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[onert-micro] Add MaxPool2D
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This pr adds MaxPool2D refactored kernel into onert-micro.

ONE-DCO-1.0-Signed-off-by: Artem Balyshev <[email protected]>
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Artem Balyshev committed Feb 28, 2024
1 parent d003f92 commit 5e51d4f
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1 change: 1 addition & 0 deletions onert-micro/onert-micro/include/OMStatus.h
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Expand Up @@ -30,6 +30,7 @@ enum OMStatus
ModelNotImport,
FailedCheckCondition,
NoQuantization,
UnsupportedQuantizationType,
UnsupportedDynamicShapeCase,
};

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95 changes: 95 additions & 0 deletions onert-micro/onert-micro/include/pal/common/PALMaxPool2DCommon.h
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/*
* Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

#ifndef ONERT_MICRO_EXECUTE_PAL_MAX_POOL_2D_COMMON_H
#define ONERT_MICRO_EXECUTE_PAL_MAX_POOL_2D_COMMON_H

#include "Params.h"
#include "PALUtils.h"

#include "core/OMKernelData.h"

namespace onert_micro
{
namespace execute
{
namespace pal
{

OMStatus MaxPool(const core::Pool2DParams &params, const core::OMRuntimeShape &input_shape,
const float *input_data, const core::OMRuntimeShape &output_shape,
float *output_data)
{
const int32_t batches = input_shape.dims(0);
const int32_t depth = output_shape.dims(3);
const int32_t input_height = input_shape.dims(1);
const int32_t input_width = input_shape.dims(2);
const int32_t output_height = output_shape.dims(1);
const int32_t output_width = output_shape.dims(2);
const int32_t stride_height = params.stride_h;
const int32_t stride_width = params.stride_w;
for (int batch = 0; batch < batches; ++batch)
{
for (int out_y = 0; out_y < output_height; ++out_y)
{
for (int out_x = 0; out_x < output_width; ++out_x)
{
for (int channel = 0; channel < depth; ++channel)
{
const int in_x_origin = (out_x * stride_width) - params.pad_w;
const int in_y_origin = (out_y * stride_height) - params.pad_h;
// Compute the boundaries of the filter region clamped so as to
// ensure that the filter window fits in the input array.
const int filter_x_start = std::max(0, -in_x_origin);
const int filter_x_end = std::min(params.filter_w, input_width - in_x_origin);
const int filter_y_start = std::max(0, -in_y_origin);
const int filter_y_end = std::min(params.filter_h, input_height - in_y_origin);
float max = std::numeric_limits<float>::lowest();
for (int filter_y = filter_y_start; filter_y < filter_y_end; ++filter_y)
{
for (int filter_x = filter_x_start; filter_x < filter_x_end; ++filter_x)
{
const int in_x = in_x_origin + filter_x;
const int in_y = in_y_origin + filter_y;

const int input_data_offset =
((batch * input_shape.dims(1) + in_y) * input_shape.dims(2) + in_x) *
input_shape.dims(3) +
channel;

max = std::max(max, input_data[input_data_offset]);
}
}
const int output_data_offset =
((batch * output_shape.dims(1) + out_y) * output_shape.dims(2) + out_x) *
output_shape.dims(3) +
channel;

output_data[output_data_offset] =
std::min(std::max(max, params.activation_min), params.activation_max);
}
}
}
}
return Ok;
}

} // namespace pal
} // namespace execute
} // namespace onert_micro

#endif // ONERT_MICRO_EXECUTE_PAL_MAX_POOL_2D_COMMON_H
3 changes: 3 additions & 0 deletions onert-micro/onert-micro/include/pal/mcu/KernelsToBuild.lst
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Expand Up @@ -2,3 +2,6 @@ REGISTER_KERNEL(ABS, Abs)
REGISTER_KERNEL(ADD, Add)
REGISTER_KERNEL(LOGISTIC, Logistic)
REGISTER_KERNEL(CONCATENATION, Concatenation)
REGISTER_KERNEL(MAX_POOL_2D, MaxPool2D)
REGISTER_KERNEL(MUL, Mul)
REGISTER_KERNEL(SUB, Sub)
41 changes: 41 additions & 0 deletions onert-micro/onert-micro/include/pal/mcu/PALMaxPool2D.h
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/*
* Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

#ifndef ONERT_MICRO_EXECUTE_PAL_MAX_POOL_2D_H
#define ONERT_MICRO_EXECUTE_PAL_MAX_POOL_2D_H

#include "PALMaxPool2DCommon.h"

namespace onert_micro
{
namespace execute
{
namespace pal
{

OMStatus MaxPool(const core::Pool2DParams &, const core::OMRuntimeShape &, const uint8_t *,
const core::OMRuntimeShape &, uint8_t *, circle::TensorType)
{
assert(false && "Not impl yet");
return UnsupportedType;
}

} // namespace pal
} // namespace execute
} // namespace onert_micro

#endif // ONERT_MICRO_EXECUTE_PAL_MAX_POOL_2D_H
107 changes: 107 additions & 0 deletions onert-micro/onert-micro/include/test_models/maxpool2d/FloatMaxPool2DKernel.h
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/*
* Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

#ifndef ONERT_MICRO_TEST_MODELS_FLOAT_MAXPOOL2D_KERNEL_H
#define ONERT_MICRO_TEST_MODELS_FLOAT_MAXPOOL2D_KERNEL_H

#include "TestDataMaxPool2DBase.h"

namespace onert_micro
{
namespace test_model
{
namespace maxpool2d_float
{
/*
* maxpool2d Kernel:
*
* Input(1, 3, 5, 1)
* |
* MaxPool2D
* |
* Output(1, 2, 2, 1)
*/
const unsigned char test_kernel_model_circle[] = {
0x18, 0x00, 0x00, 0x00, 0x43, 0x49, 0x52, 0x30, 0x00, 0x00, 0x0e, 0x00, 0x14, 0x00, 0x00, 0x00,
0x0c, 0x00, 0x08, 0x00, 0x10, 0x00, 0x04, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
0xbc, 0x00, 0x00, 0x00, 0x10, 0x02, 0x00, 0x00, 0x2c, 0x02, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00,
0xa8, 0x00, 0x00, 0x00, 0xa0, 0x00, 0x00, 0x00, 0x98, 0x00, 0x00, 0x00, 0x78, 0x00, 0x00, 0x00,
0x04, 0x00, 0x00, 0x00, 0x96, 0xff, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x5c, 0x00, 0x00, 0x00,
0x0c, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0e, 0x00, 0x08, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00,
0x14, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x0c, 0x00, 0x08, 0x00,
0x00, 0x00, 0x07, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x04, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x10, 0x00, 0x0c, 0x00, 0x08, 0x00, 0x04, 0x00,
0x0a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
0x05, 0x00, 0x00, 0x00, 0x32, 0x2e, 0x39, 0x2e, 0x31, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00,
0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
0x31, 0x2e, 0x35, 0x2e, 0x30, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
0xd0, 0xfe, 0xff, 0xff, 0xd4, 0xfe, 0xff, 0xff, 0xd8, 0xfe, 0xff, 0xff, 0x01, 0x00, 0x00, 0x00,
0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x18, 0x00, 0x14, 0x00, 0x10, 0x00, 0x0c, 0x00,
0x08, 0x00, 0x04, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00,
0x7c, 0x00, 0x00, 0x00, 0x80, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
0x6d, 0x61, 0x69, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00,
0x00, 0x00, 0x0e, 0x00, 0x16, 0x00, 0x00, 0x00, 0x10, 0x00, 0x0c, 0x00, 0x07, 0x00, 0x08, 0x00,
0x0e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x1c, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00,
0x34, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00, 0x18, 0x00, 0x17, 0x00, 0x10, 0x00, 0x0c, 0x00,
0x08, 0x00, 0x04, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x01, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
0x5c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xba, 0xff, 0xff, 0xff, 0x10, 0x00, 0x00, 0x00,
0x10, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0xac, 0xff, 0xff, 0xff,
0x11, 0x00, 0x00, 0x00, 0x50, 0x61, 0x72, 0x74, 0x69, 0x74, 0x69, 0x6f, 0x6e, 0x65, 0x64, 0x43,
0x61, 0x6c, 0x6c, 0x3a, 0x30, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0e, 0x00,
0x14, 0x00, 0x10, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x08, 0x00, 0x04, 0x00, 0x0e, 0x00, 0x00, 0x00,
0x14, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
0x04, 0x00, 0x04, 0x00, 0x04, 0x00, 0x00, 0x00, 0x13, 0x00, 0x00, 0x00, 0x73, 0x65, 0x72, 0x76,
0x69, 0x6e, 0x67, 0x5f, 0x64, 0x65, 0x66, 0x61, 0x75, 0x6c, 0x74, 0x5f, 0x78, 0x3a, 0x30, 0x00,
0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x0c, 0x00,
0x0b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x11, 0x00, 0x00, 0x00,
0x00, 0x00, 0x00, 0x11, 0x11, 0x00, 0x00, 0x00, 0x4f, 0x4e, 0x45, 0x2d, 0x74, 0x66, 0x6c, 0x69,
0x74, 0x65, 0x32, 0x63, 0x69, 0x72, 0x63, 0x6c, 0x65, 0x00, 0x00, 0x00};

const std::vector<float> input_data = {
1, -1, 0, -2, 2, //
-7, -6, -5, -4, -3, //
5, 4, 3, 6, 7, //
};

const std::vector<float> reference_output_data{
1, 2, //
5, 7, //
};

} // namespace maxpool2d_float

class TestDataFloatMaxPool2D : public TestDataMaxPool2DBase<float>
{
public:
TestDataFloatMaxPool2D()
{
_input_data = maxpool2d_float::input_data;
_reference_output_data = maxpool2d_float::reference_output_data;
_test_kernel_model_circle = maxpool2d_float::test_kernel_model_circle;
}

~TestDataFloatMaxPool2D() override = default;
};

} // namespace test_model
} // namespace onert_micro

#endif // ONERT_MICRO_TEST_MODELS_FLOAT_MAXPOOL2D_KERNEL_H
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