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author | Moritz Pflanzer <moritz.pflanzer@arm.com> | 2017-09-01 20:41:12 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | a09de0c8b2ed0f1481502d3b023375609362d9e3 (patch) | |
tree | e34b56d9ca69b025d7d9b943cc4df59cd458f6cb /tests/validation_new/fixtures/FullyConnectedLayerFixture.h | |
parent | 5280071b336d53aff94ca3a6c70ebbe6bf03f4c3 (diff) | |
download | ComputeLibrary-a09de0c8b2ed0f1481502d3b023375609362d9e3.tar.gz |
COMPMID-415: Rename and move tests
The boost validation is now "standalone" in validation_old and builds as
arm_compute_validation_old. The new validation builds now as
arm_compute_validation.
Change-Id: Ib93ba848a25680ac60afb92b461d574a0757150d
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/86187
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/validation_new/fixtures/FullyConnectedLayerFixture.h')
-rw-r--r-- | tests/validation_new/fixtures/FullyConnectedLayerFixture.h | 250 |
1 files changed, 0 insertions, 250 deletions
diff --git a/tests/validation_new/fixtures/FullyConnectedLayerFixture.h b/tests/validation_new/fixtures/FullyConnectedLayerFixture.h deleted file mode 100644 index 0953b0b67e..0000000000 --- a/tests/validation_new/fixtures/FullyConnectedLayerFixture.h +++ /dev/null @@ -1,250 +0,0 @@ -/* - * Copyright (c) 2017 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_FULLY_CONNECTED_LAYER_FIXTURE -#define ARM_COMPUTE_TEST_FULLY_CONNECTED_LAYER_FIXTURE - -#include "arm_compute/core/TensorShape.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Utils.h" -#include "framework/Asserts.h" -#include "framework/Fixture.h" -#include "tests/AssetsLibrary.h" -#include "tests/Globals.h" -#include "tests/IAccessor.h" -#include "tests/RawTensor.h" -#include "tests/validation_new/CPP/FullyConnectedLayer.h" -#include "tests/validation_new/Helpers.h" - -#include <random> - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace -{ -RawTensor transpose(const RawTensor &src, int interleave = 1) -{ - // Create reference - TensorShape dst_shape(src.shape()); - dst_shape.set(0, src.shape().y() * interleave); - dst_shape.set(1, std::ceil(src.shape().x() / static_cast<float>(interleave))); - - RawTensor dst{ dst_shape, src.data_type() }; - - // Compute reference - uint8_t *out_ptr = dst.data(); - - for(int i = 0; i < dst.num_elements(); i += interleave) - { - Coordinates coord = index2coord(dst.shape(), i); - size_t coord_x = coord.x(); - coord.set(0, coord.y() * interleave); - coord.set(1, coord_x / interleave); - - const int num_elements = std::min<int>(interleave, src.shape().x() - coord.x()); - - std::copy_n(static_cast<const uint8_t *>(src(coord)), num_elements * src.element_size(), out_ptr); - - out_ptr += interleave * dst.element_size(); - } - - return dst; -} -} // namespace - -template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave> -class FullyConnectedLayerValidationFixedPointFixture : public framework::Fixture -{ -public: - template <typename...> - void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type, int fractional_bits) - { - ARM_COMPUTE_UNUSED(weights_shape); - ARM_COMPUTE_UNUSED(bias_shape); - - _fractional_bits = fractional_bits; - _data_type = data_type; - - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights, data_type, fractional_bits); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights, data_type, fractional_bits); - } - -protected: - template <typename U> - void fill(U &&tensor, int i) - { - if(is_data_type_float(_data_type)) - { - std::uniform_real_distribution<> distribution(0.5f, 1.f); - library->fill(tensor, distribution, i); - } - else - { - library->fill_tensor_uniform(tensor, i); - } - } - - TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, bool transpose_weights, - bool reshape_weights, DataType data_type, int fixed_point_position) - { - TensorShape reshaped_weights_shape(weights_shape); - - // Test actions depending on the target settings - // - // | reshape | !reshape - // -----------+-----------+--------------------------- - // transpose | | *** - // -----------+-----------+--------------------------- - // !transpose | transpose | transpose & - // | | transpose1xW (if required) - // - // ***: That combination is invalid. But we can ignore the transpose flag and handle all !reshape the same - if(!reshape_weights || !transpose_weights) - { - const size_t shape_x = reshaped_weights_shape.x(); - reshaped_weights_shape.set(0, reshaped_weights_shape.y()); - reshaped_weights_shape.set(1, shape_x); - - // Weights have to be passed reshaped - // Transpose 1xW for batched version - if(!reshape_weights && output_shape.y() > 1 && run_interleave) - { - const int transpose_width = 16 / data_size_from_type(data_type); - const float shape_x = reshaped_weights_shape.x(); - reshaped_weights_shape.set(0, reshaped_weights_shape.y() * transpose_width); - reshaped_weights_shape.set(1, static_cast<unsigned int>(std::ceil(shape_x / transpose_width))); - } - } - - // Create tensors - TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position); - TensorType weights = create_tensor<TensorType>(reshaped_weights_shape, data_type, 1, fixed_point_position); - TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1, fixed_point_position); - TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position); - - // Create and configure function. - FunctionType fc; - fc.configure(&src, &weights, &bias, &dst, transpose_weights, !reshape_weights); - - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Allocate tensors - src.allocator()->allocate(); - weights.allocator()->allocate(); - bias.allocator()->allocate(); - dst.allocator()->allocate(); - - ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Fill tensors - fill(AccessorType(src), 0); - fill(AccessorType(bias), 2); - - if(!reshape_weights || !transpose_weights) - { - TensorShape tmp_shape(weights_shape); - RawTensor tmp(tmp_shape, data_type, 1, fixed_point_position); - - // Fill with original shape - fill(tmp, 1); - - // Transpose elementwise - tmp = transpose(tmp); - - // Reshape weights for batched runs - if(!reshape_weights && output_shape.y() > 1 && run_interleave) - { - // Transpose with interleave - const int interleave_size = 16 / tmp.element_size(); - tmp = transpose(tmp, interleave_size); - } - - AccessorType weights_accessor(weights); - - for(int i = 0; i < tmp.num_elements(); ++i) - { - Coordinates coord = index2coord(tmp.shape(), i); - std::copy_n(static_cast<const RawTensor::value_type *>(tmp(coord)), - tmp.element_size(), - static_cast<RawTensor::value_type *>(weights_accessor(coord))); - } - } - else - { - fill(AccessorType(weights), 1); - } - - // Compute NEFullyConnectedLayer function - fc.run(); - - return dst; - } - - SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, bool transpose_weights, - bool reshape_weights, DataType data_type, int fixed_point_position = 0) - { - // Create reference - SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position }; - SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position }; - SimpleTensor<T> bias{ bias_shape, data_type, 1, fixed_point_position }; - - // Fill reference - fill(src, 0); - fill(weights, 1); - fill(bias, 2); - - return reference::fully_connected_layer<T>(src, weights, bias, output_shape); - } - - TensorType _target{}; - SimpleTensor<T> _reference{}; - int _fractional_bits{}; - DataType _data_type{}; -}; - -template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave> -class FullyConnectedLayerValidationFixture : public FullyConnectedLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T, run_interleave> -{ -public: - template <typename...> - void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type) - { - FullyConnectedLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, - reshape_weights, data_type, - 0); - } -}; -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_FULLY_CONNECTED_LAYER_FIXTURE */ |