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+/*
+ * 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.
+ */
+#include "NEON/Helper.h"
+#include "NEON/NEAccessor.h"
+#include "TypePrinter.h"
+#include "dataset/ConvolutionLayerDataset.h"
+#include "validation/Datasets.h"
+#include "validation/Reference.h"
+#include "validation/Validation.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
+
+#include <random>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::neon;
+using namespace arm_compute::test::validation;
+
+namespace
+{
+const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+const float tolerance_qs8 = 3.0f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
+
+Tensor compute_convolution_layer(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, DataType dt,
+ const PadStrideInfo &conv_info, int fixed_point_position)
+{
+ // Create tensors
+ Tensor src = create_tensor(input_shape, dt, 1, fixed_point_position);
+ Tensor weights = create_tensor(weights_shape, dt, 1, fixed_point_position);
+ Tensor bias = create_tensor(bias_shape, dt, 1, fixed_point_position);
+ Tensor dst = create_tensor(output_shape, dt, 1, fixed_point_position);
+
+ // Create and configure function
+ NEConvolutionLayer conv;
+ conv.configure(&src, &weights, &bias, &dst, conv_info);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ weights.allocator()->allocate();
+ bias.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ BOOST_TEST(!src.info()->is_resizable());
+ BOOST_TEST(!weights.info()->is_resizable());
+ BOOST_TEST(!bias.info()->is_resizable());
+ BOOST_TEST(!dst.info()->is_resizable());
+
+ // Fill tensors
+ if(dt == DataType::F32)
+ {
+ std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+ library->fill(NEAccessor(src), distribution, 0);
+ library->fill(NEAccessor(weights), distribution, 1);
+ library->fill(NEAccessor(bias), distribution, 2);
+ }
+ else
+ {
+ library->fill_tensor_uniform(NEAccessor(src), 0);
+ library->fill_tensor_uniform(NEAccessor(weights), 1);
+ library->fill_tensor_uniform(NEAccessor(bias), 2);
+ }
+
+ // Compute NEConvolutionLayer function
+ conv.run();
+
+ return dst;
+}
+} // namespace
+
+#ifndef DOXYGEN_SKIP_THIS
+BOOST_AUTO_TEST_SUITE(NEON)
+BOOST_AUTO_TEST_SUITE(ConvolutionLayer)
+BOOST_AUTO_TEST_SUITE(GEMM)
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(Configuration,
+ AlexNetConvolutionLayerDataset() * boost::unit_test::data::make({ DataType::F32, DataType::QS8 }),
+ conv_set, dt)
+{
+ // Set fixed point position data type allowed
+ int fixed_point_position = (dt == DataType::F32) ? 0 : 3;
+
+ // Create tensors
+ Tensor src = create_tensor(conv_set.src_shape, dt, 1, fixed_point_position);
+ Tensor weights = create_tensor(conv_set.weights_shape, dt, 1, fixed_point_position);
+ Tensor bias = create_tensor(conv_set.bias_shape, dt, 1, fixed_point_position);
+ Tensor dst = create_tensor(conv_set.dst_shape, dt, 1, fixed_point_position);
+
+ BOOST_TEST(src.info()->is_resizable());
+ BOOST_TEST(weights.info()->is_resizable());
+ BOOST_TEST(bias.info()->is_resizable());
+ BOOST_TEST(dst.info()->is_resizable());
+
+ // Create and configure function
+ NEConvolutionLayer conv;
+ conv.configure(&src, &weights, &bias, &dst, conv_set.info);
+
+ // Validate valid region
+ const ValidRegion src_valid_region = shape_to_valid_region(conv_set.src_shape);
+ const ValidRegion weights_valid_region = shape_to_valid_region(conv_set.weights_shape);
+ const ValidRegion bias_valid_region = shape_to_valid_region(conv_set.bias_shape);
+ const ValidRegion dst_valid_region = shape_to_valid_region(conv_set.dst_shape);
+
+ validate(src.info()->valid_region(), src_valid_region);
+ validate(weights.info()->valid_region(), weights_valid_region);
+ validate(bias.info()->valid_region(), bias_valid_region);
+ validate(dst.info()->valid_region(), dst_valid_region);
+}
+
+BOOST_AUTO_TEST_SUITE(Float)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(SmallConvolutionLayer,
+ SmallConvolutionLayerDataset() * boost::unit_test::data::make(DataType::F32),
+ conv_set, dt)
+{
+ // Compute function
+ Tensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Validate output
+ validate(NEAccessor(dst), ref_dst, tolerance_f32);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(LargeConvolutionLayer,
+ AlexNetConvolutionLayerDataset() * boost::unit_test::data::make(DataType::F32),
+ conv_set, dt)
+{
+ // Compute function
+ Tensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, 0);
+
+ // Validate output
+ validate(NEAccessor(dst), ref_dst, tolerance_f32);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE(Quantized)
+BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
+BOOST_DATA_TEST_CASE(SmallConvolutionLayer,
+ SmallConvolutionLayerDataset() * boost::unit_test::data::make(DataType::QS8) * boost::unit_test::data::xrange(4, 7),
+ conv_set, dt, fixed_point_position)
+{
+ // Compute function
+ Tensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, fixed_point_position);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, fixed_point_position);
+
+ // Validate output
+ validate(NEAccessor(dst), ref_dst, tolerance_qs8);
+}
+
+BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
+BOOST_DATA_TEST_CASE(LargeConvolutionLayer,
+ AlexNetConvolutionLayerDataset() * boost::unit_test::data::make(DataType::QS8) * boost::unit_test::data::xrange(4, 7),
+ conv_set, dt, fixed_point_position)
+{
+ // Compute function
+ Tensor dst = compute_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, fixed_point_position);
+
+ // Compute reference
+ RawTensor ref_dst = Reference::compute_reference_convolution_layer(conv_set.src_shape, conv_set.weights_shape, conv_set.bias_shape, conv_set.dst_shape, dt, conv_set.info, fixed_point_position);
+
+ // Validate output
+ validate(NEAccessor(dst), ref_dst, tolerance_qs8);
+}
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+BOOST_AUTO_TEST_SUITE_END()
+#endif \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-19 22:16:27 +0000