diff options
Diffstat (limited to 'tests/validation/fixtures/DeconvolutionLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/DeconvolutionLayerFixture.h | 37 |
1 files changed, 13 insertions, 24 deletions
diff --git a/tests/validation/fixtures/DeconvolutionLayerFixture.h b/tests/validation/fixtures/DeconvolutionLayerFixture.h index e98f5e93c0..f2455f31ac 100644 --- a/tests/validation/fixtures/DeconvolutionLayerFixture.h +++ b/tests/validation/fixtures/DeconvolutionLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -43,20 +43,15 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class DeconvolutionLayerFixtureBase : public framework::Fixture { public: - /* - * - * @param[in] a The number of zeros added to right and bottom edges of the input. - * @param[in] u How much to scale the X and Y axis. - */ template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, - const std::pair<unsigned int, unsigned int> &a, const std::pair<unsigned int, unsigned int> &u, DataType data_type, int fractional_bits) + const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type, int fractional_bits) { _fractional_bits = fractional_bits; _data_type = data_type; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, a, u, data_type, fractional_bits); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, a, data_type, fractional_bits); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, fractional_bits); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, fractional_bits); } protected: @@ -75,13 +70,9 @@ protected: library->fill_tensor_uniform(tensor, i); } } - /* - * - * @param[in] a The number of zeros added to right and bottom edges of the input. - * @param[in] u How much to scale the X and Y axis. - */ + TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, - const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a, const std::pair<float, float> &u, DataType data_type, int fixed_point_position) + const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type, int fixed_point_position) { // Create tensors TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position); @@ -91,7 +82,7 @@ protected: // Create and configure function FunctionType conv; - conv.configure(&src, &weights, &bias, &dst, info, a.first, a.second, u.first, u.second); + conv.configure(&src, &weights, &bias, &dst, info, inner_border.first, inner_border.second); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -121,7 +112,7 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, - const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> a, DataType data_type, int fixed_point_position) + const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> inner_border, DataType data_type, int fixed_point_position) { // Create reference SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position }; @@ -133,7 +124,7 @@ protected: fill(weights, 1); fill(bias, 2); - return reference::deconvolution_layer<T>(src, weights, bias, output_shape, info, a); + return reference::deconvolution_layer<T>(src, weights, bias, output_shape, info, inner_border); } TensorType _target{}; @@ -148,18 +139,16 @@ class DeconvolutionValidationFixture : public DeconvolutionLayerFixtureBase<Tens public: template <typename...> void setup(TensorShape input_shape, unsigned int sx, unsigned int sy, unsigned int padx, unsigned int pady, - unsigned int ax, unsigned int ay, unsigned int ux, unsigned int uy, unsigned int num_kernels, DataType data_type) + unsigned int inner_border_right, unsigned int inner_border_top, unsigned int num_kernels, DataType data_type) { ARM_COMPUTE_ERROR_ON_MSG(kernel_size_x != kernel_size_y, "Only square kernels supported"); const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels); const TensorShape bias_shape(num_kernels); const PadStrideInfo info(sx, sy, padx, pady, DimensionRoundingType::CEIL); - const std::pair<unsigned int, unsigned int> a(ax, ay); - const std::pair<float, float> u(ux, uy); - auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, padx, pady, a.first, a.second, u.first, u.second, - DimensionRoundingType::CEIL); + const std::pair<unsigned int, unsigned int> inner_border(inner_border_right, inner_border_top); + auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, padx, pady, inner_border.first, inner_border.second, sx, sy); TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape); - DeconvolutionLayerFixtureBase<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, a, u, data_type, 0); + DeconvolutionLayerFixtureBase<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, 0); } }; |