diff options
Diffstat (limited to 'src/gpu/cl/kernels/ClDirectConv2dKernel.cpp')
| -rw-r--r-- | src/gpu/cl/kernels/ClDirectConv2dKernel.cpp | 542 |
1 files changed, 542 insertions, 0 deletions
diff --git a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp new file mode 100644 index 0000000000..7cf1958c1b --- /dev/null +++ b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp @@ -0,0 +1,542 @@ +/* + * Copyright (c) 2017-2023 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/gpu/cl/kernels/ClDirectConv2dKernel.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/ITensor.h" +#include "arm_compute/core/KernelDescriptors.h" +#include "arm_compute/core/PixelValue.h" +#include "arm_compute/core/utils/ActivationFunctionUtils.h" +#include "arm_compute/core/utils/helpers/AdjustVecSize.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" +#include "arm_compute/core/utils/StringUtils.h" + +#include "src/core/AccessWindowStatic.h" +#include "src/core/CL/CLUtils.h" +#include "src/core/CL/CLValidate.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" +#include "src/gpu/cl/kernels/gemm/ClGemmHelpers.h" +#include "support/Cast.h" +#include "support/StringSupport.h" + +namespace arm_compute +{ +namespace opencl +{ +namespace kernels +{ +namespace +{ +Status validate_arguments(const ITensorInfo *src, + const ITensorInfo *weights, + const ITensorInfo *biases, + const ITensorInfo *dst, + const PadStrideInfo &conv_info, + const ActivationLayerInfo &act_info, + const DirectConvComputeKernelInfo &desc) +{ + 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 = 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(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(desc.export_input_to_cl_image == true, + "Export to CLImage is not supported for the input tensor"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.export_output_to_cl_image == true, + "Export to CLImage is not supported for the output tensor"); + + if (data_layout == DataLayout::NCHW) + { + 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(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) && + std::get<0>(conv_info.stride()) > 2, + "Strides larger than 2 not supported for 3x3, 5x5, 9x9 convolution."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(act_info.enabled(), "Fused activation is not supported for NCHW layout"); + + 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"); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG( + weights->dimension(width_idx) != 1 && weights->dimension(width_idx) != 3 && + weights->dimension(width_idx) != 5, + "Kernel sizes other than 1x1, 3x3 or 5x5 are not supported with float data types"); + } + } + + if (data_layout == DataLayout::NHWC) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(act_info.enabled() && !is_data_type_float(src->data_type()), + "Fused activation in NHWC is only supported for floating point."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.m0 <= 0 || desc.m0 > 8, + "M0 can only be greater than 0 and less than or equal to 8"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.n0 != 1 && desc.n0 != 2 && desc.n0 != 3 && desc.n0 != 4 && desc.n0 != 8 && + desc.n0 != 16, + "N0 can only be: 1, 2, 3, 4, 8, and 16"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.k0 != 1 && desc.k0 != 2 && desc.k0 != 3 && desc.k0 != 4 && desc.k0 != 8 && + desc.k0 != 16, + "K0 can only be: 1, 2, 3, 4, 8, and 16"); + if (desc.export_weights_to_cl_image) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(desc.k0 != 4 && desc.k0 != 8 && desc.k0 != 16, + "K0 can only be: 4, 8, and 16"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(!export_to_cl_image(weights), + "Export to CLImage is not supported for this weight configuration"); + } + } + + if (biases != nullptr) + { + if (is_data_type_quantized_asymmetric(src->data_type())) + { + 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_MSG(biases->dimension(0) != weights->dimension(3), + "Biases size and number of dst feature maps should match"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->num_dimensions() > 1, "Biases should be one dimensional"); + } + + // Checks performed when dst is configured + if (dst->total_size() != 0) + { + 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 = src->data_type(); + if (is_data_type_quantized(data_type)) + { + 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; + int output_shift = 0; + ARM_COMPUTE_RETURN_ON_ERROR( + quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift)); + } + return Status{}; +} +} // namespace + +ClDirectConv2dKernel::ClDirectConv2dKernel() +{ + _type = CLKernelType::DIRECT; +} + +void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, + ITensorInfo *src, + ITensorInfo *weights, + ITensorInfo *biases, + ITensorInfo *dst, + const PadStrideInfo &conv_info, + const ActivationLayerInfo &act_info, + const DirectConvComputeKernelInfo &desc) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src, weights, dst); + + // Perform validation + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, weights, biases, dst, conv_info, act_info, desc)); + + 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->dimension(width_idx); + const DataType data_type = src->data_type(); + + const GPUTarget gpu_target = get_target(); + unsigned int _num_elems_processed_per_iteration = 0; + + // 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(*dst, output_shape, 1, src->data_type(), src->quantization_info()); + + // Configure kernel window + Window win; + if (_data_layout == DataLayout::NHWC) + { + output_shape.collapse(2U, 1U); + const unsigned int n0 = adjust_vec_size(desc.n0, output_shape[0]); + const unsigned int m0 = adjust_vec_size(desc.m0, output_shape[1]); + + // Create window and update padding + win = calculate_max_window(output_shape, Steps(n0, m0)); + } + else if (_data_layout == DataLayout::NCHW) + { + _num_elems_processed_per_iteration = 1u; + win = calculate_max_window(*dst, Steps(_num_elems_processed_per_iteration)); + } + + ICLKernel::configure_internal(win); + + std::stringstream kernel_name; + CLBuildOptions build_options; + + if (_data_layout == DataLayout::NHWC) + { + kernel_name << "direct_convolution_nhwc"; + + const unsigned int n0 = win.x().step(); + const unsigned int m0 = win.y().step(); + const unsigned int k0 = adjust_vec_size(desc.k0, src->dimension(channel_idx)); + const unsigned int partial_store_n0 = dst->dimension(channel_idx) % n0; + const unsigned int pad_left = conv_info.pad_left(); + const unsigned int pad_top = conv_info.pad_top(); + + _export_weights_to_cl_image = desc.export_weights_to_cl_image; + _export_input_to_cl_image = desc.export_input_to_cl_image; + _export_output_to_cl_image = desc.export_output_to_cl_image; + + // Update the padding for the weights tensor if we can export to cl_image + if (_export_weights_to_cl_image) + { + gemm::update_padding_for_cl_image(weights); + } + + if (_export_output_to_cl_image) + { + gemm::update_padding_for_cl_image(dst); + } + + if (_export_input_to_cl_image) + { + gemm::update_padding_for_cl_image(src); + } + + 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->data_type()))); + } + + // Conditions of -cl-fast-relaxed-math causing accuracy issues can be traced from COMPMID-5324 + const auto act_function = act_info.activation(); + const auto dst_data_type = dst->data_type(); + + if ((gpu_target != GPUTarget::G71 && (gpu_target & GPUTarget::GPU_ARCH_MASK) == GPUTarget::BIFROST) && + (act_function == ActivationLayerInfo::ActivationFunction::BOUNDED_RELU || + act_function == ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) && + (dst_data_type == DataType::F32 || dst_data_type == DataType::F16)) + { + // -cl-fast-relaxed-math also sets -cl-finite-math-only and -cl-unsafe-math-optimizations + // to disable -cl-finite-math-only, we only include -cl-unsafe-math-optimizations + build_options.add_option("-cl-unsafe-math-optimizations"); + } + else + { + build_options.add_option("-cl-fast-relaxed-math"); + } + + build_options.add_option_if_else(_export_input_to_cl_image, "-DSRC_TENSOR_TYPE=IMAGE", + "-DSRC_TENSOR_TYPE=BUFFER"); + build_options.add_option("-DSRC_DATA_TYPE=" + get_cl_type_from_data_type(src->data_type())); + build_options.add_option("-DSRC_CHANNELS=" + support::cpp11::to_string(src->dimension(0))); + build_options.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(1))); + build_options.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(2))); + build_options.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(dst->dimension(0))); + build_options.add_option("-DDST_WIDTH=" + support::cpp11::to_string(dst->dimension(1))); + build_options.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(dst->dimension(2))); + build_options.add_option_if_else(_export_output_to_cl_image, "-DDST_TENSOR_TYPE=IMAGE", + "-DDST_TENSOR_TYPE=BUFFER"); + build_options.add_option("-DDST_DATA_TYPE=" + get_cl_type_from_data_type(dst_data_type)); + build_options.add_option_if_else(_export_weights_to_cl_image, "-DWEI_TENSOR_TYPE=IMAGE", + "-DWEI_TENSOR_TYPE=BUFFER"); + 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)); + build_options.add_option("-DM0=" + support::cpp11::to_string(m0)); + build_options.add_option("-DK0=" + support::cpp11::to_string(k0)); + build_options.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_store_n0)); + build_options.add_option_if((src->dimension(channel_idx) % k0) != 0, "-DLEFTOVER_LOOP"); + build_options.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_function))); + + if (is_data_type_quantized(data_type)) + { + 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, src->data_type(), src->quantization_info()); + int zero_value_s32; + zero_value.get(zero_value_s32); + + float multiplier = iqinfo.scale * wqinfo.scale / oqinfo.scale; + int output_multiplier = 0; + int output_shift = 0; + quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift); + build_options.add_option("-DIS_QUANTIZED"); + build_options.add_option("-DDST_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); + build_options.add_option("-DDST_SHIFT=" + support::cpp11::to_string(output_shift)); + build_options.add_option("-DSRC_OFFSET=" + support::cpp11::to_string(-iqinfo.offset)); + build_options.add_option("-DWEI_OFFSET=" + support::cpp11::to_string(-wqinfo.offset)); + build_options.add_option("-DDST_OFFSET=" + support::cpp11::to_string(oqinfo.offset)); + build_options.add_option("-DZERO_VALUE=" + support::cpp11::to_string(zero_value_s32)); + build_options.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(DataType::S32)); + } + else + { + build_options.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(data_type)); + build_options.add_option("-DZERO_VALUE=" + support::cpp11::to_string(0)); + build_options.add_option("-DSRC_OFFSET=" + support::cpp11::to_string(0)); + build_options.add_option("-DWEI_OFFSET=" + support::cpp11::to_string(0)); + build_options.add_option("-DDST_OFFSET=" + support::cpp11::to_string(0)); + build_options.add_option_if(act_info.enabled(), + "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); + build_options.add_option_if(act_info.enabled(), + "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); + } + + if (compile_context.get_ddk_version() >= 30) + { + build_options.add_option("-fregister-allocation=64"); + } + } + else + { + _export_weights_to_cl_image = false; + + kernel_name << "direct_convolution_nchw"; + build_options.add_option_if(biases != nullptr, std::string("-DHAS_BIAS")); + 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("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left())); + build_options.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top())); + 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("-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(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->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))); + build_options.add_option( + std::string("-DVEC_SIZE=" + support::cpp11::to_string(_num_elems_processed_per_iteration))); + build_options.add_option( + std::string("-DVEC_SIZE_LEFTOVER=" + + support::cpp11::to_string(src->dimension(0) % _num_elems_processed_per_iteration))); + + if (is_data_type_quantized(data_type)) + { + 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; + int output_shift = 0; + quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift); + build_options.add_option("-DIS_QUANTIZED"); + build_options.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); + build_options.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + build_options.add_option("-DKERNEL_SIZE=" + support::cpp11::to_string(kernel_size)); + build_options.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iqinfo.offset)); + build_options.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wqinfo.offset)); + build_options.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oqinfo.offset)); + } + } + + _kernel = create_kernel(compile_context, kernel_name.str(), build_options.options()); + + // Set config_id for enabling LWS tuning + // config_id should include the variables used to parameterize the kernel + _config_id = kernel_name.str(); + _config_id += "_"; + _config_id += lower_string(string_from_data_type(data_type)); + _config_id += "_"; + _config_id += support::cpp11::to_string(kernel_size); + _config_id += "_"; + _config_id += support::cpp11::to_string(border_size().left); + _config_id += "_"; + _config_id += support::cpp11::to_string(border_size().top); + _config_id += "_"; + _config_id += support::cpp11::to_string(border_size().right); + _config_id += "_"; + _config_id += support::cpp11::to_string(border_size().bottom); + _config_id += "_"; + _config_id += support::cpp11::to_string(conv_stride_x); + _config_id += "_"; + _config_id += support::cpp11::to_string(conv_stride_y); + // SRC_CHANNELS, SRC_WIDTH, SRC_HEIGHT + _config_id += "_"; + _config_id += support::cpp11::to_string(src->dimension(channel_idx)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src->dimension(width_idx)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src->dimension(height_idx)); + _config_id += "_"; + // DST_CHANNELS, DST_WIDTH, DST_HEIGHT + _config_id += support::cpp11::to_string(dst->dimension(channel_idx)); + _config_id += "_"; + _config_id += support::cpp11::to_string(dst->dimension(width_idx)); + _config_id += "_"; + _config_id += support::cpp11::to_string(dst->dimension(height_idx)); + _config_id += "_"; + _config_id += lower_string(string_from_data_layout(_data_layout)); +} + +Status ClDirectConv2dKernel::validate(const ITensorInfo *src, + const ITensorInfo *weights, + const ITensorInfo *biases, + const ITensorInfo *dst, + const PadStrideInfo &conv_info, + const ActivationLayerInfo &act_info, + const DirectConvComputeKernelInfo &desc) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, weights, biases, dst, conv_info, act_info, desc)); + return Status{}; +} + +void ClDirectConv2dKernel::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); + + // 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) + { + cl::Image2D weights_cl_image; + cl::Image2D output_cl_image; + cl::Image2D input_cl_image; + + if (_export_weights_to_cl_image) + { + // Export tensor to cl_image + weights_cl_image = create_image2d_from_tensor(weights, CLImage2DType::ReadOnly); + } + + if (_export_output_to_cl_image) + { + // Export tensor to cl_image + output_cl_image = create_image2d_from_tensor(dst, CLImage2DType::WriteOnly); + } + + if (_export_input_to_cl_image) + { + // Export tensor to cl_image + input_cl_image = create_image2d_from_tensor(src, CLImage2DType::ReadOnly); + } + + unsigned int idx = 0; + if (_export_input_to_cl_image) + { + _kernel.setArg(idx++, input_cl_image); + } + add_4d_tensor_nhwc_argument(idx, src); + if (_export_output_to_cl_image) + { + _kernel.setArg(idx++, output_cl_image); + } + add_4d_tensor_nhwc_argument(idx, dst); + if (_export_weights_to_cl_image) + { + _kernel.setArg(idx++, weights_cl_image); + } + add_4d_tensor_nhwc_argument(idx, weights); + if (biases != nullptr) + { + add_1D_tensor_argument(idx, biases, slice); + } + enqueue(queue, *this, slice, lws_hint()); + } + else + { + unsigned int idx1 = 2 * num_arguments_per_3D_tensor(); + add_3D_tensor_argument(idx1, weights, slice); + + if (biases != nullptr) + { + Window 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])); + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, src, slice); + add_3D_tensor_argument(idx, dst, slice); + enqueue(queue, *this, slice, lws_hint()); + } while (window.slide_window_slice_3D(slice)); + } +} +} // namespace kernels +} // namespace opencl +} // namespace arm_compute |