diff options
Diffstat (limited to 'src/core/CL/kernels')
8 files changed, 134 insertions, 674 deletions
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp index 287a965f5b..dda70d2231 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp @@ -114,20 +114,19 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, } std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, GPUTarget gpu_target, std::string &kernel_name, const Size2D dilation) + unsigned int depth_multiplier, std::string &kernel_name, const Size2D dilation) { // Output auto inizialitation if not yet initialized const ConvolutionInfo info { conv_info, depth_multiplier, ActivationLayerInfo(), dilation }; - const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, info); + const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, info); auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_quantization_info(output->quantization_info())); const unsigned int conv_stride_x = conv_info.stride().first; const unsigned int conv_stride_y = conv_info.stride().second; const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); - const bool is_bifrost = get_arch_from_target(gpu_target) == GPUTarget::BIFROST; // Configure kernel window unsigned int num_elems_read_per_iteration_x = 0; @@ -156,31 +155,28 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * conv_stride_x; break; } - if(is_bifrost) + if(conv_stride_x == 1 && conv_stride_y == 1) { - if(conv_stride_x == 1 && conv_stride_y == 1) - { - kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f16"; - num_elems_read_per_iteration_x = 8; - num_elems_written_per_iteration_x = 4; - num_elems_read_per_iteration_y = 6; - num_elems_written_per_iteration_y = 4; - } - else if(conv_stride_x == 2 && conv_stride_y == 2) - { - kernel_name = "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f16"; - num_elems_read_per_iteration_x = 10; - num_elems_written_per_iteration_x = 4; - num_elems_read_per_iteration_y = 5; - num_elems_written_per_iteration_y = 2; - } + kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_f16"; + num_elems_read_per_iteration_x = 8; + num_elems_written_per_iteration_x = 4; + num_elems_read_per_iteration_y = 6; + num_elems_written_per_iteration_y = 4; + } + else if(conv_stride_x == 2 && conv_stride_y == 2) + { + kernel_name = "depthwise_convolution_3x3_stridex2_stridey2_f16"; + num_elems_read_per_iteration_x = 10; + num_elems_written_per_iteration_x = 4; + num_elems_read_per_iteration_y = 5; + num_elems_written_per_iteration_y = 2; } } - else if(input->data_type() == DataType::F32 && is_bifrost) + else if(input->data_type() == DataType::F32) { if(conv_stride_x == 1 && conv_stride_y == 1) { - kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f32"; + kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_f32"; num_elems_read_per_iteration_x = 4; num_elems_read_per_iteration_y = 6; num_elems_written_per_iteration_x = 2; @@ -188,7 +184,7 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen } else if(conv_stride_x == 2 && conv_stride_y == 2) { - kernel_name = "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f32"; + kernel_name = "depthwise_convolution_3x3_stridex2_stridey2_f32"; num_elems_read_per_iteration_x = 6; num_elems_read_per_iteration_y = 5; num_elems_written_per_iteration_x = 2; @@ -239,7 +235,7 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen } // namespace CLDepthwiseConvolutionLayer3x3NCHWKernel::CLDepthwiseConvolutionLayer3x3NCHWKernel() - : _conv_stride_x(0), _conv_pad_top(0), _conv_pad_left(0) + : _border_size(0), _input(), _output(), _weights(), _biases(), _conv_stride_y(1), _output_multipliers(), _output_shifts(), _is_quantized(false), _conv_stride_x(0), _conv_pad_top(0), _conv_pad_left(0) { } @@ -278,10 +274,9 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const CLCompileContext _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); // Configure kernel window - std::string kernel_name; - const GPUTarget gpu_target = get_target(); + std::string kernel_name; - auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, gpu_target, kernel_name, dilation); + auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, kernel_name, dilation); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); @@ -372,13 +367,13 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const CLCompileContext } Status CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { std::string kernel_name; ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), - conv_info, depth_multiplier, gpu_target, kernel_name, dilation) + conv_info, depth_multiplier, kernel_name, dilation) .first); return Status{}; diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h index 45b5869676..c4e475f6f2 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020 Arm Limited. + * Copyright (c) 2018-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -24,7 +24,7 @@ #ifndef ARM_COMPUTE_CLDEPTHWISECONVOLUTIONNCHWKERNEL3x3_H #define ARM_COMPUTE_CLDEPTHWISECONVOLUTIONNCHWKERNEL3x3_H -#include "src/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h" +#include "src/core/CL/ICLKernel.h" namespace arm_compute { @@ -32,11 +32,19 @@ class ICLTensor; /** Interface for the kernel to run a 3x3 depthwise convolution on a tensor when the data layout is NCHW. */ -class CLDepthwiseConvolutionLayer3x3NCHWKernel : public ICLDepthwiseConvolutionLayer3x3Kernel +class CLDepthwiseConvolutionLayer3x3NCHWKernel : public ICLKernel { public: /** Default constructor */ CLDepthwiseConvolutionLayer3x3NCHWKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayer3x3NCHWKernel(const CLDepthwiseConvolutionLayer3x3NCHWKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayer3x3NCHWKernel &operator=(const CLDepthwiseConvolutionLayer3x3NCHWKernel &) = delete; + /** Default Move Constructor. */ + CLDepthwiseConvolutionLayer3x3NCHWKernel(CLDepthwiseConvolutionLayer3x3NCHWKernel &&) = default; + /** Default move assignment operator */ + CLDepthwiseConvolutionLayer3x3NCHWKernel &operator=(CLDepthwiseConvolutionLayer3x3NCHWKernel &&) = default; /** Initialize the function's source, destination, conv and border_size. * * @param[in] input Source tensor. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32. @@ -56,7 +64,7 @@ public: */ void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override; + const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr); /** Initialize the function's source, destination, conv and border_size. * * @param[in] compile_context The compile context to be used. @@ -77,7 +85,7 @@ public: */ void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override; + const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr); /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NCHWKernel * * @param[in] input Source tensor info. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32. @@ -89,7 +97,6 @@ public: * @param[in] conv_info Padding and stride information to use for the convolution. * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. - * @param[in] gpu_target (Optional) GPU target to validate the kernel for. Defaults to midgard. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * @param[in] output_multipliers (Optional) Output multipliers tensor info for quantized computations. In case of per-channel quantization, * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 @@ -99,13 +106,23 @@ public: * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, + unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), const ITensorInfo *output_multipliers = nullptr, const ITensorInfo *output_shifts = nullptr); void run(const Window &window, cl::CommandQueue &queue) override; BorderSize border_size() const override; private: + BorderSize _border_size; + const ICLTensor *_input; + ICLTensor *_output; + const ICLTensor *_weights; + const ICLTensor *_biases; + unsigned int _conv_stride_y; + const ICLTensor *_output_multipliers; + const ICLTensor *_output_shifts; + bool _is_quantized; + unsigned int _conv_stride_x; unsigned int _conv_pad_top; unsigned int _conv_pad_left; diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp index f7603e6397..2a1365e6e2 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "src/core/AccessWindowStatic.h" #include "src/core/CL/CLValidate.h" #include "src/core/CL/ICLKernel.h" @@ -43,17 +42,11 @@ namespace arm_compute namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation, - const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { + ARM_COMPUTE_UNUSED(act_info); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::QASYMM8 || input->data_type() == DataType::QASYMM8_SIGNED) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LOGISTIC), - "For QASYMM8 only logistic, relu, lower bounded relu and lower-upper bounded relu are supported"); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1); // COMPMID-1071 Add depth multiplier support for NHWC ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1); @@ -61,54 +54,21 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1)); - const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); const size_t weights_width = 3; const size_t weights_height = 3; const ConvolutionInfo info{ conv_info, depth_multiplier, ActivationLayerInfo(), dilation }; - const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape( - *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), info); - if(is_qasymm) - { - DepthwiseConvolutionReshapeInfo info; - info.c0 = 4; - ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(0) / info.c0) != weights_width * weights_height); - - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1); - ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1); - - if(is_data_type_quantized_per_channel(weights->data_type())) - { - ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != output_multipliers->dimension(0)); - ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != output_shifts->dimension(0)); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0)); - ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0)); - } - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(1) != weights_width) || (weights->dimension(2) != weights_height)); - } + + const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape( + *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), info); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(1) != weights_width) || (weights->dimension(2) != weights_height)); if(biases != nullptr) { ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[0]); - if(is_qasymm) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); - } + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); } @@ -122,10 +82,9 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, } std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, - ITensorInfo *output_multipliers, ITensorInfo *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) { - ARM_COMPUTE_UNUSED(weights); + ARM_COMPUTE_UNUSED(weights, bias); ARM_COMPUTE_UNUSED(depth_multiplier); const bool is_stride_1_dilation_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1) && dilation.x() == 1 && dilation.y() == 1); @@ -134,115 +93,46 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen Window win{}; Status err{}; - if(is_data_type_quantized_asymmetric(input->data_type())) - { - const unsigned int num_elems_accessed_per_iteration = 4; - const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2; - const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast<float>(conv_info.stride().first)); - - BorderSize border_size; - border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); - - // Configure kernel window - win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration)); - - AccessWindowStatic input_access(input, 0, -border_size.top, ceil_to_multiple(input->dimension(0), num_elems_accessed_per_iteration), - ceil_to_multiple(input->dimension(1) + border_size.bottom, num_rows_read_per_iteration)); - AccessWindowRectangle output_access(output, 0, 0, num_elems_accessed_per_iteration, num_rows_written_per_iteration); - - bool window_changed = false; - - if((output_multipliers != nullptr) && (output_shifts != nullptr)) - { - AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, num_elems_accessed_per_iteration); - AccessWindowHorizontal output_shifts_access(output_shifts, 0, num_elems_accessed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, input_access, output_access, output_multipliers_access, output_shifts_access); - } - else - { - Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input"); - return std::make_pair(err, win); - } - - if(bias != nullptr) - { - AccessWindowHorizontal bias_access(bias, 0, num_elems_accessed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, bias_access); - } - - err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - } - else - { - unsigned int num_elems_accessed_per_iteration = adjust_vec_size(4 / input->element_size(), input->dimension(0)); - win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_processed_per_iteration)); - } + unsigned int num_elems_accessed_per_iteration = adjust_vec_size(4 / input->element_size(), input->dimension(0)); + win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_processed_per_iteration)); return std::make_pair(err, win); } } // namespace CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel() - : _num_planes_processed_per_iteration(1) -{ -} - -BorderSize CLDepthwiseConvolutionLayer3x3NHWCKernel::border_size() const + : _input(), _output(), _weights(), _biases(), _num_planes_processed_per_iteration(1) { - return _border_size; } void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ICLTensor *output_multipliers, const ICLTensor *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { - configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts); + configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ICLTensor *output_multipliers, const ICLTensor *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), - conv_info, depth_multiplier, act_info, dilation, - (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, - (output_shifts != nullptr) ? output_shifts->info() : nullptr)); + conv_info, depth_multiplier, act_info, dilation)); auto padding_info = get_padding_info({ input, weights, biases, output }); auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), - conv_info, depth_multiplier, dilation, - (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, - (output_shifts != nullptr) ? output_shifts->info() : nullptr); + conv_info, depth_multiplier, dilation); - const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); - const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); - const bool is_quantized_per_channel = is_data_type_quantized_per_channel(weights->info()->data_type()); - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_quantized_per_channel; + const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); + const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); _input = input; _output = output; _weights = weights; _biases = biases; - _conv_stride_y = conv_info.stride().second; _num_planes_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; - _output_multipliers = output_multipliers; - _output_shifts = output_shifts; - _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); - if(_is_quantized) - { - _border_size = BorderSize(input->info()->padding()); - - // If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1 - if(is_dot8_supported) - { - _num_planes_processed_per_iteration = 1; - } - } - - unsigned int num_elems_accessed_per_iteration = _is_quantized ? 4 : adjust_vec_size(4 / input->info()->element_size(), input->info()->dimension(0)); + unsigned int num_elems_accessed_per_iteration = adjust_vec_size(4 / input->info()->element_size(), input->info()->dimension(0)); unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; CLBuildOptions build_opts; @@ -257,54 +147,8 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); build_opts.add_option_if(_input->info()->tensor_shape().total_size_upper(3) > 1, "-DDST_DEPTH=" + support::cpp11::to_string(static_cast<int>(std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration))))); - - if(_is_quantized) - { - const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); - - build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1))); - build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset)); - build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset)); - build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset)); - build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * iq_info.offset * wq_info.offset)); - build_opts.add_option_if(is_quantized_per_channel, "-DPER_CHANNEL_QUANTIZATION"); - build_opts.add_option_if(is_dot8_supported, "-DIS_DOT8"); - - // Compute non-per-channel multiplier and shift anyway to make OpenCL kernel simpler - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift); - build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); - build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); - - if(act_info.enabled()) - { - int a_val{}; - int b_val{}; - std::tie(b_val, a_val) = get_quantized_activation_min_max(act_info, input->info()->data_type(), oq_info); - - const int o1 = oq_info.offset; - - build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val)); - build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val)); - build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1)); - - const float s1 = iq_info.scale; - build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); - build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); - } - - build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type())); - build_opts.add_option("-DWEIGHTS_PROMOTED_TYPE=" + get_cl_promoted_type_from_data_type(weights->info()->data_type())); - } - else - { - build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); - build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); - } + build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); + build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); if(is_stride_1_dilation_1) { @@ -317,30 +161,20 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext else { build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(conv_info.stride().first)); - build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); + build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(conv_info.stride().second)); build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); } - std::string kernel_name; // Create kernel - if(_is_quantized) - { - kernel_name = std::string("dwc_3x3_reshaped_quantized8"); - kernel_name += (is_dot8_supported && is_stride_1_dilation_1 ? "_dot8" : ""); - kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); - kernel_name += "_nhwc"; - } - else - { - kernel_name = std::string("depthwise_convolution_3x3_nhwc"); - kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); - } + std::string kernel_name; + kernel_name = std::string("depthwise_convolution_3x3_nhwc"); + kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); ICLKernel::configure_internal(win_config.second); _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - ARM_COMPUTE_ERROR_ON(!_is_quantized && has_padding_changed(padding_info)); + ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); // Set config_id for enabling LWS tuning _config_id = kernel_name; @@ -359,15 +193,12 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext } Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), biases != nullptr ? biases->clone().get() : nullptr, - output->clone().get(), conv_info, depth_multiplier, dilation, - (output_multipliers != nullptr) ? output_multipliers->clone().get() : nullptr, - (output_shifts != nullptr) ? output_shifts->clone().get() : nullptr) + output->clone().get(), conv_info, depth_multiplier, dilation) .first); return Status{}; } @@ -382,16 +213,7 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com Window win = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); win.set(Window::DimZ, Window::Dimension(0, std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration)) * total_batches, 1)); - unsigned int idx = 2 * num_arguments_per_4D_tensor() + (_is_quantized ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); - - if(_is_quantized) - { - Window slice; - slice.use_tensor_dimensions(_output_multipliers->info()->tensor_shape()); - slice.set_dimension_step(Window::DimX, window.x().step()); - add_1D_tensor_argument(idx, _output_multipliers, slice); - add_1D_tensor_argument(idx, _output_shifts, slice); - } + unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor(); if(_biases != nullptr) { @@ -401,62 +223,14 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com add_1D_tensor_argument(idx, _biases, win_biases); } - if(_is_quantized) - { - // Calculate the max_offset. - // max_offset is the offset for the last NOT valid value in the Z dimension (spatial dimension Y for NHWC) - // |******************| - // | pad_top | - // |******************| - // | | - // | plane0 | - // | batch0 | - // |__________________| - // |******************| Batch 0 - // | pad_bottom | - // | pad_top | - // |******************| - // | | - // | plane1 | - // | batch0 | - // |__________________|-----> max_offset - // |******************| - // | pad_bottom | - // | pad_top | - // |******************| - // | | - // | plane0 | - // | batch1 | - // |__________________| - // |******************| Batch 1 - // | pad_bottom | - // | pad_top | - // |******************| - // | | - // | plane1 | - // | batch1 | - // |__________________| - // | pad_bottom | - // |******************| - const int max_offset = ((_input->info()->dimension(1) * _input->info()->dimension(2)) + (_input->info()->padding().bottom + _input->info()->padding().top) * (_input->info()->dimension( - 2) - 1)) * _input->info()->strides_in_bytes().y(); - _kernel.setArg(idx, max_offset); - } - Window slice = win.first_slice_window_4D(); do { unsigned int idx = 0; add_4D_tensor_argument(idx, _input, slice); add_4D_tensor_argument(idx, _output, slice); - if(_is_quantized) - { - add_2D_tensor_argument(idx, _weights, slice); - } - else - { - add_3D_tensor_argument(idx, _weights, slice); - } + add_3D_tensor_argument(idx, _weights, slice); + enqueue(queue, *this, slice, lws_hint()); } while(win.slide_window_slice_4D(slice)); diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h index ce0bf5ceb3..ee47d98807 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020 Arm Limited. + * Copyright (c) 2018-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -24,7 +24,7 @@ #ifndef ARM_COMPUTE_CLDEPTHWISECONVOLUTIONNHWCKERNEL3x3_H #define ARM_COMPUTE_CLDEPTHWISECONVOLUTIONNHWCKERNEL3x3_H -#include "src/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h" +#include "src/core/CL/ICLKernel.h" namespace arm_compute { @@ -32,81 +32,78 @@ class ICLTensor; /** Interface for the kernel to run a 3x3 depthwise convolution on a tensor when the data layout is NHWC. */ -class CLDepthwiseConvolutionLayer3x3NHWCKernel : public ICLDepthwiseConvolutionLayer3x3Kernel +class CLDepthwiseConvolutionLayer3x3NHWCKernel : public ICLKernel { public: /** Default constructor */ CLDepthwiseConvolutionLayer3x3NHWCKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayer3x3NHWCKernel(const CLDepthwiseConvolutionLayer3x3NHWCKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayer3x3NHWCKernel &operator=(const CLDepthwiseConvolutionLayer3x3NHWCKernel &) = delete; + /** Default Move Constructor. */ + CLDepthwiseConvolutionLayer3x3NHWCKernel(CLDepthwiseConvolutionLayer3x3NHWCKernel &&) = default; + /** Default move assignment operator */ + CLDepthwiseConvolutionLayer3x3NHWCKernel &operator=(CLDepthwiseConvolutionLayer3x3NHWCKernel &&) = default; /** Default move assignment operator. */ /** Initialize the function's source, destination, conv and border_size. * - * @param[in] input Source tensor. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32. - * @param[in] weights Weights tensor. A 3D tensor with dimensions [IFM, 3, 3]. - * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. - * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] conv_info Padding and stride information to use for the convolution. - * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. - * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - * @param[in] output_shifts (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 + * @param[in] input Source tensor. DataType supported: F16/F32. + * @param[in] weights Weights tensor. A 3D tensor with dimensions [IFM, 3, 3]. + * Data type supported: Same as @p input. + * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input. + * @param[out] output Destination tensor. Data type supported: Same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). */ void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override; + unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); /** Initialize the function's source, destination, conv and border_size. * - * @param[in] compile_context The compile context to be used. - * @param[in] input Source tensor. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32. - * @param[in] weights Weights tensor. A 3D tensor with dimensions [IFM, 3, 3]. - * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. - * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] conv_info Padding and stride information to use for the convolution. - * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. - * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - * @param[in] output_shifts (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 + * @param[in] compile_context The compile context to be used. + * @param[in] input Source tensor. DataType supported: F16/F32. + * @param[in] weights Weights tensor. A 3D tensor with dimensions [IFM, 3, 3]. + * Data type supported: Same as @p input. + * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input. + * @param[out] output Destination tensor. Data type supported: Same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). */ void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override; + unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NHWCKernel * - * @param[in] input Source tensor info. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32. - * @param[in] weights Weights tensor info. A 3D tensor with dimensions [IFM, 3, 3]. - * Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED. - * @param[in] biases Biases tensor info. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED. - * @param[in] output Destination tensor info. Data type supported: Same as @p input. - * @param[in] conv_info Padding and stride information to use for the convolution. - * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. - * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] output_multipliers (Optional) Output multipliers tensor info for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - * @param[in] output_shifts (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 + * @param[in] input Source tensor info. DataType supported: F16/F32. + * @param[in] weights Weights tensor info. A 3D tensor with dimensions [IFM, 3, 3]. + * Data type supported: Same as @p input. + * @param[in] biases Biases tensor info. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input. + * @param[in] output Destination tensor info. Data type supported: Same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ITensorInfo *output_multipliers = nullptr, const ITensorInfo *output_shifts = nullptr); + unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); // Inherited methods overridden: void run(const Window &window, cl::CommandQueue &queue) override; - BorderSize border_size() const override; private: + const ICLTensor *_input; + ICLTensor *_output; + const ICLTensor *_weights; + const ICLTensor *_biases; + unsigned int _num_planes_processed_per_iteration; }; } // namespace arm_compute diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp deleted file mode 100644 index 386d634cea..0000000000 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp +++ /dev/null @@ -1,131 +0,0 @@ -/* - * Copyright (c) 2019-2021 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. - */ -#include "src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLKernelLibrary.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "src/core/AccessWindowStatic.h" -#include "src/core/CL/CLValidate.h" -#include "src/core/CL/ICLKernel.h" -#include "src/core/helpers/AutoConfiguration.h" -#include "src/core/helpers/WindowHelpers.h" -#include "support/StringSupport.h" - -namespace arm_compute -{ -namespace -{ -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const DepthwiseConvolutionReshapeInfo &info) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); - const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); - const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); - - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC); - ARM_COMPUTE_RETURN_ERROR_ON(info.c0 != 4); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_h) != 3); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_w) != 3); - ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); - - if(output->total_size() != 0) - { - auto reshaped_weights_shape = arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_shape(*input, info); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), reshaped_weights_shape); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); - } - - return Status{}; -} - -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const DepthwiseConvolutionReshapeInfo &info) -{ - auto reshaped_input_shape = arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_shape(*input, info); - auto_init_if_empty(*output, reshaped_input_shape, 1, input->data_type(), input->quantization_info()); - - Window win = calculate_max_window(*input, Steps(info.c0)); - AccessWindowHorizontal weights_access(input, 0, info.c0); - const bool window_changed = update_window_and_padding(win, weights_access); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -CLDepthwiseConvolutionLayerReshapeWeightsKernel::CLDepthwiseConvolutionLayerReshapeWeightsKernel() - : _input(nullptr), _output(nullptr) -{ -} - -void CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure(const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info) -{ - configure(CLKernelLibrary::get().get_compile_context(), input, output, info); -} - -void CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), info)); - auto win_config = validate_and_configure_window(input->info(), output->info(), info); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - ICLKernel::configure_internal(win_config.second); - - _input = input; - _output = output; - - // Build the kernel - CLBuildOptions build_opts; - build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(info.c0)); - build_opts.add_option("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(0))); - build_opts.add_option_if(info.transpose, "-DTRANSPOSE"); - build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); - - _kernel = create_kernel(compile_context, "depthwise_convolution_reshape_weights", build_opts.options()); -} - -Status CLDepthwiseConvolutionLayerReshapeWeightsKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const DepthwiseConvolutionReshapeInfo &info) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), info).first); - return Status{}; -} - -void CLDepthwiseConvolutionLayerReshapeWeightsKernel::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 idx = 0; - add_3D_tensor_argument(idx, _input, window); - add_2D_tensor_argument(idx, _output, window); - enqueue(queue, *this, window, lws_hint()); -} -} // namespace arm_compute diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h b/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h deleted file mode 100644 index 650fe9a11b..0000000000 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h +++ /dev/null @@ -1,85 +0,0 @@ -/* - * Copyright (c) 2019-2020 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_CLDEPTHWISECONVOLUTIONLAYERRESHAPEWEIGHTSKERNEL_H -#define ARM_COMPUTE_CLDEPTHWISECONVOLUTIONLAYERRESHAPEWEIGHTSKERNEL_H - -#include "src/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** Interface for the kernel to reshape the weights of depthwise convolution. */ -class CLDepthwiseConvolutionLayerReshapeWeightsKernel : public ICLKernel -{ -public: - /** Default constructor */ - CLDepthwiseConvolutionLayerReshapeWeightsKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDepthwiseConvolutionLayerReshapeWeightsKernel(const CLDepthwiseConvolutionLayerReshapeWeightsKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDepthwiseConvolutionLayerReshapeWeightsKernel &operator=(const CLDepthwiseConvolutionLayerReshapeWeightsKernel &) = delete; - /** Default Move Constructor. */ - CLDepthwiseConvolutionLayerReshapeWeightsKernel(CLDepthwiseConvolutionLayerReshapeWeightsKernel &&) = default; - /** Default move assignment operator */ - CLDepthwiseConvolutionLayerReshapeWeightsKernel &operator=(CLDepthwiseConvolutionLayerReshapeWeightsKernel &&) = default; - - /** Initialize the function's source and destination. - * - * @param[in] input The input tensor of dimension [IFM, W, H]. Data types supported: All. Data layouts supported: NHWC - * @param[out] output The output tensor of dimension [W*H*C0, ceil(IFM/C0)]. C0 is the number of channels read by each thread. Data types supported: same as @p weights. - * @param[in] info Depthwise convolution information to reshape the input tensor. - */ - void configure(const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info); - /** Initialize the function's source and destination. - * - * @param[in] compile_context The compile context to be used. - * @param[in] input The input tensor of dimension [IFM, W, H]. Data types supported: All. Data layouts supported: NHWC - * @param[out] output The output tensor of dimension [W*H*C0, ceil(IFM/C0)]. C0 is the number of channels read by each thread. Data types supported: same as @p weights. - * @param[in] info Depthwise convolution information to reshape the input tensor. - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info); - - /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NHWCKernel - * - * @param[in] input The input tensor info of dimension [IFM, W, H]. Data types supported: All. Data layouts supported: NHWC - * @param[in] output The output tensor info of dimension [W*H*C0, ceil(IFM/C0)]. C0 is the number of channels read by each thread. Data types supported: same as @p weights. - * @param[in] info Depthwise convolution information to reshape the input tensor. - * - * @return a Status - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *output, const DepthwiseConvolutionReshapeInfo &info); - - // Inherited methods overridden: - void run(const Window &window, cl::CommandQueue &queue) override; - -private: - const ICLTensor *_input; - ICLTensor *_output; - - void configure_dot_product(const DepthwiseConvolutionReshapeInfo &info); - void configure_generic(const DepthwiseConvolutionReshapeInfo &info); -}; -} // namespace arm_compute -#endif /* ARM_COMPUTE_CLDEPTHWISECONVOLUTIONLAYERRESHAPEWEIGHTSKERNEL_H */ diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp index d9f293ba73..c688951d57 100644 --- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp +++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp @@ -36,8 +36,6 @@ #include "support/StringSupport.h" -#include "utils/TypePrinter.h" - namespace arm_compute { namespace diff --git a/src/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h b/src/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h deleted file mode 100644 index 4c92ae417f..0000000000 --- a/src/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h +++ /dev/null @@ -1,105 +0,0 @@ -/* - * Copyright (c) 2017-2020 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_ICLDEPTHWISECONVOLUTIONKERNEL3x3_H -#define ARM_COMPUTE_ICLDEPTHWISECONVOLUTIONKERNEL3x3_H - -#include "src/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** Interface for the kernel to run a 3x3 depthwise convolution on a tensor. - */ -class ICLDepthwiseConvolutionLayer3x3Kernel : public ICLKernel -{ -public: - /** Default constructor */ - ICLDepthwiseConvolutionLayer3x3Kernel() - : _border_size(0), _input(), _output(), _weights(), _biases(), _conv_stride_y(1), _output_multipliers(), _output_shifts(), _is_quantized(false) - { - } - /** Prevent instances of this class from being copied (As this class contains pointers) */ - ICLDepthwiseConvolutionLayer3x3Kernel(const ICLDepthwiseConvolutionLayer3x3Kernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - ICLDepthwiseConvolutionLayer3x3Kernel &operator=(const ICLDepthwiseConvolutionLayer3x3Kernel &) = delete; - /** Default Move Constructor. */ - ICLDepthwiseConvolutionLayer3x3Kernel(ICLDepthwiseConvolutionLayer3x3Kernel &&) = default; - /** Default move assignment operator */ - ICLDepthwiseConvolutionLayer3x3Kernel &operator=(ICLDepthwiseConvolutionLayer3x3Kernel &&) = default; - /** Initialize the function's source, destination, conv and border_size. - * - * @param[in] input Source tensor. DataType supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. A 3D tensor with dimensions [3, 3, IFM]. - * Data type supported: Same as @p input, QASYMM8/QSYMM8_PER_CHANNEL when input is QASYMM8. - * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input, S32 when input is QASYMM8. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] conv_info Padding and stride information to use for the convolution. - * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported for QASYMM8. - * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - * @param[in] output_shifts (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - */ - virtual void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) = 0; - /** Initialize the function's source, destination, conv and border_size. - * - * @param[in] compile_context The compile context to be used. - * @param[in] input Source tensor. DataType supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. A 3D tensor with dimensions [3, 3, IFM]. - * Data type supported: Same as @p input, QASYMM8/QSYMM8_PER_CHANNEL when input is QASYMM8. - * @param[in] biases Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input, S32 when input is QASYMM8. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] conv_info Padding and stride information to use for the convolution. - * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported for QASYMM8. - * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). - * @param[in] output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - * @param[in] output_shifts (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization, - * the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32 - */ - virtual void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), - const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) = 0; - -protected: - BorderSize _border_size; - const ICLTensor *_input; - ICLTensor *_output; - const ICLTensor *_weights; - const ICLTensor *_biases; - unsigned int _conv_stride_y; - const ICLTensor *_output_multipliers; - const ICLTensor *_output_shifts; - bool _is_quantized; -}; -} // namespace arm_compute -#endif /*ARM_COMPUTE_ICLDEPTHWISECONVOLUTIONKERNEL3x3_H */ |