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author | Moritz Pflanzer <moritz.pflanzer@arm.com> | 2017-09-08 09:53:14 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | cde1e8adeacea5c33a1682ef7b05a0ef643463b8 (patch) | |
tree | 47e58abdf5bb6ef39db362a2ac777c93b3f76666 /tests/validation/fixtures/DirectConvolutionLayerFixture.h | |
parent | 86b53339679e12c952a24a8845a5409ac3d52de6 (diff) | |
download | ComputeLibrary-cde1e8adeacea5c33a1682ef7b05a0ef643463b8.tar.gz |
COMPMID-415: Add tests for ConvolutionLayer reshaped weights
Change-Id: I6c1209a2afafccba2cbdbcda16aceb3ae0cc7b4b
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/87000
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'tests/validation/fixtures/DirectConvolutionLayerFixture.h')
-rw-r--r-- | tests/validation/fixtures/DirectConvolutionLayerFixture.h | 87 |
1 files changed, 85 insertions, 2 deletions
diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h index 6ffebce108..a709157c7b 100644 --- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h @@ -41,20 +41,103 @@ namespace test namespace validation { template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class DirectConvolutionValidationFixedPointFixture : public ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T> +class DirectConvolutionValidationFixedPointFixture : public framework::Fixture { public: template <typename...> void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits) { + _fractional_bits = fractional_bits; + _data_type = data_type; + const TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels); const TensorShape bias_shape(num_kernels); const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR); const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info); - ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits); + } + +protected: + template <typename U> + void fill(U &&tensor, int i) + { + switch(tensor.data_type()) + { + case DataType::F16: + case DataType::F32: + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + break; + } + default: + 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, const PadStrideInfo &info, + DataType data_type, int fixed_point_position) + { + // Create tensors + TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position); + TensorType weights = create_tensor<TensorType>(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 conv; + conv.configure(&src, &weights, &bias, &dst, info); + + 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(weights), 1); + fill(AccessorType(bias), 2); + + // Compute NEConvolutionLayer function + conv.run(); + + return dst; + } + + SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, + DataType data_type, int fixed_point_position) + { + // 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::convolution_layer<T>(src, weights, bias, output_shape, info); } + TensorType _target{}; + SimpleTensor<T> _reference{}; + int _fractional_bits{}; + DataType _data_type{}; + private: TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info) { |