1.21'); assert(*scores.data[3] == FP16x16 { mag: 66192, sign: true }, '*scores[3] == -1.01'); - assert(*scores.data[4] == FP16x16 { mag: 140903, sign: true },'*scores[4] == -2.15'); - assert(*scores.data[5] == FP16x16 { mag: 127796, sign: true },'*scores[5] == -1.95'); - + assert(*scores.data[4] == FP16x16 { mag: 140903, sign: true }, '*scores[4] == -2.15'); + assert(*scores.data[5] == FP16x16 { mag: 127796, sign: true }, '*scores[5] == -1.95'); } From a6741259f6389fba2b864c92f393d990d1952263 Mon Sep 17 00:00:00 2001 From: chachaleo Date: Mon, 18 Dec 2023 17:05:57 +0700 Subject: [PATCH 10/16] post transform --- tests/lib.cairo | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/lib.cairo b/tests/lib.cairo index c408347ef..f5cecb77d 100644 --- a/tests/lib.cairo +++ b/tests/lib.cairo @@ -5,4 +5,3 @@ mod nodes; mod ml; mod operators; - From 3330dd0d0ee7f9dba560b8b6da59213f5b775fc5 Mon Sep 17 00:00:00 2001 From: chachaleo Date: Mon, 18 Dec 2023 17:24:09 +0700 Subject: [PATCH 11/16] rebase error fix --- src/operators/ml.cairo | 3 --- 1 file changed, 3 deletions(-) diff --git a/src/operators/ml.cairo b/src/operators/ml.cairo index 311287115..4bfd10060 100644 --- a/src/operators/ml.cairo +++ b/src/operators/ml.cairo @@ -12,6 +12,3 @@ use orion::operators::ml::tree_ensemble::tree_ensemble_regressor::{ TreeEnsembleRegressor, TreeEnsembleRegressorImpl, TreeEnsembleRegressorTrait, AGGREGATE_FUNCTION }; use orion::operators::ml::linear::linear_regressor::{LinearRegressorTrait, LinearRegressorImpl, LinearRegressor}; -use orion::operators::ml::linear::linear_regressor::{ - LinearRegressorTrait, LinearRegressorImpl, LinearRegressor -}; From dbcae814fdea4bdd99d026f3b3bfad424ecfd77d Mon Sep 17 00:00:00 2001 From: raphaelDkhn <113879115+raphaelDkhn@users.noreply.github.com> Date: Tue, 19 Dec 2023 16:48:48 +0200 Subject: [PATCH 12/16] Update orion-usage.md --- orion-usage.md | 1 + 1 file changed, 1 insertion(+) diff --git a/orion-usage.md b/orion-usage.md index 7a29e1a6d..31a23458e 100644 --- a/orion-usage.md +++ b/orion-usage.md @@ -57,3 +57,4 @@ Discover amazing ML apps and POCs made by the community with Orion! | StorSwift | Verifiable Medical Diagnosis | A verifiable medical diagnosis web3 app. The aim is to create a robust and reliable platform to empower individuals in their healthcare decision-making process | | dblancove & dataonchain | Fraud Detection with Verifiable ML | A verifiable anomaly detection model in fraud detection and analysis of bank transaction alerts. | | John William Q. Embate, Plutarch Romiel Degollacion|[ZKML Solar PV Positioning Optimizer Module](https://taikai.network/starkware/hackathons/starknet-infra-hackathon/projects/clpnv5gav00d6x401lol9jaf8/idea) | The ZKML-powered Solar PV Positioning Optimizer Module ensures efficient solar energy use through data-driven reporting and precise PV positioning in the pre-installation phase. | +| Zion | Onairos | Onairos is a groundbreaking platform that combines the power of AI, Data Privacy, and Blockchain to create digital personalities. These digital personalities represent individuals and help users interact with the online world while retaining control over their data | From a7d0f76b23189506c3588d0214dcbc177f09c783 Mon Sep 17 00:00:00 2001 From: raphaelDkhn <113879115+raphaelDkhn@users.noreply.github.com> Date: Tue, 19 Dec 2023 16:51:10 +0200 Subject: [PATCH 13/16] Update orion-usage.md --- orion-usage.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/orion-usage.md b/orion-usage.md index 31a23458e..a2d14aafe 100644 --- a/orion-usage.md +++ b/orion-usage.md @@ -57,4 +57,4 @@ Discover amazing ML apps and POCs made by the community with Orion! | StorSwift | Verifiable Medical Diagnosis | A verifiable medical diagnosis web3 app. The aim is to create a robust and reliable platform to empower individuals in their healthcare decision-making process | | dblancove & dataonchain | Fraud Detection with Verifiable ML | A verifiable anomaly detection model in fraud detection and analysis of bank transaction alerts. | | John William Q. Embate, Plutarch Romiel Degollacion|[ZKML Solar PV Positioning Optimizer Module](https://taikai.network/starkware/hackathons/starknet-infra-hackathon/projects/clpnv5gav00d6x401lol9jaf8/idea) | The ZKML-powered Solar PV Positioning Optimizer Module ensures efficient solar energy use through data-driven reporting and precise PV positioning in the pre-installation phase. | -| Zion | Onairos | Onairos is a groundbreaking platform that combines the power of AI, Data Privacy, and Blockchain to create digital personalities. These digital personalities represent individuals and help users interact with the online world while retaining control over their data | +| Zion | [Onairos](https://onairos.uk/) | Onairos is a groundbreaking platform that combines the power of AI, Data Privacy, and Blockchain to create digital personalities. These digital personalities represent individuals and help users interact with the online world while retaining control over their data | From 3a92c3f267f7231d2da8bc40d16edcdf76c39402 Mon Sep 17 00:00:00 2001 From: Raphael Doukhan Date: Thu, 21 Dec 2023 13:10:48 +0000 Subject: [PATCH 14/16] GITBOOK-42: Update doc --- .../assets/ORION_tutorial (1) (1).png | Bin 0 -> 4762104 bytes docs/.gitbook/assets/ORION_tutorial (1).png | Bin 4762104 -> 4772163 bytes docs/.gitbook/assets/accuracy.png | Bin 0 -> 56324 bytes docs/.gitbook/assets/forecasts.png | Bin 0 -> 74675 bytes docs/.gitbook/assets/tutorial#1.png | Bin 0 -> 1454816 bytes docs/.gitbook/assets/tutorial#2.png | Bin 0 -> 1410620 bytes docs/.gitbook/assets/tutorial#3.png | Bin 0 -> 1377296 bytes docs/.gitbook/assets/tutorial#5 (1).png | Bin 0 -> 1433171 bytes docs/.gitbook/assets/tutorial#5.png | Bin 0 -> 1368467 bytes docs/SUMMARY.md | 1 + docs/academy/tutorials/README.md | 5 + .../implement-new-operators-in-orion.md | 2 +- .../mnist-classification-with-orion.md | 4 +- ...r-forecasting-aaves-lifetime-repayments.md | 1097 +++++++++++++++++ ...fiable-linear-regression-model-in-orion.md | 2 +- ...erifiable-principal-components-analysis.md | 4 +- docs/hub/algorithms.md | 2 +- docs/hub/spaces.md | 2 +- 18 files changed, 1112 insertions(+), 7 deletions(-) create mode 100644 docs/.gitbook/assets/ORION_tutorial (1) (1).png create mode 100644 docs/.gitbook/assets/accuracy.png create mode 100644 docs/.gitbook/assets/forecasts.png create mode 100644 docs/.gitbook/assets/tutorial#1.png create mode 100644 docs/.gitbook/assets/tutorial#2.png create mode 100644 docs/.gitbook/assets/tutorial#3.png create mode 100644 docs/.gitbook/assets/tutorial#5 (1).png create mode 100644 docs/.gitbook/assets/tutorial#5.png create mode 100644 docs/academy/tutorials/provable-mlr-forecasting-aaves-lifetime-repayments.md diff --git a/docs/.gitbook/assets/ORION_tutorial (1) (1).png b/docs/.gitbook/assets/ORION_tutorial (1) (1).png new file 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