diff options
| -rw-r--r-- | src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp | 8 | ||||
| -rw-r--r-- | src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp | 25 | ||||
| -rw-r--r-- | src/core/CL/kernels/CLPoolingLayerKernel.cpp | 48 | ||||
| -rw-r--r-- | src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp | 31 | ||||
| -rw-r--r-- | tests/datasets/DepthwiseConvolutionLayerDataset.h | 3 | ||||
| -rw-r--r-- | tests/datasets/PoolingLayerDataset.h | 15 | ||||
| -rw-r--r-- | tests/validation/CL/DirectConvolutionLayer.cpp | 4 | ||||
| -rw-r--r-- | tests/validation/CL/PoolingLayer.cpp | 12 | ||||
| -rw-r--r-- | tests/validation/NEON/DirectConvolutionLayer.cpp | 4 | ||||
| -rw-r--r-- | tests/validation/NEON/PoolingLayer.cpp | 9 | ||||
| -rw-r--r-- | tests/validation/fixtures/PoolingLayerFixture.h | 13 | ||||
| -rw-r--r-- | tests/validation/reference/DepthwiseConvolutionLayer.cpp | 8 |
12 files changed, 103 insertions, 77 deletions
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp index c7cee4c387..c24420a7e3 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3Kernel.cpp @@ -121,10 +121,10 @@ void CLDepthwiseConvolutionLayer3x3Kernel::configure(const ICLTensor *input, con const GPUTarget gpu_target = get_arch_from_target(get_target()); // Configure kernel window - const unsigned int conv_pad_left = std::max(conv_info.pad_left(), 1U); - const unsigned int conv_pad_top = std::max(conv_info.pad_top(), 1U); - const unsigned int conv_pad_right = std::max(conv_info.pad_right(), 1U); - const unsigned int conv_pad_bottom = std::max(conv_info.pad_bottom(), 1U); + const unsigned int conv_pad_left = conv_info.pad_left(); + const unsigned int conv_pad_top = conv_info.pad_top(); + const unsigned int conv_pad_right = conv_info.pad_right(); + const unsigned int conv_pad_bottom = conv_info.pad_bottom(); unsigned int num_elems_read_per_iteration_x = 0; unsigned int num_elems_read_per_iteration_y = 0; diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp index 4b141f7ecd..ac3c9ac4a6 100644 --- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp +++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -126,10 +126,10 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen unsigned int conv_stride_x = std::get<0>(conv_info.stride()); unsigned int conv_stride_y = std::get<1>(conv_info.stride()); - unsigned int conv_pad_left = std::max(conv_info.pad_left(), kernel_size / 2); - unsigned int conv_pad_top = std::max(conv_info.pad_top(), kernel_size / 2); - unsigned int conv_pad_right = std::max(conv_info.pad_right(), kernel_size / 2); - unsigned int conv_pad_bottom = std::max(conv_info.pad_bottom(), kernel_size / 2); + unsigned int conv_pad_left = conv_info.pad_left(); + unsigned int conv_pad_top = conv_info.pad_top(); + unsigned int conv_pad_right = conv_info.pad_right(); + unsigned int conv_pad_bottom = conv_info.pad_bottom(); unsigned int num_elems_read_per_iteration_x = 0; unsigned int num_elems_read_per_iteration_y = 0; @@ -302,18 +302,13 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL _conv_stride_x = std::get<0>(conv_info.stride()); _conv_stride_y = std::get<1>(conv_info.stride()); + _border_size = BorderSize(conv_info.pad_top(), conv_info.pad_right(), conv_info.pad_bottom(), conv_info.pad_left()); _input = input; _weights = weights; _output = output; _biases = biases; - int conv_pad_left = std::min(conv_info.pad_left(), kernel_size / 2); - int conv_pad_top = std::min(conv_info.pad_top(), kernel_size / 2); - int conv_pad_right = std::min(conv_info.pad_right(), kernel_size / 2); - int conv_pad_bottom = std::min(conv_info.pad_bottom(), kernel_size / 2); - _border_size = BorderSize(conv_pad_top, conv_pad_right, conv_pad_bottom, conv_pad_left); - const GPUTarget gpu_target = get_arch_from_target(get_target()); std::stringstream kernel_name; @@ -450,13 +445,13 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL _config_id += "_"; _config_id += support::cpp11::to_string(kernel_size); _config_id += "_"; - _config_id += support::cpp11::to_string(conv_pad_left); + _config_id += support::cpp11::to_string(border_size().left); _config_id += "_"; - _config_id += support::cpp11::to_string(conv_pad_top); + _config_id += support::cpp11::to_string(border_size().top); _config_id += "_"; - _config_id += support::cpp11::to_string(conv_pad_right); + _config_id += support::cpp11::to_string(border_size().right); _config_id += "_"; - _config_id += support::cpp11::to_string(conv_pad_bottom); + _config_id += support::cpp11::to_string(border_size().bottom); _config_id += "_"; _config_id += support::cpp11::to_string(_conv_stride_x); _config_id += "_"; diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp index c515ed68e7..b3034e10cc 100644 --- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp +++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp @@ -61,15 +61,11 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(input->data_type()) && pool_info.pool_type() == PoolingType::L2), "Unsupported combination of parameters!"); - ARM_COMPUTE_RETURN_ERROR_ON(!pool_info.pad_stride_info().padding_is_symmetric()); const bool is_global_pooling = pool_info.is_global_pooling(); const unsigned int pool_size_x = is_global_pooling ? input->tensor_shape().x() : pool_info.pool_size().width; const unsigned int pool_size_y = is_global_pooling ? input->tensor_shape().y() : pool_info.pool_size().height; - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_global_pooling && ((pool_info.pad_stride_info().pad().first >= pool_size_x) || (pool_info.pad_stride_info().pad().second >= pool_size_y)), - "Invalid pool size and pool pad combination!"); - // Checks performed when output is configured if(output->total_size() != 0) { @@ -92,8 +88,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const PoolingLayerInfo &pool_info) { - int pool_pad_x = 0; - int pool_pad_y = 0; int pool_stride_x = 0; int pool_stride_y = 0; unsigned int pooled_w = 0; @@ -101,8 +95,11 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso int pool_size_x = pool_info.is_global_pooling() ? input->dimension(0) : pool_info.pool_size().width; int pool_size_y = pool_info.is_global_pooling() ? input->dimension(1) : pool_info.pool_size().height; const PadStrideInfo pad_stride_info = pool_info.pad_stride_info(); - std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad(); std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); + const int pool_pad_right = pad_stride_info.pad_right(); + const int pool_pad_top = pad_stride_info.pad_top(); + const int pool_pad_left = pad_stride_info.pad_left(); + const int pool_pad_bottom = pad_stride_info.pad_bottom(); ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); @@ -115,7 +112,7 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso auto_init(input, output, pooled_w, pooled_h); - BorderSize border_size = BorderSize(pool_pad_y, pool_pad_x); + BorderSize border_size = BorderSize(pool_pad_top, pool_pad_right, pool_pad_bottom, pool_pad_left); const DataType data_type = input->data_type(); const int input_width = input->dimension(0); @@ -131,15 +128,15 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso const int num_iterations_x = (pooled_w + num_elems_processed_per_iteration - 1) / num_elems_processed_per_iteration; // Upper limit for the number of right/bottom border elements that are accessed - const int upper_bound_w = ((num_iterations_x - 1) * num_elems_processed_per_iteration * pool_stride_x - pool_pad_x + num_elems_read_per_iteration) - input_width; - const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_y + pool_size_y) - input_height; + const int upper_bound_w = ((num_iterations_x - 1) * num_elems_processed_per_iteration * pool_stride_x - pool_pad_left + num_elems_read_per_iteration) - input_width; + const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_top + pool_size_y) - input_height; - border_size.right = std::max(upper_bound_w, pool_pad_x); - border_size.bottom = std::max(upper_bound_h, pool_pad_y); + border_size.right = std::max(upper_bound_w, pool_pad_right); + border_size.bottom = std::max(upper_bound_h, pool_pad_bottom); Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); - AccessWindowRectangle input_access(input, -pool_pad_x, -pool_pad_y, num_elems_read_per_iteration, pool_size_y, + AccessWindowRectangle input_access(input, -pool_pad_left, -pool_pad_top, num_elems_read_per_iteration, pool_size_y, pool_stride_x * num_elems_processed_per_iteration, pool_stride_y); AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); bool window_changed = update_window_and_padding(win, input_access, output_access); @@ -162,8 +159,6 @@ BorderSize CLPoolingLayerKernel::border_size() const void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info) { - int pool_pad_x = 0; - int pool_pad_y = 0; int pool_stride_x = 0; int pool_stride_y = 0; unsigned int pooled_w = 0; @@ -173,8 +168,9 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const int pool_size_y = pool_info.is_global_pooling() ? input->info()->dimension(1) : pool_info.pool_size().height; const PadStrideInfo pad_stride_info = pool_info.pad_stride_info(); const bool exclude_padding = pool_info.exclude_padding(); - std::tie(pool_pad_x, pool_pad_y) = pad_stride_info.pad(); std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); + const int pool_pad_top = pad_stride_info.pad_top(); + const int pool_pad_left = pad_stride_info.pad_left(); ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); @@ -207,11 +203,11 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, if(pool_type != PoolingType::MAX) { build_opts.add_option_if(exclude_padding, "-DEXCLUDE_PADDING"); - build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_x))); - build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_y))); + build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(input->info()->dimension(0) + (exclude_padding ? 0 : pool_pad_left))); + build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1) + (exclude_padding ? 0 : pool_pad_top))); build_opts.add_option("-DSTRIDE_Y=" + support::cpp11::to_string(pool_stride_y)); - build_opts.add_option("-DPAD_X=" + support::cpp11::to_string(pool_pad_x)); - build_opts.add_option("-DPAD_Y=" + support::cpp11::to_string(pool_pad_y)); + build_opts.add_option("-DPAD_X=" + support::cpp11::to_string(pool_pad_left)); + build_opts.add_option("-DPAD_Y=" + support::cpp11::to_string(pool_pad_top)); } // Create kernel @@ -278,8 +274,8 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue) ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); - unsigned int pool_pad_x, pool_pad_y, pool_stride_x, pool_stride_y = 0; - std::tie(pool_pad_x, pool_pad_y) = _pool_info.pad_stride_info().pad(); + unsigned int pool_stride_x = 0; + unsigned int pool_stride_y = 0; std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride(); Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); @@ -289,11 +285,11 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue) { // Upsample input by pool size Window in_slice(slice); - in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start() - pool_pad_x, - (in_slice.x().end() - pool_pad_x) * pool_stride_x, + in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start() - _pool_info.pad_stride_info().pad_left(), + (in_slice.x().end() - _pool_info.pad_stride_info().pad_left()) * pool_stride_x, pool_stride_x * _num_elems_processed_per_iteration)); - in_slice.set(Window::DimY, Window::Dimension(in_slice.y().start() - pool_pad_y, - (in_slice.y().end() - pool_pad_y) * pool_stride_y, + in_slice.set(Window::DimY, Window::Dimension(in_slice.y().start() - _pool_info.pad_stride_info().pad_top(), + (in_slice.y().end() - _pool_info.pad_stride_info().pad_top()) * pool_stride_y, pool_stride_y)); // Set inputs diff --git a/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp b/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp index 536a667799..4dc186a8a7 100644 --- a/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp +++ b/src/core/NEON/kernels/NEDirectConvolutionLayerKernel.cpp @@ -274,6 +274,7 @@ public: ARM_COMPUTE_ERROR_ON(input->info()->dimension(Window::DimX) > small_tensor_size_optim); ARM_COMPUTE_ERROR_ON(input->info()->dimension(Window::DimY) > small_tensor_size_optim); + const int input_stride_x = input->info()->strides_in_bytes().x(); const int input_stride_y = input->info()->strides_in_bytes().y(); const int input_stride_z = input->info()->strides_in_bytes().z(); const int output_stride_y = output->info()->strides_in_bytes().y(); @@ -284,6 +285,8 @@ public: const int range_z = window.z().end() - window.z().start(); const int kernel_depth = weights->info()->dimension(Window::DimZ); const unsigned int conv_stride_y = std::get<1>(conv_info.stride()); + const unsigned int conv_pad_left = conv_info.pad_left(); + const unsigned int conv_pad_top = conv_info.pad_top(); // setup output window for the iterator Window window_out = window; @@ -307,7 +310,7 @@ public: execute_window_loop(window_out, [&](const Coordinates & id) { - const uint8_t *input_ptr = in.ptr(); + const uint8_t *input_ptr = in.ptr() - conv_pad_left * input_stride_x - conv_pad_top * input_stride_y; uint8_t *out_ptr = out.ptr(); int ih = 0; int oh = 0; @@ -351,6 +354,7 @@ public: static void convolve(const Window &window, unsigned int num_elems_read_per_iteration, unsigned int num_elems_written_per_iteration, const ITensor *input, const ITensor *weights, ITensor *output, const PadStrideInfo &conv_info) { + const int input_stride_x = input->info()->strides_in_bytes().x(); const int input_stride_y = input->info()->strides_in_bytes().y(); const int input_stride_z = input->info()->strides_in_bytes().z(); const int output_stride_y = output->info()->strides_in_bytes().y(); @@ -362,6 +366,8 @@ public: const int range_z = window.z().end() - window.z().start(); const int kernel_depth = weights->info()->dimension(Window::DimZ); const unsigned int conv_stride_y = std::get<1>(conv_info.stride()); + const unsigned int conv_pad_left = conv_info.pad_left(); + const unsigned int conv_pad_top = conv_info.pad_top(); const int fixed_point_position = input->info()->fixed_point_position(); // setup output window for the iterator @@ -389,7 +395,7 @@ public: /* For a detailed explanation on how the algorithm works refer to template <> class convolver_3x3<1> */ - const uint8_t *input_ptr = in.ptr(); + const uint8_t *input_ptr = in.ptr() - conv_pad_left * input_stride_x - conv_pad_top * input_stride_y; uint8_t *out_ptr = out.ptr(); int ih = 0; int oh = 0; @@ -680,8 +686,8 @@ public: const int delta_input = get_input_num_elems_processed<stridex>(num_elems_written_per_iteration); const int kernel_depth = weights->info()->dimension(Window::DimZ); const unsigned int conv_stride_y = std::get<1>(conv_info.stride()); - const unsigned int conv_pad_x = std::get<0>(conv_info.pad()); - const unsigned int conv_pad_y = std::get<1>(conv_info.pad()); + const unsigned int conv_pad_left = conv_info.pad_left(); + const unsigned int conv_pad_top = conv_info.pad_top(); const int fixed_point_position = input->info()->fixed_point_position(); // setup output window for the iterator @@ -707,7 +713,7 @@ public: execute_window_loop(window_out, [&](const Coordinates & id) { - const uint8_t *input_ptr = in.ptr() - conv_pad_x * input_stride_x - conv_pad_y * input_stride_y; + const uint8_t *input_ptr = in.ptr() - conv_pad_left * input_stride_x - conv_pad_top * input_stride_y; uint8_t *out_ptr = out.ptr(); int ih = 0; int oh = 0; @@ -804,8 +810,8 @@ public: const int delta_input = get_input_num_elems_processed<stridex>(num_elems_written_per_iteration); const int kernel_depth = weights->info()->dimension(Window::DimZ); const unsigned int conv_stride_y = std::get<1>(conv_info.stride()); - const unsigned int conv_pad_x = std::get<0>(conv_info.pad()); - const unsigned int conv_pad_y = std::get<1>(conv_info.pad()); + const unsigned int conv_pad_left = conv_info.pad_left(); + const unsigned int conv_pad_top = conv_info.pad_top(); const int fixed_point_position = input->info()->fixed_point_position(); // setup output window for the iterator @@ -831,7 +837,7 @@ public: execute_window_loop(window_out, [&](const Coordinates & id) { - const uint8_t *input_ptr = in.ptr() - conv_pad_x * input_stride_x - conv_pad_y * input_stride_y; + const uint8_t *input_ptr = in.ptr() - conv_pad_left * input_stride_x - conv_pad_top * input_stride_y; uint8_t *out_ptr = out.ptr(); int ih = 0; int oh = 0; @@ -1016,13 +1022,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - ARM_COMPUTE_RETURN_ERROR_ON(!conv_info.padding_is_symmetric()); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(0) == 1 && (std::get<0>(conv_info.pad()) || std::get<1>(conv_info.pad())), - "Pad > 0 not supported for 1x1 weights"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(0) == 3 && (std::get<0>(conv_info.pad()) > 1 || std::get<1>(conv_info.pad()) > 1), - "Pad > 1 not supported for 3x3 weights"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(0) == 5 && (std::get<0>(conv_info.pad()) > 2 || std::get<1>(conv_info.pad()) > 2), - "Pad > 2 not supported for 5x5 weights"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported."); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(2) != input->dimension(2)); @@ -1204,7 +1203,7 @@ Status NEDirectConvolutionLayerKernel::validate(const ITensorInfo *input, const unsigned int num_weight_elems_read_per_row = 0; unsigned int num_elems_read_per_iteration = 0; unsigned int num_elems_written_per_iteration = 0; - BorderSize border_size(conv_info.pad().first, conv_info.pad().second); + BorderSize border_size = {}; ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, output, conv_info)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), diff --git a/tests/datasets/DepthwiseConvolutionLayerDataset.h b/tests/datasets/DepthwiseConvolutionLayerDataset.h index 629217a8a8..b8a16a7c3d 100644 --- a/tests/datasets/DepthwiseConvolutionLayerDataset.h +++ b/tests/datasets/DepthwiseConvolutionLayerDataset.h @@ -159,6 +159,9 @@ public: add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(11U, 14U, 11U), PadStrideInfo(3, 2, 1, 1)); add_config(TensorShape(21U, 31U, 9U, 4U), TensorShape(3U, 3U, 9U), TensorShape(21U, 15U, 9U, 4U), PadStrideInfo(1, 2, 1, 0)); add_config(TensorShape(33U, 27U, 11U, 3U), TensorShape(3U, 3U, 11U), TensorShape(31U, 14U, 11U, 3U), PadStrideInfo(1, 2, 0, 1)); + // Asymmetric padding + add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(16U, 13U, 11U), PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR)); + add_config(TensorShape(33U, 27U, 11U), TensorShape(3U, 3U, 11U), TensorShape(18U, 14U, 11U), PadStrideInfo(2, 2, 3, 1, 2, 1, DimensionRoundingType::FLOOR)); } }; diff --git a/tests/datasets/PoolingLayerDataset.h b/tests/datasets/PoolingLayerDataset.h index 56ec3b87d8..53e392fe69 100644 --- a/tests/datasets/PoolingLayerDataset.h +++ b/tests/datasets/PoolingLayerDataset.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -105,6 +105,19 @@ private: std::vector<TensorShape> _dst_shapes{}; std::vector<PoolingLayerInfo> _infos{}; }; + +// Special pooling dataset +class PoolingLayerDatasetSpecial final : public PoolingLayerDataset +{ +public: + PoolingLayerDatasetSpecial() + { + // Special cases + add_config(TensorShape(60U, 52U, 3U, 2U), TensorShape(13U, 11U, 32U), PoolingLayerInfo(PoolingType::AVG, Size2D(100, 100), PadStrideInfo(5, 5, 50, 50), true)); + // Asymmetric padding + add_config(TensorShape(112U, 112U, 32U), TensorShape(56U, 56U, 32U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR))); + } +}; } // namespace datasets } // namespace test } // namespace arm_compute diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp index 4af825e526..bf8b4057ee 100644 --- a/tests/validation/CL/DirectConvolutionLayer.cpp +++ b/tests/validation/CL/DirectConvolutionLayer.cpp @@ -56,8 +56,8 @@ constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for qu const auto data = combine(datasets::SmallDirectConvolutionShapes(), combine(framework::dataset::make("StrideX", 1, 3), combine(framework::dataset::make("StrideY", 1, 3), - combine(concat(combine(framework::dataset::make("PadX", 0), - combine(framework::dataset::make("PadY", 0), + combine(concat(combine(framework::dataset::make("PadX", 0, 1), + combine(framework::dataset::make("PadY", 0, 1), framework::dataset::make("KernelSize", 1))), combine(framework::dataset::make("PadX", 0, 2), combine(framework::dataset::make("PadY", 0, 2), diff --git a/tests/validation/CL/PoolingLayer.cpp b/tests/validation/CL/PoolingLayer.cpp index dc9604423f..9da4c55c78 100644 --- a/tests/validation/CL/PoolingLayer.cpp +++ b/tests/validation/CL/PoolingLayer.cpp @@ -27,6 +27,7 @@ #include "arm_compute/runtime/CL/functions/CLPoolingLayer.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" +#include "tests/datasets/PoolingLayerDataset.h" #include "tests/datasets/PoolingTypesDataset.h" #include "tests/datasets/ShapeDatasets.h" #include "tests/framework/Asserts.h" @@ -43,12 +44,6 @@ namespace validation { namespace { -/** Failing data set */ -const auto PoolingLayerDatasetSpecial = ((((framework::dataset::make("Shape", TensorShape{ 60U, 52U, 3U, 5U }) - * framework::dataset::make("PoolType", PoolingType::AVG)) - * framework::dataset::make("PoolingSize", Size2D(100, 100))) - * framework::dataset::make("PadStride", PadStrideInfo(5, 5, 50, 50))) - * framework::dataset::make("ExcludePadding", true)); /** Input data set for floating-point data types */ const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3), Size2D(7, 7), Size2D(9, 9), Size2D(5, 7), Size2D(7, 9) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), @@ -121,9 +116,12 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( template <typename T> using CLPoolingLayerFixture = PoolingLayerValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>; +template <typename T> +using CLSpecialPoolingLayerFixture = SpecialPoolingLayerValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>; + TEST_SUITE(Float) TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSpecial, CLPoolingLayerFixture<float>, framework::DatasetMode::ALL, PoolingLayerDatasetSpecial * framework::dataset::make("DataType", DataType::F32)) +FIXTURE_DATA_TEST_CASE(RunSpecial, CLSpecialPoolingLayerFixture<float>, framework::DatasetMode::ALL, datasets::PoolingLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp index f51752d946..57e030c349 100644 --- a/tests/validation/NEON/DirectConvolutionLayer.cpp +++ b/tests/validation/NEON/DirectConvolutionLayer.cpp @@ -49,8 +49,8 @@ constexpr AbsoluteTolerance<float> tolerance_fp16(0.01f); /**< Tolerance for ha constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ /** Direct convolution data set. */ -const auto data_pad_f32 = concat(concat(combine(framework::dataset::make("PadX", 0), - combine(framework::dataset::make("PadY", 0), +const auto data_pad_f32 = concat(concat(combine(framework::dataset::make("PadX", 0, 1), + combine(framework::dataset::make("PadY", 0, 1), framework::dataset::make("KernelSize", 1))), combine(framework::dataset::make("PadX", 0, 2), combine(framework::dataset::make("PadY", 0, 2), diff --git a/tests/validation/NEON/PoolingLayer.cpp b/tests/validation/NEON/PoolingLayer.cpp index 4697d4db01..350a7b883b 100644 --- a/tests/validation/NEON/PoolingLayer.cpp +++ b/tests/validation/NEON/PoolingLayer.cpp @@ -27,6 +27,7 @@ #include "arm_compute/runtime/TensorAllocator.h" #include "tests/NEON/Accessor.h" #include "tests/PaddingCalculator.h" +#include "tests/datasets/PoolingLayerDataset.h" #include "tests/datasets/PoolingTypesDataset.h" #include "tests/datasets/ShapeDatasets.h" #include "tests/framework/Asserts.h" @@ -119,8 +120,16 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( template <typename T> using NEPoolingLayerFixture = PoolingLayerValidationFixture<Tensor, Accessor, NEPoolingLayer, T>; +template <typename T> +using NESpecialPoolingLayerFixture = SpecialPoolingLayerValidationFixture<Tensor, Accessor, NEPoolingLayer, T>; + TEST_SUITE(Float) TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSpecial, NESpecialPoolingLayerFixture<float>, framework::DatasetMode::ALL, datasets::PoolingLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f32); +} FIXTURE_DATA_TEST_CASE(RunSmall, NEPoolingLayerFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFP, framework::dataset::make("DataType", DataType::F32)))) { diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h index f101199365..3bbb403ae7 100644 --- a/tests/validation/fixtures/PoolingLayerFixture.h +++ b/tests/validation/fixtures/PoolingLayerFixture.h @@ -164,6 +164,18 @@ public: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class SpecialPoolingLayerValidationFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape src_shape, TensorShape dst_shape, PoolingLayerInfo pool_info, DataType data_type) + { + ARM_COMPUTE_UNUSED(dst_shape); + PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(src_shape, pool_info, data_type, 0, QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> class GlobalPoolingLayerValidationFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: @@ -173,6 +185,7 @@ public: PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type), data_type, 0, QuantizationInfo()); } }; + } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/reference/DepthwiseConvolutionLayer.cpp b/tests/validation/reference/DepthwiseConvolutionLayer.cpp index ffea1bcf89..b2a7067709 100644 --- a/tests/validation/reference/DepthwiseConvolutionLayer.cpp +++ b/tests/validation/reference/DepthwiseConvolutionLayer.cpp @@ -143,10 +143,10 @@ SimpleTensor<uint8_t> depthwise_convolution(const SimpleTensor<uint8_t> &src, co const int filter_half_width = filter_width / 2; const int filter_half_height = filter_height / 2; - const int pad_left = std::min(static_cast<int>(conv_info.pad_left()), filter_half_width); - const int pad_top = std::min(static_cast<int>(conv_info.pad_top()), filter_half_height); - const int pad_right = std::min(static_cast<int>(conv_info.pad_right()), filter_half_width); - const int pad_bottom = std::min(static_cast<int>(conv_info.pad_bottom()), filter_half_height); + const int pad_left = conv_info.pad_left(); + const int pad_top = conv_info.pad_top(); + const int pad_right = conv_info.pad_right(); + const int pad_bottom = conv_info.pad_bottom(); const int minimum_x = -pad_left + filter_half_width; const int minimum_y = -pad_top + filter_half_height; |