From 35c96c1e9ca1d253fd8443e6de17286844914f6b Mon Sep 17 00:00:00 2001 From: SigureMo Date: Sat, 25 Jan 2025 12:19:45 +0800 Subject: [PATCH 1/3] [CodeStyle][Typos][I-15] Fix typo `infered` (part1) --- paddle/phi/kernels/onednn/reshape_kernel.cc | 2 +- .../transforms/shape_optimization_pass.cc | 4 +- .../src/dialect/shape/utils/shape_analysis.cc | 5 +- python/paddle/base/variable_index.py | 2 +- .../auto_parallel/custom_op_spmd_rule_test.cc | 16 +- .../fused_rms_norm_spmd_rule_test.cc | 50 +- .../moe_combine_spmd_rule_test.cc | 4 +- .../moe_gate_dispatch_spmd_rule_test.cc | 4 +- test/cpp/auto_parallel/spmd_rule_test.cc | 690 +++++++++--------- .../test_reshape_mkldnn_op_deprecated.py | 32 +- test/legacy_test/test_reshape_op.py | 46 +- test/legacy_test/test_swiglu.py | 20 +- test/legacy_test/testsuite.py | 2 +- test/mkldnn/test_reshape_bf16_op.py | 6 +- test/xpu/test_reshape2_op_xpu.py | 30 +- 15 files changed, 458 insertions(+), 455 deletions(-) diff --git a/paddle/phi/kernels/onednn/reshape_kernel.cc b/paddle/phi/kernels/onednn/reshape_kernel.cc index b86bcc4031043..a9aac205f66c1 100644 --- a/paddle/phi/kernels/onednn/reshape_kernel.cc +++ b/paddle/phi/kernels/onednn/reshape_kernel.cc @@ -22,7 +22,7 @@ static DDim ValidateShape(const std::vector& shape, in_dims_vec.cend(), [](int64_t i) { return i > 0; }); // only one dimension can be set to -1, whose size will be automatically - // infered + // inferred const int64_t unk_dim_val = -1; const int64_t copy_dim_val = 0; diff --git a/paddle/pir/src/dialect/shape/transforms/shape_optimization_pass.cc b/paddle/pir/src/dialect/shape/transforms/shape_optimization_pass.cc index 0d4ec7676c058..f6b95381c11bf 100644 --- a/paddle/pir/src/dialect/shape/transforms/shape_optimization_pass.cc +++ b/paddle/pir/src/dialect/shape/transforms/shape_optimization_pass.cc @@ -32,8 +32,8 @@ COMMON_DECLARE_bool(pir_apply_shape_optimization_pass); constexpr int vlog_level = 3; -// TODO(zhangbopd): Some op results infered by InferSymbolicShape is NOT consist -// with the result infered by InferMeta and should be fixed. +// TODO(zhangbopd): Some op results inferred by InferSymbolicShape is NOT +// consist with the result inferred by InferMeta and should be fixed. namespace { bool NeedCheckInferSymbolicWithInferMeta(const std::string& op_name, size_t result_idx) { diff --git a/paddle/pir/src/dialect/shape/utils/shape_analysis.cc b/paddle/pir/src/dialect/shape/utils/shape_analysis.cc index 39a1c4f6694a5..8729e7043b90b 100644 --- a/paddle/pir/src/dialect/shape/utils/shape_analysis.cc +++ b/paddle/pir/src/dialect/shape/utils/shape_analysis.cc @@ -513,7 +513,7 @@ void ShapeConstraintIRAnalysis::InferShapeOrDataForValue(Value val) { } }; - const auto& VisitNotInferedInputOp = + const auto& VisitNotInferredInputOp = [&](Operation* op, const std::function& Visit) { for (auto& operand : GetRealOperandSource(op)) { if (operand.impl() && !context_.HasShapeOrDataForValue(operand)) { @@ -526,7 +526,8 @@ void ShapeConstraintIRAnalysis::InferShapeOrDataForValue(Value val) { } }; - ::common::BfsWalker build_subgraph_walker(VisitNotInferedInputOp); + ::common::BfsWalker build_subgraph_walker( + VisitNotInferredInputOp); build_subgraph_walker(val.defining_op(), [&](Operation* op) { subgraph_ops.insert(op); bool has_prev_op = false; diff --git a/python/paddle/base/variable_index.py b/python/paddle/base/variable_index.py index 9a809f75a2233..7ad2342f2cdd4 100644 --- a/python/paddle/base/variable_index.py +++ b/python/paddle/base/variable_index.py @@ -910,7 +910,7 @@ def _getitem_static(x, indices): def parse_bool_and_broadcast_indices(indices): # deal with multiple Tensors and translating bool tensor to int tensor. - # In static mode, bool-tensor cannot be broadcasted since its corresponding int tensor's shape cannot be infered. + # In static mode, bool-tensor cannot be broadcasted since its corresponding int tensor's shape cannot be inferred. for i, indice in enumerate(indices): if ( indice.dtype == paddle.bool diff --git a/test/cpp/auto_parallel/custom_op_spmd_rule_test.cc b/test/cpp/auto_parallel/custom_op_spmd_rule_test.cc index 203582d53d8ad..30b3d8778caf8 100644 --- a/test/cpp/auto_parallel/custom_op_spmd_rule_test.cc +++ b/test/cpp/auto_parallel/custom_op_spmd_rule_test.cc @@ -55,25 +55,25 @@ TEST(CustomOp, Ctor) { std::vector infer_inputs = {inputs}; std::vector attrs = {axis}; - auto infered_dist_attrs = forward_spmd_func(infer_inputs, attrs); + auto inferred_dist_attrs = forward_spmd_func(infer_inputs, attrs); // list of tensor => single tensor - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); EXPECT_TRUE( paddle::holds_alternative>( - infered_dist_attrs.first[0])); + inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( - infered_dist_attrs.second[0])); + inferred_dist_attrs.second[0])); auto& inputs_infer1 = PADDLE_GET_CONST(std::vector, - infered_dist_attrs.first[0]); + inferred_dist_attrs.first[0]); for (auto e : inputs_infer1) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_dist_attrs.second[0], {-1, 1, 0}); - check_partial_dims(infered_dist_attrs.second[0], {}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, 1, 0}); + check_partial_dims(inferred_dist_attrs.second[0], {}); } TEST(CustomOp, Register) { diff --git a/test/cpp/auto_parallel/fused_rms_norm_spmd_rule_test.cc b/test/cpp/auto_parallel/fused_rms_norm_spmd_rule_test.cc index a204d422b91a8..8ea898097f60e 100644 --- a/test/cpp/auto_parallel/fused_rms_norm_spmd_rule_test.cc +++ b/test/cpp/auto_parallel/fused_rms_norm_spmd_rule_test.cc @@ -44,16 +44,16 @@ TEST(FusedRmsNormSPMDRule, test_fused_rms_norm) { phi::distributed::DistMetaTensor x(common::make_ddim(x_shape), x_dist_attr); phi::distributed::DistMetaTensor scale(common::make_ddim(scale_shape), scale_dist_attr); - auto infered_dist_attrs = phi::distributed::RmsNormInferSpmd(x, scale, 0.5); + auto inferred_dist_attrs = phi::distributed::RmsNormInferSpmd(x, scale, 0.5); size_t input_size = 2; size_t output_size = 2; - EXPECT_EQ(infered_dist_attrs.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs.second.size(), output_size); - check_dim_mapping(infered_dist_attrs.first[0], {1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {1, -1}); + EXPECT_EQ(inferred_dist_attrs.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs.second.size(), output_size); + check_dim_mapping(inferred_dist_attrs.first[0], {1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {1, -1}); VLOG(4) << "test1 done."; @@ -63,11 +63,11 @@ TEST(FusedRmsNormSPMDRule, test_fused_rms_norm) { scale = phi::distributed::DistMetaTensor(common::make_ddim(scale_shape), scale_dist_attr); - infered_dist_attrs = phi::distributed::RmsNormInferSpmd(x, scale, 0.5); - check_dim_mapping(infered_dist_attrs.first[0], {1, 0, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, 0, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {1, 0}); + inferred_dist_attrs = phi::distributed::RmsNormInferSpmd(x, scale, 0.5); + check_dim_mapping(inferred_dist_attrs.first[0], {1, 0, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, 0, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {1, 0}); VLOG(4) << "test2 done."; TensorDistAttr out_dist_attr = TensorDistAttr(); @@ -84,26 +84,26 @@ TEST(FusedRmsNormSPMDRule, test_fused_rms_norm) { phi::distributed::DistMetaTensor invvar(common::make_ddim(variance_shape), invvar_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::RmsNormInferSpmdReverse(x, scale, out, invvar, 0.5); - check_dim_mapping(infered_dist_attrs.first[0], {0, 1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {0, 1}); + check_dim_mapping(inferred_dist_attrs.first[0], {0, 1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {0, 1}); VLOG(4) << "test3 done."; x_dist_attr.set_dims_mapping({0, 1, -1}); x = phi::distributed::DistMetaTensor(common::make_ddim(x_shape), x_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::RmsNormGradInferSpmd(x, scale, invvar, out, 0.5); - check_dim_mapping(infered_dist_attrs.first[0], {0, 1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.first[2], {0, 1}); - check_dim_mapping(infered_dist_attrs.first[3], {0, 1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {-1}); - check_partial_dims(infered_dist_attrs.second[1], {0, 1}); + check_dim_mapping(inferred_dist_attrs.first[0], {0, 1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.first[2], {0, 1}); + check_dim_mapping(inferred_dist_attrs.first[3], {0, 1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {-1}); + check_partial_dims(inferred_dist_attrs.second[1], {0, 1}); } } // namespace auto_parallel } // namespace distributed diff --git a/test/cpp/auto_parallel/moe_combine_spmd_rule_test.cc b/test/cpp/auto_parallel/moe_combine_spmd_rule_test.cc index 45672cc22c3fe..8d260c33bd34a 100644 --- a/test/cpp/auto_parallel/moe_combine_spmd_rule_test.cc +++ b/test/cpp/auto_parallel/moe_combine_spmd_rule_test.cc @@ -91,9 +91,9 @@ void test_moe_combine_spmd( << dist_attrs.size() << " != " << dims_mappings.size(); for (size_t j = 0; j < dist_attrs.size(); ++j) { - const ArgDistAttr& infered_attr = dist_attrs[j]; + const ArgDistAttr& inferred_attr = dist_attrs[j]; const std::vector& expected_dims_mapping = dims_mappings[j]; - check_dim_mapping(infered_attr, expected_dims_mapping); + check_dim_mapping(inferred_attr, expected_dims_mapping); } } } diff --git a/test/cpp/auto_parallel/moe_gate_dispatch_spmd_rule_test.cc b/test/cpp/auto_parallel/moe_gate_dispatch_spmd_rule_test.cc index af927532a7f41..dab3f9fa8f319 100644 --- a/test/cpp/auto_parallel/moe_gate_dispatch_spmd_rule_test.cc +++ b/test/cpp/auto_parallel/moe_gate_dispatch_spmd_rule_test.cc @@ -96,9 +96,9 @@ void test_moe_gate_dispatch_spmd( << dist_attrs.size() << " != " << dims_mappings.size(); for (size_t j = 0; j < dist_attrs.size(); ++j) { - const ArgDistAttr& infered_attr = dist_attrs[j]; + const ArgDistAttr& inferred_attr = dist_attrs[j]; const std::vector& expected_dims_mapping = dims_mappings[j]; - check_dim_mapping(infered_attr, expected_dims_mapping); + check_dim_mapping(inferred_attr, expected_dims_mapping); } } } diff --git a/test/cpp/auto_parallel/spmd_rule_test.cc b/test/cpp/auto_parallel/spmd_rule_test.cc index 3baf050d02f80..135b400866ee9 100644 --- a/test/cpp/auto_parallel/spmd_rule_test.cc +++ b/test/cpp/auto_parallel/spmd_rule_test.cc @@ -51,14 +51,14 @@ TEST(MatmulSPMDRule, Ctor) { // mk[1, -1],kn[-1, -1] --> mk[1, -1],kn[-1, -1] = nm[1, -1] partial[] phi::distributed::InferSpmdContext ctx( {x, y}, {/*trans_x=*/false, /*trans_x=*/false}); - auto infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - - EXPECT_EQ(infered_dist_attrs.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs.second.size(), output_size); - check_dim_mapping(infered_dist_attrs.first[0], {1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); + auto inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + + EXPECT_EQ(inferred_dist_attrs.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs.second.size(), output_size); + check_dim_mapping(inferred_dist_attrs.first[0], {1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); VLOG(4) << "test1 done." << std::endl << std::endl << std::endl; // mk[-1,-1],kn[-1,0] --> mk[-1,-1],kn[-1,0] = nm[-1,0] partial[] @@ -68,11 +68,11 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/false, /*trans_x=*/false}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, 0}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, 0}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, 0}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, 0}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); VLOG(4) << "test2 done." << std::endl << std::endl << std::endl; // mk[1, 0],kn[-1,-1] --> mk[1, 0],kn[0, -1] = nm[1, -1] partial[0]: done x_dist_attr.set_dims_mapping({1, 0}); @@ -81,12 +81,12 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/false, /*trans_x=*/false}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {1, 0}); - check_dim_mapping(infered_dist_attrs.first[1], {0, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - check_partial_dims(infered_dist_attrs.second[0], {0}); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.first[0], {1, 0}); + check_dim_mapping(inferred_dist_attrs.first[1], {0, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + check_partial_dims(inferred_dist_attrs.second[0], {0}); VLOG(4) << "test3 done." << std::endl << std::endl << std::endl; // mk[-1,-1],kn[1,0] --> mk[-1, 1],kn[1, 0] = nm[-1, 0] partial[1]: done @@ -96,12 +96,12 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/false, /*trans_x=*/false}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {-1, 1}); - check_dim_mapping(infered_dist_attrs.first[1], {1, 0}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, 0}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - check_partial_dims(infered_dist_attrs.second[0], {1}); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, 1}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, 0}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, 0}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + check_partial_dims(inferred_dist_attrs.second[0], {1}); VLOG(4) << "test4 done." << std::endl << std::endl << std::endl; // abcmk[1, 0, -1, -1],kn[-1, -1] --> abcmk[1, 0, -1, -1],kn[-1, -1] = @@ -113,11 +113,11 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/false, /*trans_x=*/false}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {0, 1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.first[0], {0, 1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); VLOG(4) << "test5 done." << std::endl << std::endl << std::endl; // abcmk[1, -1, -1, 0],kn[-1, -1] --> abcmk[1, -1, -1, 0],kn[0, -1] = abcmn[1, @@ -128,12 +128,12 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/false, /*trans_x=*/false}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {1, -1, -1, 0}); - check_dim_mapping(infered_dist_attrs.first[1], {0, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, -1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - check_partial_dims(infered_dist_attrs.second[0], {0}); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.first[0], {1, -1, -1, 0}); + check_dim_mapping(inferred_dist_attrs.first[1], {0, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + check_partial_dims(inferred_dist_attrs.second[0], {0}); VLOG(4) << "test6 done." << std::endl << std::endl << std::endl; // abcmk[1, -1, -1, 0], kn[-1, -1] --> abcmk[1, -1, -1, 0],kn[-1, -1] = @@ -144,12 +144,12 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/true, /*trans_x=*/false}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {1, -1, -1, 0}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, -1, 0, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); + check_dim_mapping(inferred_dist_attrs.first[0], {1, -1, -1, 0}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1, 0, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); VLOG(4) << "test7 done." << std::endl << std::endl << std::endl; @@ -161,14 +161,14 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/false, /*trans_x=*/true}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1, -1, 0}); - check_dim_mapping(infered_dist_attrs.first[1], {1, 0}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, -1, 1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - check_partial_dims(infered_dist_attrs.second[0], {0}); - clean_partial_dims(&infered_dist_attrs.second[0], {0}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1, -1, 0}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, 0}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, -1, 1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + check_partial_dims(inferred_dist_attrs.second[0], {0}); + clean_partial_dims(&inferred_dist_attrs.second[0], {0}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); VLOG(4) << "test8 done." << std::endl << std::endl << std::endl; // abcmk[-1, -1, 0, 1]+trans_x=true, kn[1, 0]+trans_y=true --> abcmk[-1, -1, @@ -179,17 +179,17 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/true, /*trans_x=*/true}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1, 0, 1}); - check_dim_mapping(infered_dist_attrs.first[1], + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1, 0, 1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, 0}); // conflict and should be changed to [-1, 0] - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, 1, -1}); - check_partial_dims(infered_dist_attrs.second[0], {0}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, 1, -1}); + check_partial_dims(inferred_dist_attrs.second[0], {0}); - clean_partial_status(&infered_dist_attrs.second[0]); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); - EXPECT_ANY_THROW(set_partial_status(&infered_dist_attrs.second[0], {1})); + clean_partial_status(&inferred_dist_attrs.second[0]); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); + EXPECT_ANY_THROW(set_partial_status(&inferred_dist_attrs.second[0], {1})); VLOG(4) << "test9 done." << std::endl << std::endl << std::endl; // abcmk[-1, -1, 1, 0], kn[1, 0] --> abcmk[-1, -1, -1, 0],kn[1, 0] = @@ -200,7 +200,7 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/true, /*trans_x=*/true}); - EXPECT_ANY_THROW(infered_dist_attrs = matmul_spmd_rule.InferForward(ctx)); + EXPECT_ANY_THROW(inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx)); // Error VLOG(4) << "test10 done." << std::endl << std::endl << std::endl; @@ -212,22 +212,22 @@ TEST(MatmulSPMDRule, Ctor) { y = phi::distributed::DistMetaTensor(common::make_ddim(y_shape), y_dist_attr); ctx = phi::distributed::InferSpmdContext( {x, y}, {/*trans_x=*/true, /*trans_x=*/true}); - infered_dist_attrs = matmul_spmd_rule.InferForward(ctx); - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, 1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - check_partial_dims(infered_dist_attrs.second[0], {0}); + inferred_dist_attrs = matmul_spmd_rule.InferForward(ctx); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, 1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + check_partial_dims(inferred_dist_attrs.second[0], {0}); // try to clean partial on a dim which is not partial - EXPECT_ANY_THROW(clean_partial_dims(&infered_dist_attrs.second[0], {1})); + EXPECT_ANY_THROW(clean_partial_dims(&inferred_dist_attrs.second[0], {1})); // try to clean partial on a dims which is sharded - EXPECT_ANY_THROW(set_partial_status(&infered_dist_attrs.second[0], {1})); + EXPECT_ANY_THROW(set_partial_status(&inferred_dist_attrs.second[0], {1})); // clean partial and then re-set again - clean_partial_dims(&infered_dist_attrs.second[0], {0}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), false); - set_partial_status(&infered_dist_attrs.second[0], {0}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - check_partial_dims(infered_dist_attrs.second[0], {0}); + clean_partial_dims(&inferred_dist_attrs.second[0], {0}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), false); + set_partial_status(&inferred_dist_attrs.second[0], {0}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + check_partial_dims(inferred_dist_attrs.second[0], {0}); VLOG(4) << "test11 done." << std::endl << std::endl << std::endl; } @@ -276,18 +276,18 @@ TEST(LayerNormSPMDRule, Ctor) { bias_dist_attr); phi::distributed::InferSpmdContext ctx({x, scale, bias}, {epsilon, begin_norm_axis}); - auto infered_dist_attrs = layer_norm_rule.InferForward(ctx); + auto inferred_dist_attrs = layer_norm_rule.InferForward(ctx); size_t input_size = 3; size_t output_size = 3; - EXPECT_EQ(infered_dist_attrs.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs.second.size(), output_size); - check_dim_mapping(infered_dist_attrs.first[0], {1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.first[2], {-1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {1, -1}); - check_dim_mapping(infered_dist_attrs.second[2], {1, -1}); + EXPECT_EQ(inferred_dist_attrs.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs.second.size(), output_size); + check_dim_mapping(inferred_dist_attrs.first[0], {1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.first[2], {-1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {1, -1}); + check_dim_mapping(inferred_dist_attrs.second[2], {1, -1}); VLOG(4) << "test1 done."; // ijk[1, 0, -1],k[0],k[0] --> ijk[1, -1, -1],z[1, 0],z[1, 0], @@ -303,14 +303,14 @@ TEST(LayerNormSPMDRule, Ctor) { bias_dist_attr); ctx = phi::distributed::InferSpmdContext({x, scale, bias}, {epsilon, begin_norm_axis}); - infered_dist_attrs = layer_norm_rule.InferForward(ctx); - - check_dim_mapping(infered_dist_attrs.first[0], {1, 0, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.first[2], {-1}); - check_dim_mapping(infered_dist_attrs.second[0], {1, 0, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {1, 0}); - check_dim_mapping(infered_dist_attrs.second[2], {1, 0}); + inferred_dist_attrs = layer_norm_rule.InferForward(ctx); + + check_dim_mapping(inferred_dist_attrs.first[0], {1, 0, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.first[2], {-1}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, 0, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {1, 0}); + check_dim_mapping(inferred_dist_attrs.second[2], {1, 0}); VLOG(4) << "test2 done."; // ijk[0, -1, -1],y[-1],y[1] --> ijk[0, -1, -1], i[0], i[0], y=jk, @@ -326,14 +326,14 @@ TEST(LayerNormSPMDRule, Ctor) { bias_dist_attr); ctx = phi::distributed::InferSpmdContext({x, scale, bias}, {epsilon, begin_norm_axis}); - infered_dist_attrs = layer_norm_rule.InferForward(ctx); - - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1}); - check_dim_mapping(infered_dist_attrs.first[2], {-1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {0}); - check_dim_mapping(infered_dist_attrs.second[2], {0}); + inferred_dist_attrs = layer_norm_rule.InferForward(ctx); + + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1}); + check_dim_mapping(inferred_dist_attrs.first[2], {-1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {0}); + check_dim_mapping(inferred_dist_attrs.second[2], {0}); VLOG(4) << "test3 done."; } @@ -379,19 +379,19 @@ TEST(MatmulSPMDRuleInferBackward, Ctor) { // -1] phi::distributed::InferSpmdContext ctx( {x, y, out}, {/*trans_x=*/false, /*trans_x=*/false}); - auto infered_dist_attrs = matmul_spmd_rule.InferBackward(ctx); + auto inferred_dist_attrs = matmul_spmd_rule.InferBackward(ctx); size_t input_size = 2; size_t output_size = 1; - EXPECT_EQ(infered_dist_attrs.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs.second.size(), output_size); - - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1, 1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, 1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.first[0]), false); - EXPECT_EQ(is_partial(infered_dist_attrs.first[1]), false); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); + EXPECT_EQ(inferred_dist_attrs.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs.second.size(), output_size); + + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1, 1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, 1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[0]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[1]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); VLOG(4) << "test1 done." << std::endl << std::endl << std::endl; } @@ -436,74 +436,74 @@ TEST(ReplicatedSPMDRule, Ctor) { // 2 inputs 2 outputs // call in vector arguments format - auto infered_dist_attrs_st = + auto inferred_dist_attrs_st = phi::distributed::ReplicatedInferSpmd({&x, &y}, {&out1, &out2}); // call in variadic arguments format - auto infered_dist_attrs_dy = + auto inferred_dist_attrs_dy = phi::distributed::VariadicReplicatedInferSpmd(x, y, &out1, &out2); size_t input_size = 2; size_t output_size = 2; - EXPECT_EQ(infered_dist_attrs_st.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_st.second.size(), output_size); - EXPECT_EQ(infered_dist_attrs_dy.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_dy.second.size(), output_size); - - check_dim_mapping(infered_dist_attrs_st.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_st.first[1], {-1, -1}); - check_dim_mapping(infered_dist_attrs_st.second[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_st.second[1], {-1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs_st.first[0]), false); - EXPECT_EQ(is_partial(infered_dist_attrs_st.first[1]), false); - EXPECT_EQ(is_partial(infered_dist_attrs_st.second[0]), false); - EXPECT_EQ(is_partial(infered_dist_attrs_st.second[1]), false); - EXPECT_EQ(infered_dist_attrs_st.first, infered_dist_attrs_dy.first); - EXPECT_EQ(infered_dist_attrs_st.second, infered_dist_attrs_dy.second); + EXPECT_EQ(inferred_dist_attrs_st.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_st.second.size(), output_size); + EXPECT_EQ(inferred_dist_attrs_dy.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_dy.second.size(), output_size); + + check_dim_mapping(inferred_dist_attrs_st.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_st.first[1], {-1, -1}); + check_dim_mapping(inferred_dist_attrs_st.second[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_st.second[1], {-1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.first[0]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.first[1]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.second[0]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.second[1]), false); + EXPECT_EQ(inferred_dist_attrs_st.first, inferred_dist_attrs_dy.first); + EXPECT_EQ(inferred_dist_attrs_st.second, inferred_dist_attrs_dy.second); VLOG(4) << "test1 done." << std::endl << std::endl << std::endl; // 3 inputs 1 outputs // call in vector arguments format - infered_dist_attrs_st = + inferred_dist_attrs_st = phi::distributed::ReplicatedInferSpmd({&x, &y, &out1}, {&out2}); // call in variadic arguments format - infered_dist_attrs_dy = + inferred_dist_attrs_dy = phi::distributed::VariadicReplicatedInferSpmd(x, y, out1, &out2); input_size = 3; output_size = 1; - EXPECT_EQ(infered_dist_attrs_st.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_st.second.size(), output_size); - EXPECT_EQ(infered_dist_attrs_dy.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_dy.second.size(), output_size); - check_dim_mapping(infered_dist_attrs_dy.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.first[1], {-1, -1}); - check_dim_mapping(infered_dist_attrs_dy.first[2], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[0], {-1, -1, -1}); - EXPECT_EQ(infered_dist_attrs_st.first, infered_dist_attrs_dy.first); - EXPECT_EQ(infered_dist_attrs_st.second, infered_dist_attrs_dy.second); + EXPECT_EQ(inferred_dist_attrs_st.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_st.second.size(), output_size); + EXPECT_EQ(inferred_dist_attrs_dy.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_dy.second.size(), output_size); + check_dim_mapping(inferred_dist_attrs_dy.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.first[1], {-1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.first[2], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[0], {-1, -1, -1}); + EXPECT_EQ(inferred_dist_attrs_st.first, inferred_dist_attrs_dy.first); + EXPECT_EQ(inferred_dist_attrs_st.second, inferred_dist_attrs_dy.second); VLOG(4) << "test2 done." << std::endl << std::endl << std::endl; // 1 inputs 3 outputs backward // call in vector arguments format - infered_dist_attrs_st = + inferred_dist_attrs_st = phi::distributed::ReplicatedInferSpmdReverse({&x}, {&y, &out1, &out2}); // call in variadic arguments format - infered_dist_attrs_dy = + inferred_dist_attrs_dy = phi::distributed::VariadicReplicatedInferSpmdReverse(x, &y, &out1, &out2); input_size = 1; output_size = 3; - EXPECT_EQ(infered_dist_attrs_st.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_st.second.size(), output_size); - EXPECT_EQ(infered_dist_attrs_dy.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_dy.second.size(), output_size); - - check_dim_mapping(infered_dist_attrs_dy.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[0], {-1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[1], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[2], {-1, -1, -1}); - EXPECT_EQ(infered_dist_attrs_st.first, infered_dist_attrs_dy.first); - EXPECT_EQ(infered_dist_attrs_st.second, infered_dist_attrs_dy.second); + EXPECT_EQ(inferred_dist_attrs_st.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_st.second.size(), output_size); + EXPECT_EQ(inferred_dist_attrs_dy.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_dy.second.size(), output_size); + + check_dim_mapping(inferred_dist_attrs_dy.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[0], {-1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[1], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[2], {-1, -1, -1}); + EXPECT_EQ(inferred_dist_attrs_st.first, inferred_dist_attrs_dy.first); + EXPECT_EQ(inferred_dist_attrs_st.second, inferred_dist_attrs_dy.second); VLOG(4) << "test3 done." << std::endl << std::endl << std::endl; } @@ -548,55 +548,55 @@ TEST(DefaultDataParallelSPMDRule, Ctor) { // 2 inputs 2 outputs, batch axis sharding is propagated while other axes are // replicated call in vector arguments format - auto infered_dist_attrs_st = + auto inferred_dist_attrs_st = phi::distributed::DefaultDataParallelInferSpmd({&x, &y}, {&out1, &out2}); // call in variadic arguments format - auto infered_dist_attrs_dy = + auto inferred_dist_attrs_dy = phi::distributed::VariadicDefaultDataParallelInferSpmd( x, y, &out1, &out2); size_t input_size = 2; size_t output_size = 2; - EXPECT_EQ(infered_dist_attrs_st.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_st.second.size(), output_size); - EXPECT_EQ(infered_dist_attrs_dy.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_dy.second.size(), output_size); - check_dim_mapping(infered_dist_attrs_st.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_st.first[1], {0, -1}); - check_dim_mapping(infered_dist_attrs_st.second[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_st.second[1], {0, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs_st.first[0]), false); - EXPECT_EQ(is_partial(infered_dist_attrs_st.first[1]), false); - EXPECT_EQ(is_partial(infered_dist_attrs_st.second[0]), false); - EXPECT_EQ(is_partial(infered_dist_attrs_st.second[1]), false); - - EXPECT_EQ(infered_dist_attrs_st.first, infered_dist_attrs_dy.first); - EXPECT_EQ(infered_dist_attrs_st.second, infered_dist_attrs_dy.second); + EXPECT_EQ(inferred_dist_attrs_st.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_st.second.size(), output_size); + EXPECT_EQ(inferred_dist_attrs_dy.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_dy.second.size(), output_size); + check_dim_mapping(inferred_dist_attrs_st.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_st.first[1], {0, -1}); + check_dim_mapping(inferred_dist_attrs_st.second[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_st.second[1], {0, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.first[0]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.first[1]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.second[0]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs_st.second[1]), false); + + EXPECT_EQ(inferred_dist_attrs_st.first, inferred_dist_attrs_dy.first); + EXPECT_EQ(inferred_dist_attrs_st.second, inferred_dist_attrs_dy.second); VLOG(4) << "test1 done." << std::endl << std::endl << std::endl; // 1 inputs 3 outputs, batch axis is un-sharded // call in vector arguments format - infered_dist_attrs_st = + inferred_dist_attrs_st = phi::distributed::DefaultDataParallelInferSpmd({&x}, {&y, &out1, &out2}); // call in variadic arguments format - infered_dist_attrs_dy = + inferred_dist_attrs_dy = phi::distributed::VariadicDefaultDataParallelInferSpmd( x, &y, &out1, &out2); input_size = 1; output_size = 3; - EXPECT_EQ(infered_dist_attrs_st.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_st.second.size(), output_size); - EXPECT_EQ(infered_dist_attrs_dy.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_dy.second.size(), output_size); - - check_dim_mapping(infered_dist_attrs_dy.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[0], {-1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[1], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[2], {-1, -1, -1}); - - EXPECT_EQ(infered_dist_attrs_st.first, infered_dist_attrs_dy.first); - EXPECT_EQ(infered_dist_attrs_st.second, infered_dist_attrs_dy.second); + EXPECT_EQ(inferred_dist_attrs_st.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_st.second.size(), output_size); + EXPECT_EQ(inferred_dist_attrs_dy.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_dy.second.size(), output_size); + + check_dim_mapping(inferred_dist_attrs_dy.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[0], {-1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[1], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[2], {-1, -1, -1}); + + EXPECT_EQ(inferred_dist_attrs_st.first, inferred_dist_attrs_dy.first); + EXPECT_EQ(inferred_dist_attrs_st.second, inferred_dist_attrs_dy.second); VLOG(4) << "test2 done." << std::endl << std::endl << std::endl; // conflict on batch axis @@ -608,11 +608,11 @@ TEST(DefaultDataParallelSPMDRule, Ctor) { out1 = phi::distributed::DistMetaTensor(common::make_ddim(out1_shape), out1_dist_attr); - EXPECT_ANY_THROW(infered_dist_attrs_st = + EXPECT_ANY_THROW(inferred_dist_attrs_st = phi::distributed::DefaultDataParallelInferSpmd( {&x, &y, &out1}, {&out2})); // call in variadic arguments format - EXPECT_ANY_THROW(infered_dist_attrs_dy = + EXPECT_ANY_THROW(inferred_dist_attrs_dy = phi::distributed::VariadicDefaultDataParallelInferSpmd( x, y, out1, &out2)); @@ -627,25 +627,26 @@ TEST(DefaultDataParallelSPMDRule, Ctor) { out2 = phi::distributed::DistMetaTensor(common::make_ddim(out2_shape), out2_dist_attr); - infered_dist_attrs_st = phi::distributed::DefaultDataParallelInferSpmdReverse( - {&x, &y}, {&out1, &out2}); + inferred_dist_attrs_st = + phi::distributed::DefaultDataParallelInferSpmdReverse({&x, &y}, + {&out1, &out2}); // call in variadic arguments format - infered_dist_attrs_dy = + inferred_dist_attrs_dy = phi::distributed::VariadicDefaultDataParallelInferSpmdReverse( x, y, &out1, &out2); input_size = 2; output_size = 2; - EXPECT_EQ(infered_dist_attrs_st.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_st.second.size(), output_size); - EXPECT_EQ(infered_dist_attrs_dy.first.size(), input_size); - EXPECT_EQ(infered_dist_attrs_dy.second.size(), output_size); - check_dim_mapping(infered_dist_attrs_dy.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.first[1], {0, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs_dy.second[1], {0, -1, -1}); - EXPECT_EQ(infered_dist_attrs_st.first, infered_dist_attrs_dy.first); - EXPECT_EQ(infered_dist_attrs_st.second, infered_dist_attrs_dy.second); + EXPECT_EQ(inferred_dist_attrs_st.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_st.second.size(), output_size); + EXPECT_EQ(inferred_dist_attrs_dy.first.size(), input_size); + EXPECT_EQ(inferred_dist_attrs_dy.second.size(), output_size); + check_dim_mapping(inferred_dist_attrs_dy.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.first[1], {0, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs_dy.second[1], {0, -1, -1}); + EXPECT_EQ(inferred_dist_attrs_st.first, inferred_dist_attrs_dy.first); + EXPECT_EQ(inferred_dist_attrs_st.second, inferred_dist_attrs_dy.second); VLOG(4) << "test4 done." << std::endl << std::endl << std::endl; } TEST(ConcatRule, Ctor) { @@ -676,22 +677,22 @@ TEST(ConcatRule, Ctor) { // test 1, inputs are aligned according to cost, and partial status is cleared auto inputs = build_inputs(); - auto infered_dist_attrs = phi::distributed::ConcatInferSpmd(inputs, 0); + auto inferred_dist_attrs = phi::distributed::ConcatInferSpmd(inputs, 0); // list of tensor => single tensor - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); EXPECT_TRUE( paddle::holds_alternative>( - infered_dist_attrs.first[0])); + inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( - infered_dist_attrs.second[0])); - auto& inputs_infer1 = paddle::get<1>(infered_dist_attrs.first[0]); + inferred_dist_attrs.second[0])); + auto& inputs_infer1 = paddle::get<1>(inferred_dist_attrs.first[0]); for (auto e : inputs_infer1) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_dist_attrs.second[0], {-1, 1, 0}); - check_partial_dims(infered_dist_attrs.second[0], {}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, 1, 0}); + check_partial_dims(inferred_dist_attrs.second[0], {}); auto build_output = [&](const TensorDistAttr& t_dist_attr, const std::vector& shape) { @@ -700,55 +701,55 @@ TEST(ConcatRule, Ctor) { }; auto& output_dist_attr = - PADDLE_GET_CONST(TensorDistAttr, infered_dist_attrs.second[0]); + PADDLE_GET_CONST(TensorDistAttr, inferred_dist_attrs.second[0]); auto output = build_output(output_dist_attr, {22, 16, 16}); // test reverse - auto infered_reverse_attrs = + auto inferred_reverse_attrs = phi::distributed::ConcatInferSpmdReverse(inputs, output, 0); auto& inputs_infer1_reverse = PADDLE_GET_CONST( - std::vector, infered_reverse_attrs.first[0]); + std::vector, inferred_reverse_attrs.first[0]); for (auto e : inputs_infer1_reverse) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_reverse_attrs.second[0], + check_dim_mapping(inferred_reverse_attrs.second[0], output_dist_attr.dims_mapping()); // test grad - auto infered_grad_attrs = + auto inferred_grad_attrs = phi::distributed::ConcatGradInferSpmdDynamic(inputs, output, 0); auto& inputs_infer1_grad = PADDLE_GET_CONST(std::vector, - infered_grad_attrs.first[0]); + inferred_grad_attrs.first[0]); for (auto e : inputs_infer1_grad) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_grad_attrs.first[1], + check_dim_mapping(inferred_grad_attrs.first[1], output_dist_attr.dims_mapping()); - auto& infered_grad = PADDLE_GET_CONST(std::vector, - infered_grad_attrs.second[0]); - for (auto e : infered_grad) { + auto& inferred_grad = PADDLE_GET_CONST(std::vector, + inferred_grad_attrs.second[0]); + for (auto e : inferred_grad) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } // test 2，force replicate along concat axis inputs = build_inputs(); - infered_dist_attrs = phi::distributed::ConcatInferSpmd(inputs, 1); + inferred_dist_attrs = phi::distributed::ConcatInferSpmd(inputs, 1); // list of tensor => single tensor - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); EXPECT_TRUE( paddle::holds_alternative>( - infered_dist_attrs.first[0])); + inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( - infered_dist_attrs.second[0])); - auto& inputs_infer2 = paddle::get<1>(infered_dist_attrs.first[0]); + inferred_dist_attrs.second[0])); + auto& inputs_infer2 = paddle::get<1>(inferred_dist_attrs.first[0]); for (auto e : inputs_infer2) { check_dim_mapping(e, {1, -1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_dist_attrs.second[0], {1, -1, 0}); - check_partial_dims(infered_dist_attrs.second[0], {}); + check_dim_mapping(inferred_dist_attrs.second[0], {1, -1, 0}); + check_partial_dims(inferred_dist_attrs.second[0], {}); } TEST(StackRule, Ctor) { @@ -794,68 +795,68 @@ TEST(StackRule, Ctor) { // test 1, inputs are aligned according to cost. auto inputs = build_inputs(); - auto infered_dist_attrs = phi::distributed::StackInferSpmd(inputs, 0); + auto inferred_dist_attrs = phi::distributed::StackInferSpmd(inputs, 0); // list of tensor => single tensor - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); EXPECT_TRUE( paddle::holds_alternative>( - infered_dist_attrs.first[0])); + inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( - infered_dist_attrs.second[0])); + inferred_dist_attrs.second[0])); auto& inputs_infer1 = PADDLE_GET_CONST(std::vector, - infered_dist_attrs.first[0]); + inferred_dist_attrs.first[0]); for (auto e : inputs_infer1) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, 1, 0}); - check_partial_dims(infered_dist_attrs.second[0], {}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, 1, 0}); + check_partial_dims(inferred_dist_attrs.second[0], {}); auto output_dist_attr = - PADDLE_GET_CONST(TensorDistAttr, infered_dist_attrs.second[0]); + PADDLE_GET_CONST(TensorDistAttr, inferred_dist_attrs.second[0]); auto output = build_output(output_dist_attr, 0); // test reverse - auto infered_reverse_attrs = + auto inferred_reverse_attrs = phi::distributed::StackInferSpmdReverse(inputs, output, 0); auto& inputs_infer1_reverse = PADDLE_GET_CONST( - std::vector, infered_reverse_attrs.first[0]); + std::vector, inferred_reverse_attrs.first[0]); for (auto e : inputs_infer1_reverse) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_reverse_attrs.second[0], + check_dim_mapping(inferred_reverse_attrs.second[0], output_dist_attr.dims_mapping()); // test grad - auto infered_grad_attrs = phi::distributed::StackGradInferSpmd(output, 0); - check_dim_mapping(infered_grad_attrs.first[0], + auto inferred_grad_attrs = phi::distributed::StackGradInferSpmd(output, 0); + check_dim_mapping(inferred_grad_attrs.first[0], output_dist_attr.dims_mapping()); - auto& infered_grad = PADDLE_GET_CONST(std::vector, - infered_grad_attrs.second[0]); - for (auto e : infered_grad) { + auto& inferred_grad = PADDLE_GET_CONST(std::vector, + inferred_grad_attrs.second[0]); + for (auto e : inferred_grad) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } // test 2，force replicate along concat axis inputs = build_inputs(); - infered_dist_attrs = phi::distributed::StackInferSpmd(inputs, 1); + inferred_dist_attrs = phi::distributed::StackInferSpmd(inputs, 1); // list of tensor => single tensor - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); EXPECT_TRUE( paddle::holds_alternative>( - infered_dist_attrs.first[0])); + inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( - infered_dist_attrs.second[0])); + inferred_dist_attrs.second[0])); auto& inputs_infer2 = PADDLE_GET_CONST(std::vector, - infered_dist_attrs.first[0]); + inferred_dist_attrs.first[0]); for (auto e : inputs_infer2) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); } - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, 1, 0}); - check_partial_dims(infered_dist_attrs.second[0], {}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, 1, 0}); + check_partial_dims(inferred_dist_attrs.second[0], {}); } TEST(WhereRule, Ctor) { @@ -882,21 +883,21 @@ TEST(WhereRule, Ctor) { }; auto inputs = build_inputs(); - auto infered_dist_attrs = phi::distributed::WhereGradInferSpmd( + auto inferred_dist_attrs = phi::distributed::WhereGradInferSpmd( inputs[0], inputs[1], inputs[2], inputs[0]); - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(4)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(2)); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(4)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(2)); - check_dim_mapping(infered_dist_attrs.first[0], {-1, 0, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {0, -1}); - check_dim_mapping(infered_dist_attrs.first[2], {-1}); - check_dim_mapping(infered_dist_attrs.first[3], {-1, 0, -1}); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, 0, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {0, -1}); + check_dim_mapping(inferred_dist_attrs.first[2], {-1}); + check_dim_mapping(inferred_dist_attrs.first[3], {-1, 0, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, -1}); - check_partial_dims(infered_dist_attrs.second[0], {}); - check_dim_mapping(infered_dist_attrs.second[1], {-1}); - check_partial_dims(infered_dist_attrs.second[1], {0}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, -1}); + check_partial_dims(inferred_dist_attrs.second[0], {}); + check_dim_mapping(inferred_dist_attrs.second[1], {-1}); + check_partial_dims(inferred_dist_attrs.second[1], {0}); } TEST(ReduceMaxRule, Ctor) { @@ -967,12 +968,12 @@ TEST(Numel, Ctor) { t_dist_attr.set_dynamic_dims({false, false, false}); auto input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - auto infered_dist_attrs = phi::distributed::NumelInferSpmd(input); - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); - check_dim_mapping(infered_dist_attrs.first[0], dims_mapping); - check_dim_mapping(infered_dist_attrs.second[0], {}); - check_partial_dims(infered_dist_attrs.second[0], {0}); + auto inferred_dist_attrs = phi::distributed::NumelInferSpmd(input); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); + check_dim_mapping(inferred_dist_attrs.first[0], dims_mapping); + check_dim_mapping(inferred_dist_attrs.second[0], {}); + check_partial_dims(inferred_dist_attrs.second[0], {0}); } TEST(Triu, Ctor) { @@ -990,12 +991,12 @@ TEST(Triu, Ctor) { t_dist_attr.set_dynamic_dims({false, false, false}); auto input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - auto infered_dist_attrs = phi::distributed::TriuGradInferSpmd(input, 0); - EXPECT_EQ(infered_dist_attrs.first.size(), static_cast(1)); - EXPECT_EQ(infered_dist_attrs.second.size(), static_cast(1)); - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, -1, -1}); - check_partial_dims(infered_dist_attrs.second[0], {}); + auto inferred_dist_attrs = phi::distributed::TriuGradInferSpmd(input, 0); + EXPECT_EQ(inferred_dist_attrs.first.size(), static_cast(1)); + EXPECT_EQ(inferred_dist_attrs.second.size(), static_cast(1)); + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, -1, -1}); + check_partial_dims(inferred_dist_attrs.second[0], {}); } TEST(LayerNorm, Ctor) { @@ -1349,33 +1350,34 @@ TEST(ElementwiseUnaryLike, Ctor) { // cast auto input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - auto infered_dist_attrs = + auto inferred_dist_attrs = phi::distributed::CastInferSpmd(input, phi::DataType::FLOAT32); - check_element_unary_like(infered_dist_attrs); + check_element_unary_like(inferred_dist_attrs); // full like input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::FullLikeInferSpmd(input, 1.0, phi::DataType::FLOAT32); - check_element_unary_like(infered_dist_attrs); + check_element_unary_like(inferred_dist_attrs); // pow input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - infered_dist_attrs = phi::distributed::PowInferSpmd(input, 2); - check_element_unary_like(infered_dist_attrs); + inferred_dist_attrs = phi::distributed::PowInferSpmd(input, 2); + check_element_unary_like(inferred_dist_attrs); // pow backward input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - infered_dist_attrs = phi::distributed::PowGradInferSpmd(input, input, 2); + inferred_dist_attrs = phi::distributed::PowGradInferSpmd(input, input, 2); // scale input = phi::distributed::DistMetaTensor(common::make_ddim(shape), t_dist_attr); - infered_dist_attrs = phi::distributed::ScaleInferSpmd(input, 1.0, 1.0, false); - check_element_unary_like(infered_dist_attrs); + inferred_dist_attrs = + phi::distributed::ScaleInferSpmd(input, 1.0, 1.0, false); + check_element_unary_like(inferred_dist_attrs); } TEST(EmbeddingGradInferSpmd, Ctor) { @@ -2006,11 +2008,11 @@ TEST(Conv2dSPMDRuleInferForward, Ctor) { input_dist_attr); filter = phi::distributed::DistMetaTensor(common::make_ddim(filter_shape), filter_dist_attr); - auto infered_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); + auto inferred_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, -1, -1, -1}); // test 2 input_dist_attr.set_dims_mapping(std::vector({-1, -1, -1, -1})); @@ -2020,11 +2022,11 @@ TEST(Conv2dSPMDRuleInferForward, Ctor) { input_dist_attr); filter = phi::distributed::DistMetaTensor(common::make_ddim(filter_shape), filter_dist_attr); - infered_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); + inferred_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, 0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, 0, -1, -1}); // test 3 input_dist_attr.set_dims_mapping(std::vector({0, -1, -1, -1})); @@ -2034,11 +2036,11 @@ TEST(Conv2dSPMDRuleInferForward, Ctor) { input_dist_attr); filter = phi::distributed::DistMetaTensor(common::make_ddim(filter_shape), filter_dist_attr); - infered_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); + inferred_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 1, -1, -1}); // test 4 input_dist_attr.set_dims_mapping(std::vector({-1, 0, -1, -1})); @@ -2049,12 +2051,12 @@ TEST(Conv2dSPMDRuleInferForward, Ctor) { filter = phi::distributed::DistMetaTensor(common::make_ddim(filter_shape), filter_dist_attr); - infered_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); + inferred_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); - check_dim_mapping(infered_dist_attrs.first[0], {-1, 0, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, 0, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, 0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, 0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); // test 5 input_dist_attr.set_dims_mapping(std::vector({0, 2, -1, -1})); @@ -2065,12 +2067,12 @@ TEST(Conv2dSPMDRuleInferForward, Ctor) { filter = phi::distributed::DistMetaTensor(common::make_ddim(filter_shape), filter_dist_attr); - infered_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); + inferred_dist_attrs = phi::distributed::Conv2dInferSpmd(input, filter); - check_dim_mapping(infered_dist_attrs.first[0], {0, 2, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {1, 2, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); + check_dim_mapping(inferred_dist_attrs.first[0], {0, 2, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, 2, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); } TEST(Conv2dSPMDRuleInferBackward, Ctor) { @@ -2109,12 +2111,12 @@ TEST(Conv2dSPMDRuleInferBackward, Ctor) { phi::distributed::DistMetaTensor output(common::make_ddim(output_shape), output_dist_attr); - auto infered_dist_attrs = + auto inferred_dist_attrs = phi::distributed::Conv2dInferSpmdReverse(input, filter, output); - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 1, -1, -1}); } TEST(Conv2dGradSPMDRule, Ctor) { @@ -2155,16 +2157,16 @@ TEST(Conv2dGradSPMDRule, Ctor) { common::make_ddim(output_grad_shape), output_grad_dist_attr); // test 1 - auto infered_dist_attrs = + auto inferred_dist_attrs = phi::distributed::Conv2dGradInferSpmd(input, filter, output_grad); - EXPECT_EQ(infered_dist_attrs.first.size(), (size_t)3); - EXPECT_EQ(infered_dist_attrs.second.size(), (size_t)2); - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[2], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {-1, -1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.first[2]), false); + EXPECT_EQ(inferred_dist_attrs.first.size(), (size_t)3); + EXPECT_EQ(inferred_dist_attrs.second.size(), (size_t)2); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[2], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {-1, -1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[2]), false); VLOG(4) << "test 1 done"; // test 2 @@ -2178,16 +2180,16 @@ TEST(Conv2dGradSPMDRule, Ctor) { filter_dist_attr); output_grad = phi::distributed::DistMetaTensor( common::make_ddim(output_grad_shape), output_grad_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::Conv2dGradInferSpmd(input, filter, output_grad); - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[2], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {-1, -1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.first[2]), false); - EXPECT_EQ(is_partial(infered_dist_attrs.second[1]), true); + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[2], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {-1, -1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[2]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[1]), true); // test 3 input_dist_attr.set_dims_mapping(std::vector({-1, -1, -1, -1})); @@ -2200,16 +2202,16 @@ TEST(Conv2dGradSPMDRule, Ctor) { filter_dist_attr); output_grad = phi::distributed::DistMetaTensor( common::make_ddim(output_grad_shape), output_grad_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::Conv2dGradInferSpmd(input, filter, output_grad); - check_dim_mapping(infered_dist_attrs.first[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[2], {-1, 0, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {-1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {0, -1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.first[2]), false); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); + check_dim_mapping(inferred_dist_attrs.first[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[2], {-1, 0, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {-1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {0, -1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[2]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); // test 4 input_dist_attr.set_dims_mapping(std::vector({0, -1, -1, -1})); @@ -2222,17 +2224,17 @@ TEST(Conv2dGradSPMDRule, Ctor) { filter_dist_attr); output_grad = phi::distributed::DistMetaTensor( common::make_ddim(output_grad_shape), output_grad_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::Conv2dGradInferSpmd(input, filter, output_grad); - check_dim_mapping(infered_dist_attrs.first[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {1, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[2], {0, 1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, -1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {1, -1, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.first[2]), false); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - EXPECT_EQ(is_partial(infered_dist_attrs.second[1]), true); + check_dim_mapping(inferred_dist_attrs.first[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[2], {0, 1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, -1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {1, -1, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[2]), false); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[1]), true); // test 5 input_dist_attr.set_dims_mapping(std::vector({0, 2, -1, -1})); @@ -2247,17 +2249,17 @@ TEST(Conv2dGradSPMDRule, Ctor) { output_grad = phi::distributed::DistMetaTensor( common::make_ddim(output_grad_shape), output_grad_dist_attr); - infered_dist_attrs = + inferred_dist_attrs = phi::distributed::Conv2dGradInferSpmd(input, filter, output_grad); - check_dim_mapping(infered_dist_attrs.first[0], {0, 2, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[1], {1, 2, -1, -1}); - check_dim_mapping(infered_dist_attrs.first[2], {0, 1, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[0], {0, 2, -1, -1}); - check_dim_mapping(infered_dist_attrs.second[1], {1, 2, -1, -1}); - EXPECT_EQ(is_partial(infered_dist_attrs.first[2]), true); - EXPECT_EQ(is_partial(infered_dist_attrs.second[0]), true); - EXPECT_EQ(is_partial(infered_dist_attrs.second[1]), true); + check_dim_mapping(inferred_dist_attrs.first[0], {0, 2, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[1], {1, 2, -1, -1}); + check_dim_mapping(inferred_dist_attrs.first[2], {0, 1, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[0], {0, 2, -1, -1}); + check_dim_mapping(inferred_dist_attrs.second[1], {1, 2, -1, -1}); + EXPECT_EQ(is_partial(inferred_dist_attrs.first[2]), true); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[0]), true); + EXPECT_EQ(is_partial(inferred_dist_attrs.second[1]), true); } TEST(Dropout, Ctor) { diff --git a/test/deprecated/mkldnn/test_reshape_mkldnn_op_deprecated.py b/test/deprecated/mkldnn/test_reshape_mkldnn_op_deprecated.py index a3b4ce7bc4010..be2c1c948a19c 100644 --- a/test/deprecated/mkldnn/test_reshape_mkldnn_op_deprecated.py +++ b/test/deprecated/mkldnn/test_reshape_mkldnn_op_deprecated.py @@ -32,7 +32,7 @@ def setUp(self): self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")} self.attrs = {"shape": self.new_shape} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } self.x = self.inputs["X"] @@ -43,7 +43,7 @@ def setUp(self): def init_data(self): self.ori_shape = (2, 60) self.new_shape = (12, 10) - self.infered_shape = (12, 10) + self.inferred_shape = (12, 10) def init_dtype(self): self.dtype = np.float32 @@ -69,35 +69,35 @@ class TestReshape2OneDNNOpZeroDim(TestReshape2OneDNNOp): def init_data(self): self.ori_shape = () self.new_shape = (1,) - self.infered_shape = (1,) + self.inferred_shape = (1,) class TestReshape2OneDNNOpZeroDim2(TestReshape2OneDNNOpZeroDim): def init_data(self): self.ori_shape = (1,) self.new_shape = () - self.infered_shape = () + self.inferred_shape = () class TestReshape2OneDNNOpDimInfer1(TestReshape2OneDNNOp): def init_data(self): self.ori_shape = (5, 25) self.new_shape = (5, -1, 5) - self.infered_shape = (5, -1, 5) + self.inferred_shape = (5, -1, 5) class TestReshape2OneDNNOpDimInfer2(TestReshape2OneDNNOp): def init_data(self): self.ori_shape = (6, 20) self.new_shape = (0, -1, 20) - self.infered_shape = (2, 3, 20) + self.inferred_shape = (2, 3, 20) def set_additional_inputs(self): - self.inputs["Shape"] = np.array(self.infered_shape, dtype="int32") + self.inputs["Shape"] = np.array(self.inferred_shape, dtype="int32") def set_outputs(self): self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } @@ -108,14 +108,14 @@ def set_additional_inputs(self): def set_outputs(self): self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } def init_data(self): self.ori_shape = (4, 25) self.new_shape = (10, 10) - self.infered_shape = (10, 10) + self.inferred_shape = (10, 10) class TestReshape2OneDNNOpDimInfer1_attr_OnlyShape( @@ -124,7 +124,7 @@ class TestReshape2OneDNNOpDimInfer1_attr_OnlyShape( def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 10) - self.infered_shape = (5, -1, 10) + self.inferred_shape = (5, -1, 10) self.shape = (5, -1, -1) @@ -141,7 +141,7 @@ def set_additional_inputs(self): def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 10) - self.infered_shape = (5, -1, 10) + self.inferred_shape = (5, -1, 10) self.shape = (5, -1, -1) @@ -165,7 +165,7 @@ def setUp(self): self.op_type = "reshape" def set_outputs(self): - self.outputs = {"Out": self.inputs["X"].reshape(self.infered_shape)} + self.outputs = {"Out": self.inputs["X"].reshape(self.inferred_shape)} def test_check_output(self): self.check_output(check_dygraph=False) @@ -175,7 +175,7 @@ class TestReshapeOneDNNOpDimInfer1(TestReshapeOneDNNOp): def init_data(self): self.ori_shape = (5, 25) self.new_shape = (5, -1, 5) - self.infered_shape = (5, -1, 5) + self.inferred_shape = (5, -1, 5) class TestReshapeOneDNNOp_attr_OnlyShape(TestReshape2OneDNNOp_attr_OnlyShape): @@ -184,7 +184,7 @@ def setUp(self): self.op_type = "reshape" def set_outputs(self): - self.outputs = {"Out": self.inputs["X"].reshape(self.infered_shape)} + self.outputs = {"Out": self.inputs["X"].reshape(self.inferred_shape)} def test_check_output(self): self.check_output(check_dygraph=False) @@ -196,7 +196,7 @@ class TestReshapeOneDNNOpDimInfer1_attr_OnlyShape( def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 10) - self.infered_shape = (5, -1, 10) + self.inferred_shape = (5, -1, 10) self.shape = (5, -1, -1) diff --git a/test/legacy_test/test_reshape_op.py b/test/legacy_test/test_reshape_op.py index 981ec2aad6788..25ce318b3acf8 100755 --- a/test/legacy_test/test_reshape_op.py +++ b/test/legacy_test/test_reshape_op.py @@ -34,14 +34,14 @@ def setUp(self): self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")} self.attrs = {"shape": self.new_shape} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } def init_data(self): self.ori_shape = (2, 60) self.new_shape = (12, 10) - self.infered_shape = (12, 10) + self.inferred_shape = (12, 10) def test_check_output(self): self.check_output(no_check_set=['XShape'], check_pir=True) @@ -68,28 +68,28 @@ def setUp(self): self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")} self.attrs = {"shape": self.new_shape} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } def init_data(self): self.ori_shape = () self.new_shape = (1,) - self.infered_shape = (1,) + self.inferred_shape = (1,) class TestReshapeOp_ZeroDim2(TestReshapeOp_ZeroDim1): def init_data(self): self.ori_shape = () self.new_shape = (-1,) - self.infered_shape = (1,) + self.inferred_shape = (1,) class TestReshapeOp_ZeroDim3(OpTest): def init_data(self): self.ori_shape = (1,) self.new_shape = () - self.infered_shape = () + self.inferred_shape = () @unittest.skipIf( @@ -107,7 +107,7 @@ def setUp(self): self.python_out_sig = ['Out'] self.dtype = np.uint16 x = np.random.random(self.ori_shape).astype("float32") - out = x.reshape(self.infered_shape) + out = x.reshape(self.inferred_shape) self.inputs = {"X": convert_float_to_uint16(x)} self.attrs = {"shape": self.new_shape} self.outputs = { @@ -120,7 +120,7 @@ def setUp(self): def init_data(self): self.ori_shape = (2, 60) self.new_shape = (12, 10) - self.infered_shape = (12, 10) + self.inferred_shape = (12, 10) def test_check_output(self): self.check_output(no_check_set=['XShape'], check_pir=True) @@ -147,14 +147,14 @@ def setUp(self): self.inputs = {"X": np.random.random(self.ori_shape).astype(self.dtype)} self.attrs = {"shape": self.new_shape} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype(self.dtype), } def init_data(self): self.ori_shape = (2, 60) self.new_shape = (12, 10) - self.infered_shape = (12, 10) + self.inferred_shape = (12, 10) def test_check_output(self): self.check_output(no_check_set=['XShape'], check_pir=True) @@ -173,14 +173,14 @@ class TestReshapeOpDimInfer1(TestReshapeOp): def init_data(self): self.ori_shape = (5, 25) self.new_shape = (5, -1, 5) - self.infered_shape = (5, -1, 5) + self.inferred_shape = (5, -1, 5) class TestReshapeOpDimInfer2(TestReshapeOp): def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) # situation 2: have shape(list, no tensor), have actual shape(Tensor) @@ -245,14 +245,14 @@ def setUp(self): } self.attrs = {'shape': self.shape} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } def init_data(self): self.ori_shape = (4, 25) self.new_shape = (10, 10) - self.infered_shape = (10, 10) + self.inferred_shape = (10, 10) self.shape = (-1, -1) def test_check_output(self): @@ -274,7 +274,7 @@ class TestReshapeOpDimInfer1_attr_ShapeTensor(TestReshapeOp_attr_ShapeTensor): def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 20) - self.infered_shape = (5, -1, 20) + self.inferred_shape = (5, -1, 20) self.shape = (5, -1, -1) @@ -282,7 +282,7 @@ class TestReshapeOpDimInfer2_attr_ShapeTensor(TestReshapeOp_attr_ShapeTensor): def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) self.shape = (10, 0, 3, -1) @@ -302,14 +302,14 @@ def setUp(self): } self.attrs = {} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } def init_data(self): self.ori_shape = (4, 25) self.new_shape = (10, 10) - self.infered_shape = (10, 10) + self.inferred_shape = (10, 10) def test_check_output(self): self.check_output( @@ -330,7 +330,7 @@ class TestReshapeOpDimInfer1_attr_OnlyShape(TestReshapeOp_attr_OnlyShape): def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 10) - self.infered_shape = (5, -1, 10) + self.inferred_shape = (5, -1, 10) self.shape = (5, -1, -1) @@ -338,7 +338,7 @@ class TestReshapeOpDimInfer2_attr_OnlyShape(TestReshapeOp_attr_OnlyShape): def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) self.shape = (10, 0, 3, -1) @@ -359,7 +359,7 @@ def setUp(self): 'use_mkldnn': self.use_mkldnn, } self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype(np.float32), } @@ -369,7 +369,7 @@ def init_dtype(self): def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) def test_check_output(self): self.check_output_with_place( @@ -403,7 +403,7 @@ def setUp(self): } self.attrs = {"shape": self.new_shape} self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype("float32"), } diff --git a/test/legacy_test/test_swiglu.py b/test/legacy_test/test_swiglu.py index 96800658b4bf3..84db88c8e0c18 100644 --- a/test/legacy_test/test_swiglu.py +++ b/test/legacy_test/test_swiglu.py @@ -250,12 +250,12 @@ def test_input_x_y(self): result_dist_attrs = self.rule.infer_forward( self.x_dist_tensor_spec, self.y_dist_tensor_spec ) - infered_input_dist_attrs = result_dist_attrs[0] - infered_output_dist_attrs = result_dist_attrs[1] + inferred_input_dist_attrs = result_dist_attrs[0] + inferred_output_dist_attrs = result_dist_attrs[1] self.assertEqual(len(result_dist_attrs), 2) - self.assertEqual(len(infered_input_dist_attrs), 2) - self.assertEqual(len(infered_output_dist_attrs), 1) - self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [-1, 0]) + self.assertEqual(len(inferred_input_dist_attrs), 2) + self.assertEqual(len(inferred_output_dist_attrs), 1) + self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1, 0]) def test_input_x_unshard_last_dim(self): x_shape = [64, 32] @@ -268,12 +268,12 @@ def test_input_x_unshard_last_dim(self): result_dist_attrs = self.rule.infer_forward( self.x_dist_tensor_spec, DistTensorSpec() ) - infered_input_dist_attrs = result_dist_attrs[0] - infered_output_dist_attrs = result_dist_attrs[1] + inferred_input_dist_attrs = result_dist_attrs[0] + inferred_output_dist_attrs = result_dist_attrs[1] self.assertEqual(len(result_dist_attrs), 2) - self.assertEqual(len(infered_input_dist_attrs), 2) - self.assertEqual(len(infered_output_dist_attrs), 1) - self.assertEqual(infered_output_dist_attrs[0].dims_mapping, [0, -1]) + self.assertEqual(len(inferred_input_dist_attrs), 2) + self.assertEqual(len(inferred_output_dist_attrs), 1) + self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0, -1]) if __name__ == "__main__": diff --git a/test/legacy_test/testsuite.py b/test/legacy_test/testsuite.py index 1faae7dde278c..8303bedbff93a 100644 --- a/test/legacy_test/testsuite.py +++ b/test/legacy_test/testsuite.py @@ -111,7 +111,7 @@ def create_var(block, name, np_list, var_proto, is_calc_ref=False): np_value = np_list[name] if isinstance(np_value, tuple): dtype = np_value[0].dtype - # output shape, lod should be infered from input. + # output shape, lod should be inferred from input. if is_input: shape = list(np_value[0].shape) lod_level = len(np_value[1]) diff --git a/test/mkldnn/test_reshape_bf16_op.py b/test/mkldnn/test_reshape_bf16_op.py index 8780bdcecaea0..b3351e5dcdc3b 100644 --- a/test/mkldnn/test_reshape_bf16_op.py +++ b/test/mkldnn/test_reshape_bf16_op.py @@ -39,14 +39,14 @@ def setUp(self): 'mkldnn_data_type': self.mkldnn_data_type, } self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype(np.float32), } def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) def init_input_data(self): self.input_data_fp32 = np.random.random(self.ori_shape).astype( @@ -70,7 +70,7 @@ def test_check_grad(self): check_dygraph=False, user_defined_grads=[self.input_data_fp32], user_defined_grad_outputs=[ - self.inputs["X"].reshape(self.infered_shape) + self.inputs["X"].reshape(self.inferred_shape) ], check_pir_onednn=(self.op_type == "reshape2"), ) diff --git a/test/xpu/test_reshape2_op_xpu.py b/test/xpu/test_reshape2_op_xpu.py index 8c523bede17d8..2ff00216e31f7 100644 --- a/test/xpu/test_reshape2_op_xpu.py +++ b/test/xpu/test_reshape2_op_xpu.py @@ -46,7 +46,7 @@ def setUp(self): def init_data(self): self.ori_shape = (2, 60) self.new_shape = (12, 10) - self.infered_shape = (12, 10) + self.inferred_shape = (12, 10) def init_test_input(self): self.inputs = { @@ -55,7 +55,7 @@ def init_test_input(self): def init_test_output(self): self.outputs = { - "Out": self.inputs["X"].reshape(self.infered_shape), + "Out": self.inputs["X"].reshape(self.inferred_shape), 'XShape': np.random.random(self.ori_shape).astype(self.dtype), } @@ -76,13 +76,13 @@ class TestReshapeOpDimInfer1(TestReshapeOp): def init_data(self): self.ori_shape = (5, 25) self.new_shape = (5, -1, 5) - self.infered_shape = (5, -1, 5) + self.inferred_shape = (5, -1, 5) class TestReshapeOpDimInfer2(TestReshapeOp): def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) # situation 2: have shape(list, no tensor), have actual shape(Tensor) class TestReshapeOpWithInputShape(TestReshapeOp): @@ -108,7 +108,7 @@ class TestReshapeOp_attr_ShapeTensor(TestReshapeOp): def init_data(self): self.ori_shape = (4, 25) self.new_shape = (10, 10) - self.infered_shape = (10, 10) + self.inferred_shape = (10, 10) self.shape = (-1, -1) def init_test_input(self): @@ -132,7 +132,7 @@ class TestReshapeOpDimInfer1_attr_ShapeTensor( def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 20) - self.infered_shape = (5, -1, 20) + self.inferred_shape = (5, -1, 20) self.shape = (5, -1, -1) class TestReshapeOpDimInfer2_attr_ShapeTensor( @@ -141,7 +141,7 @@ class TestReshapeOpDimInfer2_attr_ShapeTensor( def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) self.shape = (10, 0, 3, -1) # Situation 4: have shape(Tensor), no actual shape(Tensor) @@ -149,7 +149,7 @@ class TestReshapeOp_attr_OnlyShape(TestReshapeOp): def init_data(self): self.ori_shape = (4, 25) self.new_shape = (10, 10) - self.infered_shape = (10, 10) + self.inferred_shape = (10, 10) def init_test_input(self): self.inputs = { @@ -164,14 +164,14 @@ class TestReshapeOpDimInfer1_attr_OnlyShape(TestReshapeOp_attr_OnlyShape): def init_data(self): self.ori_shape = (5, 20) self.new_shape = (5, -1, 10) - self.infered_shape = (5, -1, 10) + self.inferred_shape = (5, -1, 10) self.shape = (5, -1, -1) class TestReshapeOpDimInfer2_attr_OnlyShape(TestReshapeOp_attr_OnlyShape): def init_data(self): self.ori_shape = (10, 2, 6) self.new_shape = (10, 0, 3, -1) - self.infered_shape = (10, 2, 3, -1) + self.inferred_shape = (10, 2, 3, -1) self.shape = (10, 0, 3, -1) @check_run_big_shape_test() @@ -179,35 +179,35 @@ class TestReshapeOpLargeShape1(TestReshapeOp): def init_data(self): self.ori_shape = (5120, 32) self.new_shape = (32, 5120) - self.infered_shape = (32, 5120) + self.inferred_shape = (32, 5120) @check_run_big_shape_test() class TestReshapeOpLargeShape2(TestReshapeOp): def init_data(self): self.ori_shape = (1, 8192, 5120) self.new_shape = (8192, 5120) - self.infered_shape = (8192, 5120) + self.inferred_shape = (8192, 5120) @check_run_big_shape_test() class TestReshapeOpLargeShape3(TestReshapeOp): def init_data(self): self.ori_shape = (1, 8192) self.new_shape = (8192,) - self.infered_shape = (8192,) + self.inferred_shape = (8192,) @check_run_big_shape_test() class TestReshapeOpLargeShape4(TestReshapeOp): def init_data(self): self.ori_shape = (1, 8192, 5, 64, 2) self.new_shape = (1, 8192, 5, 128) - self.infered_shape = (1, 8192, 5, 128) + self.inferred_shape = (1, 8192, 5, 128) @check_run_big_shape_test() class TestReshapeOpLargeShape5(TestReshapeOp): def init_data(self): self.ori_shape = (1, 8192, 5, 128) self.new_shape = (1, 8192, 640) - self.infered_shape = (1, 8192, 640) + self.inferred_shape = (1, 8192, 640) support_types = get_xpu_op_support_types("reshape2") From a97c0d776762937c9b0790585fea2d2df7022268 Mon Sep 17 00:00:00 2001 From: SigureMo Date: Sat, 25 Jan 2025 12:58:36 +0800 Subject: [PATCH 2/3] use `PADDLE_GET` rather than `paddle::get` --- test/cpp/auto_parallel/spmd_rule_test.cc | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/test/cpp/auto_parallel/spmd_rule_test.cc b/test/cpp/auto_parallel/spmd_rule_test.cc index 135b400866ee9..64c1af6889e69 100644 --- a/test/cpp/auto_parallel/spmd_rule_test.cc +++ b/test/cpp/auto_parallel/spmd_rule_test.cc @@ -686,7 +686,8 @@ TEST(ConcatRule, Ctor) { inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( inferred_dist_attrs.second[0])); - auto& inputs_infer1 = paddle::get<1>(inferred_dist_attrs.first[0]); + auto& inputs_infer1 = + PADDLE_GET(std::vector, inferred_dist_attrs.first[0]); for (auto e : inputs_infer1) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); @@ -743,7 +744,8 @@ TEST(ConcatRule, Ctor) { inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( inferred_dist_attrs.second[0])); - auto& inputs_infer2 = paddle::get<1>(inferred_dist_attrs.first[0]); + auto& inputs_infer2 = + PADDLE_GET(std::vector, inferred_dist_attrs.first[0]); for (auto e : inputs_infer2) { check_dim_mapping(e, {1, -1, 0}); check_partial_dims(e, {}); From 80a998edd15c9cad05d87be10eb5c90cbcbedc8a Mon Sep 17 00:00:00 2001 From: SigureMo Date: Sat, 25 Jan 2025 13:18:22 +0800 Subject: [PATCH 3/3] use `PADDLE_GET_CONST` --- test/cpp/auto_parallel/spmd_rule_test.cc | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/test/cpp/auto_parallel/spmd_rule_test.cc b/test/cpp/auto_parallel/spmd_rule_test.cc index 64c1af6889e69..9704786e4b509 100644 --- a/test/cpp/auto_parallel/spmd_rule_test.cc +++ b/test/cpp/auto_parallel/spmd_rule_test.cc @@ -686,8 +686,8 @@ TEST(ConcatRule, Ctor) { inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( inferred_dist_attrs.second[0])); - auto& inputs_infer1 = - PADDLE_GET(std::vector, inferred_dist_attrs.first[0]); + auto& inputs_infer1 = PADDLE_GET_CONST(std::vector, + inferred_dist_attrs.first[0]); for (auto e : inputs_infer1) { check_dim_mapping(e, {-1, 1, 0}); check_partial_dims(e, {}); @@ -744,8 +744,8 @@ TEST(ConcatRule, Ctor) { inferred_dist_attrs.first[0])); EXPECT_TRUE(paddle::holds_alternative( inferred_dist_attrs.second[0])); - auto& inputs_infer2 = - PADDLE_GET(std::vector, inferred_dist_attrs.first[0]); + auto& inputs_infer2 = PADDLE_GET_CONST(std::vector, + inferred_dist_attrs.first[0]); for (auto e : inputs_infer2) { check_dim_mapping(e, {1, -1, 0}); check_partial_dims(e, {});