From afd38f0c617d6f89b2b4532c6c44f116617e2b6f Mon Sep 17 00:00:00 2001 From: Felix Thomasmathibalan Date: Wed, 27 Sep 2023 17:46:17 +0100 Subject: Apply clang-format on repository Code is formatted as per a revised clang format configuration file(not part of this delivery). Version 14.0.6 is used. Exclusion List: - files with .cl extension - files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...) And the following directories - compute_kernel_writer/validation/ - tests/ - include/ - src/core/NEON/kernels/convolution/ - src/core/NEON/kernels/arm_gemm/ - src/core/NEON/kernels/arm_conv/ - data/ There will be a follow up for formatting of .cl files and the files under tests/ and compute_kernel_writer/validation/. Signed-off-by: Felix Thomasmathibalan Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391 Benchmark: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Gunes Bayir --- src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp | 45 ++++++++++++++---------- 1 file changed, 26 insertions(+), 19 deletions(-) (limited to 'src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp') diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp index 542d380e4a..9ed9d7c5b0 100644 --- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp +++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp @@ -31,10 +31,10 @@ #include "arm_compute/core/Utils.h" #include "arm_compute/core/utils/helpers/AdjustVecSize.h" #include "arm_compute/core/Validate.h" + #include "src/core/CL/CLValidate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" - #include "support/StringSupport.h" namespace arm_compute @@ -43,7 +43,8 @@ namespace { constexpr int max_input_tensor_dim = 3; -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) +Status +validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_UNUSED(epsilon); @@ -53,14 +54,15 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, cons ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis > 2, "Actual axis greater than 2 is not supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, "Actual normalization axis greater than max number of dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, + "Actual normalization axis greater than max number of dimensions"); // Reduce shape on axis TensorShape sum_shape = input->tensor_shape(); sum_shape.set(actual_axis, 1); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape); - if(output->total_size() != 0) + if (output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); @@ -78,16 +80,22 @@ CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel() _type = CLKernelType::ELEMENTWISE; } -void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon) +void CLL2NormalizeLayerKernel::configure( + const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon) { configure(CLKernelLibrary::get().get_compile_context(), input, sum, output, axis, epsilon); } -void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon) +void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context, + const ICLTensor *input, + const ICLTensor *sum, + ICLTensor *output, + int axis, + float epsilon) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon)); - auto padding_info = get_padding_info({ input, sum, output }); + auto padding_info = get_padding_info({input, sum, output}); _input = input; _sum = sum; @@ -95,8 +103,9 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context _actual_axis = wrap_around(axis, max_input_tensor_dim); _epsilon = epsilon; - const unsigned int vec_size_x = adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0)); - const int vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x; + const unsigned int vec_size_x = + adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0)); + const int vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x; // Set build options CLBuildOptions build_opts; @@ -107,7 +116,7 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context // Create kernel std::string kernel_name; unsigned int idx = 0; - switch(_actual_axis) + switch (_actual_axis) { case 0: kernel_name = "l2_normalize_x"; @@ -127,7 +136,7 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); // Set epsilon argument - if(input->info()->data_type() == DataType::F32) + if (input->info()->data_type() == DataType::F32) { _kernel.setArg(idx, _epsilon); } @@ -146,7 +155,8 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); } -Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) +Status CLL2NormalizeLayerKernel::validate( + const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon)); return Status{}; @@ -159,7 +169,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue Window window_sum(window); - switch(_actual_axis) + switch (_actual_axis) { case 0: { @@ -173,8 +183,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue add_2D_tensor_argument(idx, _sum, sum_slice); add_2D_tensor_argument(idx, _output, in_slice); enqueue(queue, *this, in_slice, lws_hint()); - } - while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice)); + } while (window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice)); } break; case 1: @@ -189,8 +198,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue add_2D_tensor_argument(idx, _sum, sum_slice); add_2D_tensor_argument(idx, _output, in_slice); enqueue(queue, *this, in_slice, lws_hint()); - } - while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice)); + } while (window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(sum_slice)); } break; case 2: @@ -205,8 +213,7 @@ void CLL2NormalizeLayerKernel::run(const Window &window, cl::CommandQueue &queue add_3D_tensor_argument(idx, _sum, sum_slice); add_3D_tensor_argument(idx, _output, in_slice); enqueue(queue, *this, in_slice, lws_hint()); - } - while(window.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(sum_slice)); + } while (window.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(sum_slice)); } break; default: -- cgit v1.2.1