diff options
Diffstat (limited to 'src/gpu/cl/kernels/ClIm2ColKernel.cpp')
| -rw-r--r-- | src/gpu/cl/kernels/ClIm2ColKernel.cpp | 154 |
1 files changed, 102 insertions, 52 deletions
diff --git a/src/gpu/cl/kernels/ClIm2ColKernel.cpp b/src/gpu/cl/kernels/ClIm2ColKernel.cpp index e890847199..ef7a52828f 100644 --- a/src/gpu/cl/kernels/ClIm2ColKernel.cpp +++ b/src/gpu/cl/kernels/ClIm2ColKernel.cpp @@ -29,9 +29,10 @@ #include "arm_compute/core/CL/OpenCL.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/StringUtils.h" +#include "arm_compute/core/Validate.h" + #include "src/core/AccessWindowStatic.h" #include "src/core/CL/CLValidate.h" #include "src/core/helpers/AutoConfiguration.h" @@ -60,13 +61,19 @@ struct Im2ColConfiguration bool is_padding_required_nchw{}; }; -Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation, - unsigned int num_groups) +Status validate_arguments(const ITensorInfo *src, + const ITensorInfo *dst, + const Size2D &kernel_dims, + const PadStrideInfo &conv_info, + bool has_bias, + const Size2D &dilation, + unsigned int num_groups) { const unsigned int channel_idx = get_data_layout_dimension_index(src->data_layout(), DataLayoutDimension::CHANNEL); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, + DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized(src->data_type()) && has_bias); ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst); ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1)); @@ -82,9 +89,10 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const const unsigned total_height = src->dimension(height_idx) + conv_info.pad_top() + conv_info.pad_bottom(); ARM_COMPUTE_RETURN_ERROR_ON((total_width < kernel_dims.width) || (total_height < kernel_dims.height)); - if(dst->total_size() > 0) + if (dst->total_size() > 0) { - const TensorInfo tensor_info_output = dst->clone()->set_tensor_shape(compute_im2col_conv_shape(src, kernel_dims, conv_info, has_bias, dilation, num_groups == 1, num_groups)); + const TensorInfo tensor_info_output = dst->clone()->set_tensor_shape( + compute_im2col_conv_shape(src, kernel_dims, conv_info, has_bias, dilation, num_groups == 1, num_groups)); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(src, dst); @@ -93,13 +101,21 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const return Status{}; } -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, ITensorInfo *dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation, - unsigned int num_elems_processed_per_iteration, bool is_padding_required_nchw, unsigned int num_groups) +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, + ITensorInfo *dst, + const Size2D &kernel_dims, + const PadStrideInfo &conv_info, + bool has_bias, + const Size2D &dilation, + unsigned int num_elems_processed_per_iteration, + bool is_padding_required_nchw, + unsigned int num_groups) { ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); // Output tensor auto initialization if not yet initialized - TensorShape expected_output_shape = compute_im2col_conv_shape(src, kernel_dims, conv_info, has_bias, dilation, num_groups == 1, num_groups); + TensorShape expected_output_shape = + compute_im2col_conv_shape(src, kernel_dims, conv_info, has_bias, dilation, num_groups == 1, num_groups); auto_init_if_empty(*dst, src->clone()->set_tensor_shape(expected_output_shape)); @@ -113,22 +129,22 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, ITenso bool window_changed = false; Window win; - if(data_layout == DataLayout::NHWC) + if (data_layout == DataLayout::NHWC) { win = calculate_max_window(*src, Steps(num_elems_processed_per_iteration)); } else { - if(is_padding_required_nchw) + if (is_padding_required_nchw) { - const BorderSize border(conv_info.pad_top(), conv_info.pad_right(), conv_info.pad_bottom(), conv_info.pad_left()); - win = calculate_max_window(*src, - Steps(num_elems_processed_per_iteration * conv_info.stride().first, conv_info.stride().second)); - AccessWindowStatic input_access(src, - -border.left, - -border.top, - ceil_to_multiple(input_width + border.right, kernel_dims.width * num_elems_processed_per_iteration), - input_height + border.bottom); + const BorderSize border(conv_info.pad_top(), conv_info.pad_right(), conv_info.pad_bottom(), + conv_info.pad_left()); + win = calculate_max_window( + *src, Steps(num_elems_processed_per_iteration * conv_info.stride().first, conv_info.stride().second)); + AccessWindowStatic input_access( + src, -border.left, -border.top, + ceil_to_multiple(input_width + border.right, kernel_dims.width * num_elems_processed_per_iteration), + input_height + border.bottom); window_changed = window_changed || update_window_and_padding(win, input_access); } else @@ -142,11 +158,17 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, ITenso // set the Z dimension's step same size as the whole dimension so that one can't split across the Z dimension win.set_dimension_step(Window::DimZ, win[Window::DimZ].end() - win[Window::DimZ].start()); - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + Status err = + (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } -Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation, unsigned int num_groups) +Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, + const Size2D &kernel_dims, + const PadStrideInfo &conv_info, + bool has_bias, + const Size2D &dilation, + unsigned int num_groups) { const DataLayout data_layout = src->data_layout(); const DataType data_type = src->data_type(); @@ -157,7 +179,8 @@ Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D const unsigned int input_height = src->dimension(height_idx); const unsigned int input_channel = src->dimension(channel_idx); - const std::pair<unsigned int, unsigned int> convolved_dims = scaled_dimensions(input_width, input_height, kernel_dims.width, kernel_dims.height, conv_info, dilation); + const std::pair<unsigned int, unsigned int> convolved_dims = + scaled_dimensions(input_width, input_height, kernel_dims.width, kernel_dims.height, conv_info, dilation); // Im2Col configuration std::string kernel_name = "im2col_generic_"; @@ -184,21 +207,22 @@ Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); build_opts.add_option_if(num_groups > 1, "-DNUM_GROUPS=" + support::cpp11::to_string(num_groups)); - build_opts.add_option_if_else(is_data_type_quantized(data_type), "-DPAD_VALUE=" + support::cpp11::to_string(qinfo.offset), "-DPAD_VALUE=0"); + build_opts.add_option_if_else(is_data_type_quantized(data_type), + "-DPAD_VALUE=" + support::cpp11::to_string(qinfo.offset), "-DPAD_VALUE=0"); build_opts.add_option_if(has_bias, "-DHAS_BIAS"); - if(data_layout == DataLayout::NHWC) + if (data_layout == DataLayout::NHWC) { num_elems_processed_per_iteration = std::min(2U, input_channel); is_padding_required_nchw = false; // Only the 3x3 and 9x9 cases are optimized for NHWC - if(kernel_dims == Size2D(3U, 3U)) + if (kernel_dims == Size2D(3U, 3U)) { kernel_name = "im2col3x3_"; build_opts.add_option("-DIM2COL_3X3"); } - else if(kernel_dims == Size2D(9U, 9U)) + else if (kernel_dims == Size2D(9U, 9U)) { kernel_name = "im2col9x9_"; build_opts.add_option("-DIM2COL_9X9"); @@ -219,17 +243,17 @@ Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D } else { - if(dilation == Size2D(1U, 1U)) + if (dilation == Size2D(1U, 1U)) { const bool squared_im2col = kernel_dims.width == kernel_dims.height; - if(squared_im2col) + if (squared_im2col) { // Check if we can run an optimized im2col for NCHW - switch(kernel_dims.width) + switch (kernel_dims.width) { case 1: // Optimized im2col1x1 if stride_x = 1 and conv_info.has_padding() = false - if(conv_info.stride().first == 1 && !conv_info.has_padding()) + if (conv_info.stride().first == 1 && !conv_info.has_padding()) { kernel_name = "im2col1x1_stridex1_"; num_elems_processed_per_iteration = 4; @@ -248,7 +272,7 @@ Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D break; case 11: // Optimized im2col11x11 if pad_x = pad_y = 0 - if(!conv_info.has_padding()) + if (!conv_info.has_padding()) { kernel_name = "im2col11x11_padx0_pady0_"; num_elems_processed_per_iteration = 1; @@ -262,7 +286,7 @@ Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D break; } } - else if(kernel_dims.width > 1 && !conv_info.has_padding()) + else if (kernel_dims.width > 1 && !conv_info.has_padding()) { kernel_name = "im2col_generic_padx0_pady0_"; num_elems_processed_per_iteration = 1; @@ -297,19 +321,29 @@ Im2ColConfiguration configure_opencl_kernel(const ITensorInfo *src, const Size2D } // namespace ClIm2ColKernel::ClIm2ColKernel() - : _data_layout(DataLayout::UNKNOWN), _convolved_dims(), _num_elems_processed_per_iteration(1), _kernel_dims(), _conv_info(), _num_groups() + : _data_layout(DataLayout::UNKNOWN), + _convolved_dims(), + _num_elems_processed_per_iteration(1), + _kernel_dims(), + _conv_info(), + _num_groups() { _type = CLKernelType::ELEMENTWISE; } -void ClIm2ColKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, - const Size2D &dilation, - unsigned int num_groups) +void ClIm2ColKernel::configure(const ClCompileContext &compile_context, + ITensorInfo *src, + ITensorInfo *dst, + const Size2D &kernel_dims, + const PadStrideInfo &conv_info, + bool has_bias, + const Size2D &dilation, + unsigned int num_groups) { ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, kernel_dims, conv_info, has_bias, dilation, num_groups)); - auto padding_info = get_padding_info({ src, dst }); + auto padding_info = get_padding_info({src, dst}); _data_layout = src->data_layout(); const unsigned int width_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); @@ -320,19 +354,22 @@ void ClIm2ColKernel::configure(const ClCompileContext &compile_context, ITensorI // Select and configure the optimal OpenCL kernel to run. // This function returns the OpenCL kernel's name, the arguments to pass at compile time, the number of elements processed per iteration // and the padding requirement flag - Im2ColConfiguration im2col_config = configure_opencl_kernel(src, kernel_dims, conv_info, has_bias, dilation, num_groups); + Im2ColConfiguration im2col_config = + configure_opencl_kernel(src, kernel_dims, conv_info, has_bias, dilation, num_groups); // Create kernel _kernel = create_kernel(compile_context, im2col_config.kernel_name, im2col_config.build_options); - _convolved_dims = scaled_dimensions(input_width, input_height, kernel_dims.width, kernel_dims.height, conv_info, dilation); + _convolved_dims = + scaled_dimensions(input_width, input_height, kernel_dims.width, kernel_dims.height, conv_info, dilation); _num_elems_processed_per_iteration = im2col_config.num_elems_processed_per_iteration; _kernel_dims = kernel_dims; // Only needed by the Tuner _conv_info = conv_info; // Only needed by the Tuner _num_groups = num_groups; // Configure kernel window - auto win_config = validate_and_configure_window(src, dst, kernel_dims, conv_info, has_bias, dilation, im2col_config.num_elems_processed_per_iteration, + auto win_config = validate_and_configure_window(src, dst, kernel_dims, conv_info, has_bias, dilation, + im2col_config.num_elems_processed_per_iteration, im2col_config.is_padding_required_nchw, num_groups); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); IClKernel::configure_internal(win_config.second); @@ -353,14 +390,22 @@ void ClIm2ColKernel::configure(const ClCompileContext &compile_context, ITensorI ARM_COMPUTE_ERROR_ON(src->data_layout() == DataLayout::NHWC && has_padding_changed(padding_info)); } -Status ClIm2ColKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation, - unsigned int num_groups) +Status ClIm2ColKernel::validate(const ITensorInfo *src, + const ITensorInfo *dst, + const Size2D &kernel_dims, + const PadStrideInfo &conv_info, + bool has_bias, + const Size2D &dilation, + unsigned int num_groups) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, kernel_dims, conv_info, has_bias, dilation, num_groups)); - Im2ColConfiguration im2col_config = configure_opencl_kernel(src, kernel_dims, conv_info, has_bias, dilation, num_groups); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get(), kernel_dims, conv_info, has_bias, dilation, im2col_config.num_elems_processed_per_iteration, + Im2ColConfiguration im2col_config = + configure_opencl_kernel(src, kernel_dims, conv_info, has_bias, dilation, num_groups); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get(), kernel_dims, + conv_info, has_bias, dilation, + im2col_config.num_elems_processed_per_iteration, im2col_config.is_padding_required_nchw, num_groups) - .first); + .first); return Status{}; } @@ -388,7 +433,7 @@ void ClIm2ColKernel::run_op(ITensorPack &tensors, const Window &window, cl::Comm Window slice_in = first_slice_3d; Window slice_out = window_output.first_slice_window_2D(); - if(_data_layout == DataLayout::NHWC) + if (_data_layout == DataLayout::NHWC) { const Window tmp_win = window.collapse_if_possible(ICLKernel::window(), 3); const int num_batches = tmp_win[3].end(); @@ -398,7 +443,10 @@ void ClIm2ColKernel::run_op(ITensorPack &tensors, const Window &window, cl::Comm } else { - slice.set(0, Window::Dimension(0, static_cast<int>(ceil_to_multiple(_convolved_dims.first, _num_elems_processed_per_iteration)), _num_elems_processed_per_iteration)); + slice.set(0, + Window::Dimension( + 0, static_cast<int>(ceil_to_multiple(_convolved_dims.first, _num_elems_processed_per_iteration)), + _num_elems_processed_per_iteration)); slice.set(1, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1)); // Note: In case of NCHW the 3rd dimension is already set collapsing the input window } @@ -414,14 +462,16 @@ void ClIm2ColKernel::run_op(ITensorPack &tensors, const Window &window, cl::Comm slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); - unsigned int idx = num_arguments_per_3D_tensor() + (_num_groups == 1 ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); + unsigned int idx = num_arguments_per_3D_tensor() + + (_num_groups == 1 ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src->info()->strides_in_bytes()[3])); - _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[((_num_groups == 1) ? 2 : 3)])); + _kernel.setArg<cl_uint>(idx++, + static_cast<unsigned int>(dst->info()->strides_in_bytes()[((_num_groups == 1) ? 2 : 3)])); do { unsigned int idx = 0; add_3D_tensor_argument(idx, src, slice_in); - if(_num_groups == 1) + if (_num_groups == 1) { add_2D_tensor_argument(idx, dst, slice_out); } @@ -430,8 +480,8 @@ void ClIm2ColKernel::run_op(ITensorPack &tensors, const Window &window, cl::Comm add_3D_tensor_argument(idx, dst, slice_out); } enqueue(queue, *this, slice, lws_hint()); - } - while(window_collapsed.slide_window_slice_3D(slice) && window_output.slide_window_slice_2D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in)); + } while (window_collapsed.slide_window_slice_3D(slice) && window_output.slide_window_slice_2D(slice_out) && + window_collapsed.slide_window_slice_3D(slice_in)); } } // namespace kernels } // namespace opencl |