diff options
Diffstat (limited to 'src/core')
| -rw-r--r-- | src/core/CL/CLKernels.h | 1 | ||||
| -rw-r--r-- | src/core/CL/kernels/CLDirectConvolutionLayerKernel.h | 126 | ||||
| -rw-r--r-- | src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp (renamed from src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp) | 250 | ||||
| -rw-r--r-- | src/core/gpu/cl/kernels/ClDirectConvolutionKernel.h | 97 | ||||
| -rw-r--r-- | src/core/gpu/cl/kernels/ClScaleKernel.cpp | 23 | ||||
| -rw-r--r-- | src/core/gpu/cl/kernels/ClScaleKernel.h | 23 |
6 files changed, 233 insertions, 287 deletions
diff --git a/src/core/CL/CLKernels.h b/src/core/CL/CLKernels.h index 0ec573c1a6..eaac415bc4 100644 --- a/src/core/CL/CLKernels.h +++ b/src/core/CL/CLKernels.h @@ -42,7 +42,6 @@ #include "src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h" #include "src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h" #include "src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h" -#include "src/core/CL/kernels/CLDirectConvolutionLayerKernel.h" #include "src/core/CL/kernels/CLFFTDigitReverseKernel.h" #include "src/core/CL/kernels/CLFFTRadixStageKernel.h" #include "src/core/CL/kernels/CLFFTScaleKernel.h" diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.h b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.h deleted file mode 100644 index 0257d0c2dd..0000000000 --- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.h +++ /dev/null @@ -1,126 +0,0 @@ -/* - * Copyright (c) 2017-2021 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. - */ -#ifndef ARM_COMPUTE_CLDIRECTCONVOLUTIONLAYERKERNEL_H -#define ARM_COMPUTE_CLDIRECTCONVOLUTIONLAYERKERNEL_H - -#include "arm_compute/core/Types.h" -#include "src/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** Interface for the direct convolution kernel. - */ -class CLDirectConvolutionLayerKernel : public ICLKernel -{ -public: - /** Default constructor */ - CLDirectConvolutionLayerKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDirectConvolutionLayerKernel(const CLDirectConvolutionLayerKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDirectConvolutionLayerKernel &operator=(const CLDirectConvolutionLayerKernel &) = delete; - /** Allow instances of this class to be moved */ - CLDirectConvolutionLayerKernel(CLDirectConvolutionLayerKernel &&) = default; - /** Allow instances of this class to be moved */ - CLDirectConvolutionLayerKernel &operator=(CLDirectConvolutionLayerKernel &&) = default; - /** Default destructor */ - ~CLDirectConvolutionLayerKernel() = default; - /** Set the input, weights, biases and output tensors. - * - * @note: DirectConvolution only works in the following configurations: - * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 - * 3x3 convolution with stride_x = 1/2, stride_y = 1/2 - * 5x5 convolution with stride_x = 1/2, stride_y = 1/2 - * 9x9 convolution with stride_x = 1/2, stride_y = 1/2 - * - * @param[in] input The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM], - * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * The 3rd dimension must be the same as the input's volume 3rd dimension. - * Data type supported:Same as @p input. - * @param[in] biases Biases tensor. Biases are 1D tensor with dimension [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type - * @param[out] output Output tensor. - * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input. - * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. - */ - void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info); - /** Set the input, weights, biases and output tensors. - * - * @note: DirectConvolution only works in the following configurations: - * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 - * 3x3 convolution with stride_x = 1/2, stride_y = 1/2 - * 5x5 convolution with stride_x = 1/2, stride_y = 1/2 - * 9x9 convolution with stride_x = 1/2, stride_y = 1/2 - * - * @param[in] compile_context The compile context to be used. - * @param[in] input The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM], - * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * The 3rd dimension must be the same as the input's volume 3rd dimension. - * Data type supported:Same as @p input. - * @param[in] biases Biases tensor. Biases are 1D tensor with dimension [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type - * @param[out] output Output tensor. - * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input. - * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info); - /** Static function to check if given info will lead to a valid configuration of @ref CLDirectConvolutionLayerKernel - * - * @param[in] input The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM], - * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * The 3rd dimension must be the same as the input's volume 3rd dimension. - * Data type supported:Same as @p input. - * @param[in] biases Biases tensor. Biases are 1D tensor with dimension [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type. - * @param[in] output Output tensor. - * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input. - * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. - * @param[in] target Target GPU architecture. - * - * @return a status - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const GPUTarget target); - - // Inherited methods overridden: - void run(const Window &window, cl::CommandQueue &queue) override; - BorderSize border_size() const override; - -public: - const ICLTensor *_input; - const ICLTensor *_biases; - const ICLTensor *_weights; - ICLTensor *_output; - DataLayout _data_layout; - BorderSize _border_size; - int _conv_stride_x; - int _conv_stride_y; - PadStrideInfo _conv_info; -}; -} // namespace arm_compute -#endif /*ARM_COMPUTE_CLDIRECTCONVOLUTIONLAYERKERNEL_H */ diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp index 2fc3c60f67..f071dbc468 100644 --- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp +++ b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp @@ -21,7 +21,7 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "src/core/CL/kernels/CLDirectConvolutionLayerKernel.h" +#include "src/core/gpu/cl/kernels/ClDirectConvolutionKernel.h" #include "arm_compute/core/CL/CLHelpers.h" #include "arm_compute/core/CL/CLKernelLibrary.h" @@ -36,26 +36,31 @@ #include "src/core/CL/CLValidate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" +#include "support/Cast.h" #include "support/StringSupport.h" namespace arm_compute { +namespace opencl +{ +namespace kernels +{ namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info) +Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info) { - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8_SIGNED, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8_SIGNED, DataType::QASYMM8, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, weights); - const DataLayout data_layout = input->data_layout(); + const DataLayout data_layout = src->data_layout(); const int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); const int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(width_idx) != weights->dimension(height_idx), "Weights should have same width and height"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(channel_idx) != input->dimension(channel_idx), - "Weights feature map dimension should match the respective input's one"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(channel_idx) != src->dimension(channel_idx), + "Weights feature map dimension should match the respective src's one"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->num_dimensions() > 4, "Weights can be at most 4 dimensional"); ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 1) && std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported for 1x1 convolution."); ARM_COMPUTE_RETURN_ERROR_ON_MSG((weights->dimension(width_idx) == 3 || weights->dimension(width_idx) == 5 || weights->dimension(width_idx) == 9) @@ -64,7 +69,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, if(data_layout == DataLayout::NCHW) { - if(is_data_type_quantized(input->data_type())) + if(is_data_type_quantized(src->data_type())) { ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(width_idx) != 1 && weights->dimension(width_idx) != 3 && weights->dimension(width_idx) != 5 && weights->dimension(width_idx) != 9, "Kernel sizes other than 1x1, 3x3, 5x5 or 9x9 are not supported with quantized data types"); @@ -78,7 +83,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, if(biases != nullptr) { - if(is_data_type_quantized_asymmetric(input->data_type())) + if(is_data_type_quantized_asymmetric(src->data_type())) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); } @@ -87,25 +92,25 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); } ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->dimension(0) != weights->dimension(3), - "Biases size and number of input feature maps should match"); + "Biases size and number of src feature maps should match"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->num_dimensions() > 1, "Biases should be one dimensional"); } - // Checks performed when output is configured - if(output->total_size() != 0) + // Checks performed when dst is configured + if(dst->total_size() != 0) { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), - misc::shape_calculator::compute_deep_convolution_shape(*input, *weights, conv_info)); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), + misc::shape_calculator::compute_deep_convolution_shape(*src, *weights, conv_info)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); } - const auto data_type = input->data_type(); + const auto data_type = src->data_type(); if(is_data_type_quantized(data_type)) { - const UniformQuantizationInfo iqinfo = input->quantization_info().uniform(); + const UniformQuantizationInfo iqinfo = src->quantization_info().uniform(); const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform(); - const UniformQuantizationInfo oqinfo = output->quantization_info().uniform(); + const UniformQuantizationInfo oqinfo = dst->quantization_info().uniform(); float multiplier = iqinfo.scale * wqinfo.scale / oqinfo.scale; int output_multiplier = 0; @@ -130,10 +135,10 @@ inline bool can_run_optimized_kernel_for_bifrost_nchw(GPUTarget gpu_target, unsi inline void setup_num_elems_nchw(unsigned int &num_elems_read_per_iteration_x, unsigned int &num_elems_read_per_iteration_y, unsigned int &num_elems_written_per_iteration_x, unsigned int &num_elems_written_per_iteration_y, - unsigned int kernel_size, const PadStrideInfo &conv_info, const GPUTarget target, ITensorInfo *input) + unsigned int kernel_size, const PadStrideInfo &conv_info, const GPUTarget target, ITensorInfo *src) { - const DataType data_type = input->data_type(); - const DataLayout data_layout = input->data_layout(); + const DataType data_type = src->data_type(); + const DataLayout data_layout = src->data_layout(); unsigned int conv_stride_x = std::get<0>(conv_info.stride()); unsigned int conv_stride_y = std::get<1>(conv_info.stride()); @@ -191,7 +196,7 @@ inline void setup_num_elems_nchw(unsigned int &num_elems_read_per_iteration_x, u num_elems_read_per_iteration_x = 16; break; case 3: - switch(input->element_size()) + switch(src->element_size()) { case 1: num_elems_read_per_iteration_x = 28; @@ -255,26 +260,26 @@ inline void setup_num_elems_nchw(unsigned int &num_elems_read_per_iteration_x, u } } -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, const GPUTarget target) +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, ITensorInfo *weights, ITensorInfo *dst, const PadStrideInfo &conv_info, const GPUTarget target) { - const DataLayout data_layout = input->data_layout(); + const DataLayout data_layout = src->data_layout(); - // Get output shape - TensorShape output_shape = misc::shape_calculator::compute_deep_convolution_shape(*input, *weights, conv_info); + // Get dst shape + TensorShape output_shape = misc::shape_calculator::compute_deep_convolution_shape(*src, *weights, conv_info); // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output, output_shape, + auto_init_if_empty(*dst, output_shape, 1, - input->data_type(), - input->quantization_info()); + src->data_type(), + src->quantization_info()); if(data_layout == DataLayout::NHWC) { - const unsigned int vec_size = std::min(static_cast<unsigned int>(output->tensor_shape()[0]), 4u); + const unsigned int vec_size = std::min(static_cast<unsigned int>(dst->tensor_shape()[0]), 4u); // Create window and update padding - Window win = calculate_max_window(*output, Steps(vec_size, 1U)); - output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape())); + Window win = calculate_max_window(*dst, Steps(vec_size, 1U)); + dst->set_valid_region(ValidRegion(Coordinates(), dst->tensor_shape())); Status err = Status{}; return std::make_pair(err, win); } @@ -295,17 +300,17 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen setup_num_elems_nchw(num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y, - kernel_size, conv_info, target, input); + kernel_size, conv_info, target, src); // Create window and update padding bool window_changed = false; - Window win = calculate_max_window(*output, Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y)); + Window win = calculate_max_window(*dst, Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y)); - AccessWindowRectangle input_access(input, -conv_pad_left, -conv_pad_top, num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, conv_stride_x, conv_stride_y); + AccessWindowRectangle input_access(src, -conv_pad_left, -conv_pad_top, num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, conv_stride_x, conv_stride_y); AccessWindowStatic weights_access(weights, 0, 0, kernel_size, kernel_size); - AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y); + AccessWindowRectangle output_access(dst, 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y); window_changed = update_window_and_padding(win, input_access, weights_access, output_access); - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + output_access.set_valid_region(win, ValidRegion(Coordinates(), dst->tensor_shape())); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } @@ -316,52 +321,39 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen } } // namespace -CLDirectConvolutionLayerKernel::CLDirectConvolutionLayerKernel() - : _input(nullptr), _biases(nullptr), _weights(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _border_size(0), _conv_stride_x(0), _conv_stride_y(0), _conv_info() -{ -} - -BorderSize CLDirectConvolutionLayerKernel::border_size() const +BorderSize ClDirectConvolutionKernel::border_size() const { return _border_size; } -void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info) +void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *dst, + const PadStrideInfo &conv_info) { - configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info); -} - -void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const PadStrideInfo &conv_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + ARM_COMPUTE_ERROR_ON_NULLPTR(src, weights, dst); // Perform validation - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), - weights->info(), - (biases != nullptr) ? biases->info() : nullptr, - output->info(), + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, + weights, + (biases != nullptr) ? biases : nullptr, + dst, conv_info)); - _conv_stride_x = std::get<0>(conv_info.stride()); - _conv_stride_y = std::get<1>(conv_info.stride()); - _data_layout = input->info()->data_layout(); - _input = input; - _weights = weights; - _output = output; - _biases = biases; - _conv_info = conv_info; + const int conv_stride_x = std::get<0>(conv_info.stride()); + const int conv_stride_y = std::get<1>(conv_info.stride()); + + _data_layout = src->data_layout(); + _conv_info = conv_info; const unsigned int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); const unsigned int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); const unsigned int channel_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL); - const unsigned int kernel_size = weights->info()->dimension(width_idx); - const DataType data_type = input->info()->data_type(); + const unsigned int kernel_size = weights->dimension(width_idx); + const DataType data_type = src->data_type(); const GPUTarget gpu_target = get_target(); // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, gpu_target); + auto win_config = validate_and_configure_window(src, weights, dst, conv_info, gpu_target); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); @@ -376,30 +368,30 @@ void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_c const unsigned int n0 = win_config.second.x().step(); const unsigned int m0 = win_config.second.y().step(); - const unsigned int k0 = adjust_vec_size(16u, _input->info()->dimension(channel_idx)); - const unsigned int partial_store_n0 = _output->info()->dimension(channel_idx) % n0; - const unsigned int partial_store_m0 = (_output->info()->dimension(width_idx) * _output->info()->dimension(height_idx)) % m0; + const unsigned int k0 = adjust_vec_size(16u, src->dimension(channel_idx)); + const unsigned int partial_store_n0 = dst->dimension(channel_idx) % n0; + const unsigned int partial_store_m0 = (dst->dimension(width_idx) * dst->dimension(height_idx)) % m0; const unsigned int pad_left = conv_info.pad_left(); const unsigned int pad_top = conv_info.pad_top(); - if(_biases != nullptr) + if(biases != nullptr) { build_options.add_option(std::string("-DHAS_BIAS")); - build_options.add_option(std::string("-DBIA_DATA_TYPE=" + get_cl_type_from_data_type(_biases->info()->data_type()))); + build_options.add_option(std::string("-DBIA_DATA_TYPE=" + get_cl_type_from_data_type(biases->data_type()))); } - build_options.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(_input->info()->dimension(width_idx))); - build_options.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(_input->info()->dimension(height_idx))); - build_options.add_option("-DSRC_CHANNELS=" + support::cpp11::to_string(_input->info()->dimension(channel_idx))); - build_options.add_option("-DSRC_DATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type())); - build_options.add_option("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(width_idx))); - build_options.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(_output->info()->dimension(height_idx))); - build_options.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(_output->info()->dimension(channel_idx))); - build_options.add_option("-DDST_DATA_TYPE=" + get_cl_type_from_data_type(_output->info()->data_type())); - build_options.add_option("-DWEI_WIDTH=" + support::cpp11::to_string(_weights->info()->dimension(width_idx))); - build_options.add_option("-DWEI_HEIGHT=" + support::cpp11::to_string(_weights->info()->dimension(height_idx))); - build_options.add_option("-DWEI_DATA_TYPE=" + get_cl_type_from_data_type(_weights->info()->data_type())); - build_options.add_option("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x)); - build_options.add_option("-DSTRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); + build_options.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(width_idx))); + build_options.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(height_idx))); + build_options.add_option("-DSRC_CHANNELS=" + support::cpp11::to_string(src->dimension(channel_idx))); + build_options.add_option("-DSRC_DATA_TYPE=" + get_cl_type_from_data_type(src->data_type())); + build_options.add_option("-DDST_WIDTH=" + support::cpp11::to_string(dst->dimension(width_idx))); + build_options.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(dst->dimension(height_idx))); + build_options.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(dst->dimension(channel_idx))); + build_options.add_option("-DDST_DATA_TYPE=" + get_cl_type_from_data_type(dst->data_type())); + build_options.add_option("-DWEI_WIDTH=" + support::cpp11::to_string(weights->dimension(width_idx))); + build_options.add_option("-DWEI_HEIGHT=" + support::cpp11::to_string(weights->dimension(height_idx))); + build_options.add_option("-DWEI_DATA_TYPE=" + get_cl_type_from_data_type(weights->data_type())); + build_options.add_option("-DSTRIDE_X=" + support::cpp11::to_string(conv_stride_x)); + build_options.add_option("-DSTRIDE_Y=" + support::cpp11::to_string(conv_stride_y)); build_options.add_option("-DPAD_LEFT=" + support::cpp11::to_string(pad_left)); build_options.add_option("-DPAD_TOP=" + support::cpp11::to_string(pad_top)); build_options.add_option("-DN0=" + support::cpp11::to_string(n0)); @@ -410,11 +402,11 @@ void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_c if(is_data_type_quantized(data_type)) { - const UniformQuantizationInfo iqinfo = _input->info()->quantization_info().uniform(); - const UniformQuantizationInfo wqinfo = _weights->info()->quantization_info().uniform(); - const UniformQuantizationInfo oqinfo = _output->info()->quantization_info().uniform(); + const UniformQuantizationInfo iqinfo = src->quantization_info().uniform(); + const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform(); + const UniformQuantizationInfo oqinfo = dst->quantization_info().uniform(); - PixelValue zero_value = PixelValue(0, input->info()->data_type(), input->info()->quantization_info()); + PixelValue zero_value = PixelValue(0, src->data_type(), src->quantization_info()); int zero_value_s32; zero_value.get(zero_value_s32); @@ -441,17 +433,17 @@ void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_c } else { - _border_size = BorderSize(_input->info()->padding()); + _border_size = BorderSize(src->padding()); kernel_name << "direct_convolution" << kernel_size << "x" << kernel_size; - build_options.add_option_if(_biases != nullptr, std::string("-DHAS_BIAS")); + build_options.add_option_if(biases != nullptr, std::string("-DHAS_BIAS")); - const bool run_optimized_for_bifrost = can_run_optimized_kernel_for_bifrost_nchw(gpu_target, _conv_stride_x, _conv_stride_y, kernel_size, data_type, _data_layout); + const bool run_optimized_for_bifrost = can_run_optimized_kernel_for_bifrost_nchw(gpu_target, conv_stride_x, conv_stride_y, kernel_size, data_type, _data_layout); if(run_optimized_for_bifrost) { - build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(channel_idx)))); + build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(weights->dimension(channel_idx)))); kernel_name << "_f32_bifrost"; } @@ -459,15 +451,15 @@ void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_c { build_options.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type))); build_options.add_option(std::string("-DDATA_SIZE=" + get_data_size_from_data_type(data_type))); - build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(channel_idx)))); - build_options.add_option(std::string("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x))); + build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(weights->dimension(channel_idx)))); + build_options.add_option(std::string("-DSTRIDE_X=" + support::cpp11::to_string(conv_stride_x))); build_options.add_option(std::string("-DDATA_TYPE_PROMOTED=" + get_cl_type_from_data_type(data_type))); if(is_data_type_quantized(data_type)) { - const UniformQuantizationInfo iqinfo = _input->info()->quantization_info().uniform(); - const UniformQuantizationInfo wqinfo = _weights->info()->quantization_info().uniform(); - const UniformQuantizationInfo oqinfo = _output->info()->quantization_info().uniform(); + const UniformQuantizationInfo iqinfo = src->quantization_info().uniform(); + const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform(); + const UniformQuantizationInfo oqinfo = dst->quantization_info().uniform(); float multiplier = iqinfo.scale * wqinfo.scale / oqinfo.scale; int output_multiplier = 0; @@ -502,27 +494,27 @@ void CLDirectConvolutionLayerKernel::configure(const CLCompileContext &compile_c _config_id += "_"; _config_id += support::cpp11::to_string(border_size().bottom); _config_id += "_"; - _config_id += support::cpp11::to_string(_conv_stride_x); + _config_id += support::cpp11::to_string(conv_stride_x); _config_id += "_"; - _config_id += support::cpp11::to_string(_conv_stride_y); + _config_id += support::cpp11::to_string(conv_stride_y); _config_id += "_"; - _config_id += support::cpp11::to_string(output->info()->dimension(width_idx)); + _config_id += support::cpp11::to_string(dst->dimension(width_idx)); _config_id += "_"; - _config_id += support::cpp11::to_string(output->info()->dimension(height_idx)); + _config_id += support::cpp11::to_string(dst->dimension(height_idx)); _config_id += "_"; _config_id += lower_string(string_from_data_layout(_data_layout)); } -Status CLDirectConvolutionLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const GPUTarget target) +Status ClDirectConvolutionKernel::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info, + const GPUTarget target) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, target).first); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, weights, biases, dst, conv_info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), weights->clone().get(), dst->clone().get(), conv_info, target).first); return Status{}; } -void CLDirectConvolutionLayerKernel::run(const Window &window, cl::CommandQueue &queue) +void ClDirectConvolutionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); @@ -530,20 +522,25 @@ void CLDirectConvolutionLayerKernel::run(const Window &window, cl::CommandQueue // Get initial windows Window slice = window.first_slice_window_3D(); + const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0)); + const auto weights = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1)); + const auto biases = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_2)); + auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); + if(_data_layout == DataLayout::NHWC) { - slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1) * _output->info()->dimension(2), 1)); - slice.set(Window::DimZ, Window::Dimension(0, _output->info()->dimension(3), 1)); + slice.set(Window::DimY, Window::Dimension(0, dst->info()->dimension(1) * dst->info()->dimension(2), 1)); + slice.set(Window::DimZ, Window::Dimension(0, dst->info()->dimension(3), 1)); unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, slice); - add_3D_tensor_argument(idx, _output, slice); - add_3D_tensor_argument(idx, _weights, slice); - if(_biases != nullptr) + add_3D_tensor_argument(idx, src, slice); + add_3D_tensor_argument(idx, dst, slice); + add_3D_tensor_argument(idx, weights, slice); + if(biases != nullptr) { - add_1D_tensor_argument(idx, _biases, slice); + add_1D_tensor_argument(idx, biases, slice); } - _kernel.setArg(idx++, static_cast<unsigned int>(_weights->info()->strides_in_bytes()[3])); + _kernel.setArg(idx++, static_cast<unsigned int>(weights->info()->strides_in_bytes()[3])); enqueue(queue, *this, slice, lws_hint()); } else @@ -556,30 +553,35 @@ void CLDirectConvolutionLayerKernel::run(const Window &window, cl::CommandQueue const int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); const int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); - win_in.set_dimension_step(width_idx, window[width_idx].step() * _conv_stride_x); - win_in.set_dimension_step(height_idx, window[height_idx].step() * _conv_stride_y); + const int conv_stride_x = std::get<0>(_conv_info.stride()); + const int conv_stride_y = std::get<1>(_conv_info.stride()); + + win_in.set_dimension_step(width_idx, window[width_idx].step() * conv_stride_x); + win_in.set_dimension_step(height_idx, window[height_idx].step() * conv_stride_y); Window slice_in = win_in.first_slice_window_3D(); unsigned int idx1 = 2 * num_arguments_per_3D_tensor(); - add_3D_tensor_argument(idx1, _weights, slice); + add_3D_tensor_argument(idx1, weights, slice); - if(_biases != nullptr) + if(biases != nullptr) { Window slice_biases; - slice_biases.use_tensor_dimensions(_biases->info()->tensor_shape()); - add_1D_tensor_argument(idx1, _biases, slice_biases); + slice_biases.use_tensor_dimensions(biases->info()->tensor_shape()); + add_1D_tensor_argument(idx1, biases, slice_biases); } - _kernel.setArg(idx1++, static_cast<unsigned int>(_weights->info()->strides_in_bytes()[3])); + _kernel.setArg(idx1++, static_cast<unsigned int>(weights->info()->strides_in_bytes()[3])); do { unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, slice_in); - add_3D_tensor_argument(idx, _output, slice); + add_3D_tensor_argument(idx, src, slice_in); + add_3D_tensor_argument(idx, dst, slice); enqueue(queue, *this, slice, lws_hint()); } while(window.slide_window_slice_3D(slice) && win_in.slide_window_slice_3D(slice_in)); } } +} // namespace kernels +} // namespace opencl } // namespace arm_compute diff --git a/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.h b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.h new file mode 100644 index 0000000000..ff2f5619db --- /dev/null +++ b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.h @@ -0,0 +1,97 @@ +/* + * Copyright (c) 2017-2021 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. + */ +#ifndef ARM_COMPUTE_CL_DIRECT_CONVOLUTION_KERNEL_H +#define ARM_COMPUTE_CL_DIRECT_CONVOLUTION_KERNEL_H + +#include "src/core/common/Macros.h" +#include "src/core/gpu/cl/ClCompileContext.h" +#include "src/core/gpu/cl/IClKernel.h" + +namespace arm_compute +{ +namespace opencl +{ +namespace kernels +{ +/** Interface for the direct convolution kernel. + */ +class ClDirectConvolutionKernel : public ICLKernel +{ +public: + ClDirectConvolutionKernel() = default; + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClDirectConvolutionKernel); + /** Set the src, weights, biases and dst tensors info. + * + * @note: Due to set_valid_region(), thus src/weights/biases cannot be const. Need to change this once the set_valid_region() is removed. + * + * @note: DirectConvolution only works in the following configurations: + * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 + * 3x3 convolution with stride_x = 1/2, stride_y = 1/2 + * 5x5 convolution with stride_x = 1/2, stride_y = 1/2 + * 9x9 convolution with stride_x = 1/2, stride_y = 1/2 + * + * @param[in] compile_context The compile context to be used. + * @param[in] src The src tensor info to convolve. 3 lower dimensions represent a single src [width, height, IFM], + * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32. + * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. + * The 3rd dimension must be the same as the src's volume 3rd dimension. + * Data type supported:Same as @p src. + * @param[in] biases Biases tensor info. Biases are 1D tensor with dimension [OFM]. + * Data type supported: Should match @p src data type, except for src of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type + * @param[out] dst Output tensor info. + * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p src. + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + */ + void configure(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *dst, const PadStrideInfo &conv_info); + /** Static function to check if given info will lead to a valid configuration of @ref ClDirectConvolutionKernel + * + * @param[in] src The src tensor info to convolve. 3 lower dimensions represent a single src [width, height, IFM], + * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32. + * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. + * The 3rd dimension must be the same as the src's volume 3rd dimension. + * Data type supported:Same as @p src. + * @param[in] biases Biases tensor info. Biases are 1D tensor with dimension [OFM]. + * Data type supported: Should match @p src data type, except for src of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type. + * @param[in] dst Output tensor info. + * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p src. + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + * @param[in] target Target GPU architecture. + * + * @return a status + */ + static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info, const GPUTarget target); + + // Inherited methods overridden: + void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override; + BorderSize border_size() const override; + +public: + DataLayout _data_layout{}; + BorderSize _border_size{}; + PadStrideInfo _conv_info{}; +}; +} // namespace kernels +} // namespace opencl +} // namespace arm_compute +#endif /*ARM_COMPUTE_CL_DIRECT_CONVOLUTION_KERNEL_H */ diff --git a/src/core/gpu/cl/kernels/ClScaleKernel.cpp b/src/core/gpu/cl/kernels/ClScaleKernel.cpp index 0882f29135..7fb5d2a5d3 100644 --- a/src/core/gpu/cl/kernels/ClScaleKernel.cpp +++ b/src/core/gpu/cl/kernels/ClScaleKernel.cpp @@ -146,28 +146,26 @@ void ClScaleKernel::configure(const CLCompileContext &compile_context, ITensorIn auto padding_info = get_padding_info({ src, dst }); // Info required for the static tuning - _info = info; - _data_type = src->data_type(); - _data_layout = _info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : _info.data_layout; + _data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout; float wr = 0.f; float hr = 0.f; - std::tie(wr, hr) = calculate_scale_factors(src, dst, _data_layout, _info.align_corners); - const bool call_quantized_kernel = is_data_type_quantized_asymmetric(src->data_type()) && _info.interpolation_policy == InterpolationPolicy::BILINEAR; + std::tie(wr, hr) = calculate_scale_factors(src, dst, _data_layout, info.align_corners); + const bool call_quantized_kernel = is_data_type_quantized_asymmetric(src->data_type()) && info.interpolation_policy == InterpolationPolicy::BILINEAR; // Compute actual border size BorderSize border = border_size(); const bool is_nhwc = _data_layout == DataLayout::NHWC; // Area interpolation behaves as Nearest Neighbour in case of up-sampling - auto interpolation_policy_to_use = _info.interpolation_policy; - if(_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) + auto interpolation_policy_to_use = info.interpolation_policy; + if(info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) { interpolation_policy_to_use = InterpolationPolicy::NEAREST_NEIGHBOR; } // Configure kernel window - auto win_config = validate_and_configure_window(src, dst, _info, border); + auto win_config = validate_and_configure_window(src, dst, info, border); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); @@ -178,7 +176,7 @@ void ClScaleKernel::configure(const CLCompileContext &compile_context, ITensorIn build_opts.add_option("-DBORDER_SIZE=" + support::cpp11::to_string(border.right)); build_opts.add_option_if(info.border_mode == BorderMode::REPLICATE, "-DBORDER_MODE_REPLICATE"); build_opts.add_option_if(is_nhwc, "-DDEPTH_OUT=" + support::cpp11::to_string(dst->dimension(2))); - build_opts.add_option_if_else(_info.sampling_policy == SamplingPolicy::CENTER, "-DSAMPLING_POLICY_CENTER", "-DSAMPLING_POLICY_TOP_LEFT"); + build_opts.add_option_if_else(info.sampling_policy == SamplingPolicy::CENTER, "-DSAMPLING_POLICY_CENTER", "-DSAMPLING_POLICY_TOP_LEFT"); build_opts.add_option_if(info.align_corners, "-DALIGN_CORNERS"); if(call_quantized_kernel) { @@ -209,13 +207,10 @@ void ClScaleKernel::configure(const CLCompileContext &compile_context, ITensorIn _kernel.setArg<float>(idx++, wr); _kernel.setArg<float>(idx++, hr); - // Set to enable static tuning - _output_x_dim = dst->dimension(0); - // Set config_id for enabling LWS tuning _config_id = "scale_"; - _config_id += (_info.border_mode == BorderMode::REPLICATE ? "Bord_rep" : ""); - _config_id += (_info.sampling_policy == SamplingPolicy::CENTER ? "center" : "topleft"); + _config_id += (info.border_mode == BorderMode::REPLICATE ? "Bord_rep" : ""); + _config_id += (info.sampling_policy == SamplingPolicy::CENTER ? "center" : "topleft"); _config_id += (is_nhwc ? "nhwc" : "nchw"); _config_id += "_"; _config_id += support::cpp11::to_string(dst->dimension(0)); diff --git a/src/core/gpu/cl/kernels/ClScaleKernel.h b/src/core/gpu/cl/kernels/ClScaleKernel.h index b6eea0620b..10a1105f08 100644 --- a/src/core/gpu/cl/kernels/ClScaleKernel.h +++ b/src/core/gpu/cl/kernels/ClScaleKernel.h @@ -70,29 +70,8 @@ public: BorderSize border_size() const override; void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override; - // Getter for interpolation policy - InterpolationPolicy get_interpolation_policy() const - { - return _info.interpolation_policy; - } - - // Getter for data type - DataType get_data_type() const - { - return _data_type; - } - - // Getter for output x dimension - unsigned int get_output_x_dim() const - { - return _output_x_dim; - } - private: - ScaleKernelInfo _info = ScaleKernelInfo(InterpolationPolicy::NEAREST_NEIGHBOR, BorderMode::UNDEFINED); - DataType _data_type = DataType::UNKNOWN; - DataLayout _data_layout = DataLayout::UNKNOWN; - unsigned int _output_x_dim = 0; + DataLayout _data_layout = DataLayout::UNKNOWN; }; } // namespace kernels } // namespace opencl |