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 <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
diff --git a/src/gpu/cl/kernels/ClWeightsReshapeKernel.cpp b/src/gpu/cl/kernels/ClWeightsReshapeKernel.cpp
index 8f36345..af80c4d 100644
--- a/src/gpu/cl/kernels/ClWeightsReshapeKernel.cpp
+++ b/src/gpu/cl/kernels/ClWeightsReshapeKernel.cpp
@@ -22,9 +22,11 @@
* SOFTWARE.
*/
#include "src/gpu/cl/kernels/ClWeightsReshapeKernel.h"
+
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/Cast.h"
@@ -39,7 +41,10 @@
{
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups)
+Status validate_arguments(const ITensorInfo *input,
+ const ITensorInfo *biases,
+ const ITensorInfo *output,
+ unsigned int num_groups)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
@@ -48,20 +53,24 @@
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4 && num_groups > 1);
ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(3) % num_groups) != 0);
- if(biases != nullptr)
+ if (biases != nullptr)
{
ARM_COMPUTE_RETURN_ERROR_ON(!is_data_type_float(input->data_type()));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases);
ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) && (biases->num_dimensions() != 1));
ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 5) && (biases->num_dimensions() != 2));
- ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) && (biases->dimension(0) != input->tensor_shape()[3]));
- ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 5) && (biases->dimension(0) != input->tensor_shape()[3] || biases->dimension(1) != input->tensor_shape()[4]));
+ ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) &&
+ (biases->dimension(0) != input->tensor_shape()[3]));
+ ARM_COMPUTE_RETURN_ERROR_ON(
+ (input->num_dimensions() == 5) &&
+ (biases->dimension(0) != input->tensor_shape()[3] || biases->dimension(1) != input->tensor_shape()[4]));
}
// Checks performed when output is configured
- if(output->total_size() != 0)
+ if (output->total_size() != 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_weights_reshaped_shape(*input, biases != nullptr, num_groups));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(
+ output->tensor_shape(), compute_weights_reshaped_shape(*input, biases != nullptr, num_groups));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
}
@@ -75,16 +84,21 @@
_type = CLKernelType::ELEMENTWISE;
}
-void ClWeightsReshapeKernel::configure(const ClCompileContext &compile_context, const ITensorInfo *src, const ITensorInfo *biases, ITensorInfo *dst, unsigned int num_groups)
+void ClWeightsReshapeKernel::configure(const ClCompileContext &compile_context,
+ const ITensorInfo *src,
+ const ITensorInfo *biases,
+ ITensorInfo *dst,
+ unsigned int num_groups)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
// Output tensor auto inizialitation if not yet initialized
- auto_init_if_empty(*dst, src->clone()->set_tensor_shape(compute_weights_reshaped_shape(*src, (biases != nullptr), num_groups)));
+ auto_init_if_empty(
+ *dst, src->clone()->set_tensor_shape(compute_weights_reshaped_shape(*src, (biases != nullptr), num_groups)));
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, biases, dst, num_groups));
- auto padding_info = get_padding_info({ src, biases, dst });
+ auto padding_info = get_padding_info({src, biases, dst});
const DataType data_type = src->data_type();
@@ -104,7 +118,10 @@
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
-Status ClWeightsReshapeKernel::validate(const ITensorInfo *src, const ITensorInfo *biases, const ITensorInfo *dst, unsigned int num_groups)
+Status ClWeightsReshapeKernel::validate(const ITensorInfo *src,
+ const ITensorInfo *biases,
+ const ITensorInfo *dst,
+ unsigned int num_groups)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, biases, dst, num_groups));
return Status{};
@@ -136,7 +153,7 @@
_kernel.setArg<cl_uint>(idx++, src->info()->dimension(3));
_kernel.setArg<cl_uint>(idx++, dst->info()->strides_in_bytes().z());
- if(biases != nullptr)
+ if (biases != nullptr)
{
biases_window.use_tensor_dimensions(biases->info()->tensor_shape());
biases_slice = biases_window.first_slice_window_1D();
@@ -148,7 +165,7 @@
unsigned idx = 0;
add_3D_tensor_argument(idx, src, in_slice);
add_2D_tensor_argument(idx, dst, out_slice);
- if(biases != nullptr)
+ if (biases != nullptr)
{
add_1D_tensor_argument(idx, biases, biases_slice);
ARM_COMPUTE_UNUSED(biases_window.slide_window_slice_1D(biases_slice));
@@ -156,8 +173,7 @@
// Run kernel
enqueue(queue, *this, in_slice, lws_hint());
- }
- while(window.slide_window_slice_4D(in_slice) && out_window.slide_window_slice_2D(out_slice));
+ } while (window.slide_window_slice_4D(in_slice) && out_window.slide_window_slice_2D(out_slice));
}
} // namespace kernels
} // namespace opencl