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/*
* Copyright (c) 2018 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FUSION_FIXTURE
#define ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FUSION_FIXTURE
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
#include "tests/IAccessor.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/Helpers.h"
#include "tests/validation/reference/BatchNormalizationLayer.h"
#include "tests/validation/reference/ConvolutionLayer.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename ConvolutionFunctionType, typename FusionFunctionType, typename T>
class BatchNormalizationLayerFusionValidationFixture : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation,
bool use_conv_b, bool use_beta, bool use_gamma, float epsilon, DataType dt, DataLayout data_layout)
{
ARM_COMPUTE_UNUSED(dilation);
_data_type = dt;
_data_layout = data_layout;
_use_conv_b = use_conv_b;
_use_beta = use_beta;
_use_gamma = use_gamma;
_target = compute_target(src_shape, w_shape, b_shape, dst_shape, info, epsilon);
_reference = compute_reference(src_shape, w_shape, b_shape, dst_shape, info, epsilon);
}
protected:
template <typename U>
void fill(U &&src, U &&w_tensor, U &&b_tensor, U &&mean_tensor, U &&var_tensor, U &&beta_tensor, U &&gamma_tensor)
{
std::uniform_real_distribution<> distribution(-1.f, 1.f);
std::uniform_real_distribution<> distribution_gz(0, 1.f);
library->fill(src, distribution, 0);
library->fill(w_tensor, distribution, 1);
library->fill(mean_tensor, distribution, 2);
library->fill(var_tensor, distribution_gz, 3);
_use_conv_b ? library->fill(b_tensor, distribution, 4) : library->fill_tensor_value(b_tensor, 0.f);
_use_beta ? library->fill(beta_tensor, distribution, 5) : library->fill_tensor_value(beta_tensor, 0.f);
_use_gamma ? library->fill(gamma_tensor, distribution, 6) : library->fill_tensor_value(gamma_tensor, 1.f);
}
TensorType compute_target(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, float epsilon)
{
if(_data_layout == DataLayout::NHWC)
{
permute(src_shape, PermutationVector(2U, 0U, 1U));
permute(w_shape, PermutationVector(2U, 0U, 1U));
permute(dst_shape, PermutationVector(2U, 0U, 1U));
}
// Create tensors
TensorType src = create_tensor<TensorType>(src_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType conv_w = create_tensor<TensorType>(w_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType conv_b = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType bn_mean = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType bn_var = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType bn_beta = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType bn_gamma = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType fused_w = create_tensor<TensorType>(w_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType fused_b = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType dst = create_tensor<TensorType>(dst_shape, _data_type, 1, QuantizationInfo(), _data_layout);
// Create and configure function
FusionFunctionType fuse_fn;
ConvolutionFunctionType conv_fn;
TensorType *conv_b_ptr = _use_conv_b ? &conv_b : nullptr;
TensorType *beta_ptr = _use_beta ? &bn_beta : nullptr;
TensorType *gamma_ptr = _use_gamma ? &bn_gamma : nullptr;
fuse_fn.configure(&conv_w, &bn_mean, &bn_var, &fused_w, &fused_b, conv_b_ptr, beta_ptr, gamma_ptr, epsilon);
conv_fn.configure(&src, &fused_w, &fused_b, &dst, info);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(conv_w.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(conv_b.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(bn_mean.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(bn_var.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(bn_beta.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(bn_gamma.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(fused_w.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(fused_b.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
conv_w.allocator()->allocate();
conv_b.allocator()->allocate();
bn_mean.allocator()->allocate();
bn_var.allocator()->allocate();
bn_beta.allocator()->allocate();
bn_gamma.allocator()->allocate();
fused_w.allocator()->allocate();
fused_b.allocator()->allocate();
dst.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!conv_w.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!conv_b.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!bn_mean.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!bn_var.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!bn_beta.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!bn_gamma.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!fused_w.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!fused_b.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
fill(AccessorType(src),
AccessorType(conv_w), AccessorType(conv_b),
AccessorType(bn_mean), AccessorType(bn_var), AccessorType(bn_beta), AccessorType(bn_gamma));
// Compute function
fuse_fn.run();
conv_fn.run();
return dst;
}
SimpleTensor<T> compute_reference(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, float epsilon)
{
// Create reference
SimpleTensor<T> src{ src_shape, _data_type, 1 };
SimpleTensor<T> conv_w{ w_shape, _data_type, 1 };
SimpleTensor<T> conv_b{ b_shape, _data_type, 1 };
SimpleTensor<T> bn_var{ b_shape, _data_type, 1 };
SimpleTensor<T> bn_mean{ b_shape, _data_type, 1 };
SimpleTensor<T> bn_beta{ b_shape, _data_type, 1 };
SimpleTensor<T> bn_gamma{ b_shape, _data_type, 1 };
// Fill reference
fill(src, conv_w, conv_b, bn_mean, bn_var, bn_beta, bn_gamma);
// Calculate Conv + BN
auto conv_res = reference::convolution_layer(src, conv_w, conv_b, dst_shape, info);
return reference::batch_normalization_layer(conv_res, bn_mean, bn_var, bn_beta, bn_gamma, epsilon, ActivationLayerInfo());
}
TensorType _target{};
SimpleTensor<T> _reference{};
DataType _data_type{};
DataLayout _data_layout{};
bool _use_conv_b{};
bool _use_beta{};
bool _use_gamma{};
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FUSION_FIXTURE */
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