diff options
Diffstat (limited to 'src/gpu/cl/kernels/ClDirectConv2dKernel.cpp')
| -rw-r--r-- | src/gpu/cl/kernels/ClDirectConv2dKernel.cpp | 192 |
1 files changed, 117 insertions, 75 deletions
diff --git a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp index 7ad398412a..7cf1958c1b 100644 --- a/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp +++ b/src/gpu/cl/kernels/ClDirectConv2dKernel.cpp @@ -23,17 +23,18 @@ */ #include "src/gpu/cl/kernels/ClDirectConv2dKernel.h" -#include "arm_compute/core/utils/ActivationFunctionUtils.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" @@ -51,11 +52,17 @@ 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) +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_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(); @@ -63,41 +70,56 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, co 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->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"); + 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) + 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, + 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())) + 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"); + 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"); + 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) + 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, + 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, + 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) + 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"); @@ -106,9 +128,9 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, co } } - if(biases != nullptr) + if (biases != nullptr) { - if(is_data_type_quantized_asymmetric(src->data_type())) + if (is_data_type_quantized_asymmetric(src->data_type())) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); } @@ -118,20 +140,19 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, co } 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"); + 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) + 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_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)) + if (is_data_type_quantized(data_type)) { const UniformQuantizationInfo iqinfo = src->quantization_info().uniform(); const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform(); @@ -140,7 +161,8 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *weights, co 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)); + ARM_COMPUTE_RETURN_ON_ERROR( + quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift)); } return Status{}; } @@ -151,8 +173,14 @@ 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) +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); @@ -178,14 +206,11 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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()); + auto_init_if_empty(*dst, output_shape, 1, src->data_type(), src->quantization_info()); // Configure kernel window Window win; - if(_data_layout == DataLayout::NHWC) + if (_data_layout == DataLayout::NHWC) { output_shape.collapse(2U, 1U); const unsigned int n0 = adjust_vec_size(desc.n0, output_shape[0]); @@ -194,7 +219,7 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT // Create window and update padding win = calculate_max_window(output_shape, Steps(n0, m0)); } - else if(_data_layout == DataLayout::NCHW) + else if (_data_layout == DataLayout::NCHW) { _num_elems_processed_per_iteration = 1u; win = calculate_max_window(*dst, Steps(_num_elems_processed_per_iteration)); @@ -205,7 +230,7 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT std::stringstream kernel_name; CLBuildOptions build_options; - if(_data_layout == DataLayout::NHWC) + if (_data_layout == DataLayout::NHWC) { kernel_name << "direct_convolution_nhwc"; @@ -221,22 +246,22 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT _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) + if (_export_weights_to_cl_image) { gemm::update_padding_for_cl_image(weights); } - if(_export_output_to_cl_image) + if (_export_output_to_cl_image) { gemm::update_padding_for_cl_image(dst); } - if(_export_input_to_cl_image) + if (_export_input_to_cl_image) { gemm::update_padding_for_cl_image(src); } - if(biases != nullptr) + if (biases != nullptr) { build_options.add_option(std::string("-DHAS_BIAS")); build_options.add_option(std::string("-DBIA_DATA_TYPE=" + get_cl_type_from_data_type(biases->data_type()))); @@ -246,9 +271,10 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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)) + 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 @@ -259,7 +285,8 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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_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))); @@ -267,9 +294,11 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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_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_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())); @@ -284,7 +313,7 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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)) + if (is_data_type_quantized(data_type)) { const UniformQuantizationInfo iqinfo = src->quantization_info().uniform(); const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform(); @@ -314,11 +343,13 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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())); + 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) + if (compile_context.get_ddk_version() >= 30) { build_options.add_option("-fregister-allocation=64"); } @@ -340,13 +371,17 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT 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("-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))); + 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)) + if (is_data_type_quantized(data_type)) { const UniformQuantizationInfo iqinfo = src->quantization_info().uniform(); const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform(); @@ -405,8 +440,13 @@ void ClDirectConv2dKernel::configure(const CLCompileContext &compile_context, IT _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) +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{}; @@ -420,52 +460,55 @@ void ClDirectConv2dKernel::run_op(ITensorPack &tensors, const Window &window, cl // 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)); + 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) + 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) + 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) + 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) + 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) + 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) + 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) + if (_export_weights_to_cl_image) { _kernel.setArg(idx++, weights_cl_image); } add_4d_tensor_nhwc_argument(idx, weights); - if(biases != nullptr) + if (biases != nullptr) { add_1D_tensor_argument(idx, biases, slice); } @@ -476,7 +519,7 @@ void ClDirectConv2dKernel::run_op(ITensorPack &tensors, const Window &window, cl unsigned int idx1 = 2 * num_arguments_per_3D_tensor(); add_3D_tensor_argument(idx1, weights, slice); - if(biases != nullptr) + if (biases != nullptr) { Window slice_biases; slice_biases.use_tensor_dimensions(biases->info()->tensor_shape()); @@ -491,8 +534,7 @@ void ClDirectConv2dKernel::run_op(ITensorPack &tensors, const Window &window, cl 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)); + } while (window.slide_window_slice_3D(slice)); } } } // namespace kernels |