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/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp b/src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp
index c022450..c51641d 100644
--- a/src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp
+++ b/src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp
@@ -32,18 +32,24 @@
{
namespace graph
{
-FusedDepthwiseConvolutionBatchNormalizationNode::FusedDepthwiseConvolutionBatchNormalizationNode(float epsilon,
- PadStrideInfo info,
- unsigned int depth_multiplier,
- DepthwiseConvolutionMethod method,
- ActivationLayerInfo fused_activation)
- : _epsilon(epsilon), _info(std::move(info)), _depth_multiplier(depth_multiplier), _method(method), _fused_activation(fused_activation)
+FusedDepthwiseConvolutionBatchNormalizationNode::FusedDepthwiseConvolutionBatchNormalizationNode(
+ float epsilon,
+ PadStrideInfo info,
+ unsigned int depth_multiplier,
+ DepthwiseConvolutionMethod method,
+ ActivationLayerInfo fused_activation)
+ : _epsilon(epsilon),
+ _info(std::move(info)),
+ _depth_multiplier(depth_multiplier),
+ _method(method),
+ _fused_activation(fused_activation)
{
_input_edges.resize(7, EmptyEdgeID);
_outputs.resize(1, NullTensorID);
}
-void FusedDepthwiseConvolutionBatchNormalizationNode::set_depthwise_convolution_method(DepthwiseConvolutionMethod method)
+void FusedDepthwiseConvolutionBatchNormalizationNode::set_depthwise_convolution_method(
+ DepthwiseConvolutionMethod method)
{
_method = method;
}
@@ -78,10 +84,11 @@
_fused_activation = fused_activation;
}
-TensorDescriptor FusedDepthwiseConvolutionBatchNormalizationNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
- const TensorDescriptor &weights_descriptor,
- const PadStrideInfo &info,
- int depth_multiplier)
+TensorDescriptor
+FusedDepthwiseConvolutionBatchNormalizationNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
+ const TensorDescriptor &weights_descriptor,
+ const PadStrideInfo &info,
+ int depth_multiplier)
{
unsigned int output_width = 0;
unsigned int output_height = 0;
@@ -92,19 +99,22 @@
const unsigned int kernel_width = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH);
const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT);
- std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
+ std::tie(output_width, output_height) =
+ scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
TensorDescriptor output_descriptor = input_descriptor;
output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::WIDTH), output_width);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::HEIGHT), output_height);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::CHANNEL), input_channels * depth_multiplier);
+ output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::HEIGHT),
+ output_height);
+ output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::CHANNEL),
+ input_channels * depth_multiplier);
return output_descriptor;
}
bool FusedDepthwiseConvolutionBatchNormalizationNode::forward_descriptors()
{
- if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID))
+ if ((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID))
{
Tensor *dst = output(0);
ARM_COMPUTE_ERROR_ON(dst == nullptr);