diff options
Diffstat (limited to 'tests')
-rw-r--r-- | tests/datasets/ShapeDatasets.h | 4 | ||||
-rw-r--r-- | tests/validation/CL/DeconvolutionLayer.cpp | 192 | ||||
-rw-r--r-- | tests/validation/NEON/DeconvolutionLayer.cpp | 14 | ||||
-rw-r--r-- | tests/validation/fixtures/DeconvolutionLayerFixture.h | 37 | ||||
-rw-r--r-- | tests/validation/reference/DeconvolutionLayer.cpp | 72 | ||||
-rw-r--r-- | tests/validation/reference/DeconvolutionLayer.h | 4 |
6 files changed, 245 insertions, 78 deletions
diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h index 58fba07bf8..a5e03c737f 100644 --- a/tests/datasets/ShapeDatasets.h +++ b/tests/datasets/ShapeDatasets.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -239,7 +239,7 @@ public: SmallDeconvolutionShapes() : ShapeDataset("InputShape", { - TensorShape{ 2U, 3U, 3U, 2U }, + TensorShape{ 4U, 3U, 3U, 2U }, TensorShape{ 5U, 5U, 3U }, TensorShape{ 11U, 13U, 4U, 3U } }) diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp new file mode 100644 index 0000000000..59e85537e5 --- /dev/null +++ b/tests/validation/CL/DeconvolutionLayer.cpp @@ -0,0 +1,192 @@ +/* + * Copyright (c) 2017, 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. + */ +#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/DeconvolutionLayerFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ + +const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) + * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); + +const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1) + * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); + +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(DeconvolutionLayer) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, (combine(datasets::SmallDeconvolutionShapes(), framework::dataset::make("DataType", DataType::F32))), + input_shape, data_type) +{ + // Create shapes + const unsigned int kernel_size_x = 3; + const unsigned int kernel_size_y = 3; + const unsigned int num_kernels = 1; + const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels); + const TensorShape bias_shape(num_kernels); + auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 0, 0, 1, 1); + TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape); + + // Create tensors + CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1); + CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1); + CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type, 1); + CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1); + + 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); + + // Create and configure function + CLDeconvolutionLayer deconv; + deconv.configure(&src, &weights, &bias, &dst, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), 0, 0); + + // Validate valid region + const ValidRegion src_valid_region = shape_to_valid_region(input_shape); + const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape); + const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape); + const ValidRegion dst_valid_region = shape_to_valid_region(output_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); +} + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid weights shape + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QS8, 4), // Non supported data type + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 11), // Invalid bias shape + TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32, 0), // Window shrink + TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32, 0), + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::QS8, 5), + TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32, 11), + TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32, 0), + })), + framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(1U), 1, DataType::F16, 0), + TensorInfo(TensorShape(1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(1U), 1, DataType::F32, 5), + TensorInfo(TensorShape(25U, 11U), 1, DataType::F32, 11), + TensorInfo(TensorShape(1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(4U), 1, DataType::F32, 0), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16, 0), + TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 5), + TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32, 0), + TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32, 0), + })), + framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 1, 1), + PadStrideInfo(1, 1, 0, 0), + })), + framework::dataset::make("ax", { 1U, + 1U, + 1U, + 1U, + 0U, + 0U, + })), + framework::dataset::make("ay", { 1U, + 1U, + 1U, + 1U, + 0U, + 0U, + })), + framework::dataset::make("Expected", { false, false, false, false, false, true })), + input_info, weights_info, bias_info, output_info, pad_info, ax, ay, expected) +{ + bool is_valid = bool(CLDeconvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pad_info, ax, ay)); + ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +template <typename T> +using CLDeconvolutionLayerFixture3x3 = DeconvolutionValidationFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 3, 3>; + +template <typename T> +using CLDeconvolutionLayerFixture1x1 = DeconvolutionValidationFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 1, 1>; + +TEST_SUITE(Float) + +TEST_SUITE(FP32) +TEST_SUITE(W3x3) + +FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture3x3<float>, framework::DatasetMode::ALL, combine(data3x3, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() + +TEST_SUITE(W1x1) +FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerFixture1x1<float>, framework::DatasetMode::ALL, combine(data1x1, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/NEON/DeconvolutionLayer.cpp b/tests/validation/NEON/DeconvolutionLayer.cpp index 751a96558a..9573784d86 100644 --- a/tests/validation/NEON/DeconvolutionLayer.cpp +++ b/tests/validation/NEON/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -44,15 +44,11 @@ namespace { constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ -const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, - 2) - * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 1, 3) * framework::dataset::make("ay", 1, 3) * framework::dataset::make("NumKernels", { 1, 3 }) - *framework::dataset::make("ux", 1, 4) *framework::dataset::make("uy", 1, 4); +const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2) + * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); -const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, - 1) - * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 1, 3) * framework::dataset::make("ay", 1, 3) * framework::dataset::make("NumKernels", { 1, 3 }) - *framework::dataset::make("ux", 1, 4) *framework::dataset::make("uy", 1, 4); +const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1) + * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 }); } // namespace 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); } }; diff --git a/tests/validation/reference/DeconvolutionLayer.cpp b/tests/validation/reference/DeconvolutionLayer.cpp index 82c2188ade..0cf1087346 100644 --- a/tests/validation/reference/DeconvolutionLayer.cpp +++ b/tests/validation/reference/DeconvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -39,26 +39,27 @@ SimpleTensor<T> deconvolution_layer(const SimpleTensor<T> &src, const SimpleTens const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a) { // Create reference + const int stride_x = info.stride().first; + const int stride_y = info.stride().second; TensorShape scaled_shape = src.shape(); - scaled_shape.set(0, output_shape.x()); - scaled_shape.set(1, output_shape.y()); + int out_x = src.shape().x() + (src.shape().x() - 1) * (stride_x - 1) + a.first + 2 * info.pad().first; + int out_y = src.shape().y() + (src.shape().y() - 1) * (stride_y - 1) + a.second + 2 * info.pad().second; + scaled_shape.set(0, out_x); + scaled_shape.set(1, out_y); SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1, src.fixed_point_position() }; - const int width_in = src.shape().x(); - const int height_in = src.shape().y(); - const int width_scaled = scaled.shape().x(); - const int height_scaled = scaled.shape().y(); - const int num_2d_slices = src.shape().total_size() / (width_in * height_in); - const float width_ratio = static_cast<float>(width_in) / static_cast<float>(width_scaled); - const float height_ratio = static_cast<float>(height_in) / static_cast<float>(height_scaled); - const int ax = a.first; // The number of zeros added to right edge of the input. - const int ay = a.second; // The number of zeros added to bottom edge of the input. - const unsigned int kernel_size = weights.shape().x(); - ARM_COMPUTE_ERROR_ON(info.pad().first > (kernel_size - 1)); - const int transposed_convolution_padx = kernel_size - info.pad().first - 1; - const int transposed_convolution_pady = kernel_size - info.pad().second - 1; - const int stridex = info.stride().first; - const int stridey = info.stride().second; + const int width_in = src.shape().x(); + const int height_in = src.shape().y(); + const int width_scaled = scaled.shape().x(); + const int height_scaled = scaled.shape().y(); + const int num_2d_slices = src.shape().total_size() / (width_in * height_in); + const int ax = a.first; // The number of zeros added to right edge of the input. + const int ay = a.second; // The number of zeros added to top edge of the input. + ARM_COMPUTE_ERROR_ON(info.pad().first > (weights.shape().x() - 1)); + + ARM_COMPUTE_ERROR_ON_MSG(ax > stride_x - 1, "ax must be smaller than stride_x"); + ARM_COMPUTE_ERROR_ON_MSG(ay > stride_y - 1, "ay must be smaller than stride_y"); + for(int j = 0; j < scaled.num_elements(); ++j) { scaled[j] = T(0); @@ -68,34 +69,23 @@ SimpleTensor<T> deconvolution_layer(const SimpleTensor<T> &src, const SimpleTens { const int offset_slice_in = slice * width_in * height_in; const int offset_slice_out = slice * width_scaled * height_scaled; - for(int yi = ay; yi < height_scaled; yi += stridey) + const int start_x = info.pad().first; + const int start_y = ay + info.pad().second; + const int end_y = height_scaled - info.pad().second; + const int end_x = width_scaled - ax - info.pad().first; + + for(int yi = start_y, in_y = 0; yi < end_y; yi += stride_y, in_y++) { - for(int xi = transposed_convolution_padx; xi < width_scaled; xi += stridex) + for(int xi = start_x, in_x = 0; xi < end_x; xi += stride_x, in_x++) { - const float x_src = (xi + 0.5f) * width_ratio - 0.5f; - const float y_src = (yi + 0.5f) * height_ratio - 0.5f; - T *out = scaled.data() + offset_slice_out + xi + yi * width_scaled; - const bool in_bounds = x_src > -1 && y_src > -1 && x_src < width_in && y_src < height_in; - const bool in_axy = xi < transposed_convolution_padx || xi >= (width_scaled - ax) // this is checking if the x coordinate is in the padded left/right area - || yi < ay || yi >= (height_scaled - transposed_convolution_pady); // like above but top and bottom padding in the upscaled XY plane - if(!in_axy) - { - if(in_bounds) - { - const int in_scaled_x = (x_src < 0.f) ? static_cast<int>(x_src - 0.5f) : static_cast<int>(x_src + 0.5f); - const int in_scaled_y = (y_src < 0.f) ? static_cast<int>(y_src - 0.5f) : static_cast<int>(y_src + 0.5f); - const T *in = src.data() + offset_slice_in + in_scaled_x + in_scaled_y * width_in; - *out = *in; - } - else - { - *out = T(0); - } - } + const T *in = src.data() + offset_slice_in + in_y * width_in + in_x; + T *out = scaled.data() + offset_slice_out + xi + yi * width_scaled; + *out = *in; } } } - const PadStrideInfo conv_info(1, 1, 1, 1, DimensionRoundingType::CEIL); + + const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); return convolution_layer(scaled, weights, bias, output_shape, conv_info); } diff --git a/tests/validation/reference/DeconvolutionLayer.h b/tests/validation/reference/DeconvolutionLayer.h index 8222e32027..c0bc1fa928 100644 --- a/tests/validation/reference/DeconvolutionLayer.h +++ b/tests/validation/reference/DeconvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -42,7 +42,7 @@ namespace reference * bias Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input. * output_shape Output tensor shape. The output has the same number of dimensions as the @p input. * info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. - * a The number of zeros added to right edge of the input. + * a The number of zeros added to right and top edges of the input. * */ template <typename T> |