From afd38f0c617d6f89b2b4532c6c44f116617e2b6f Mon Sep 17 00:00:00 2001
From: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
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 <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>
---
 src/graph/nodes/FullyConnectedLayer.cpp | 29 +++++++++++++++++------------
 1 file changed, 17 insertions(+), 12 deletions(-)

(limited to 'src/graph/nodes/FullyConnectedLayer.cpp')

diff --git a/src/graph/nodes/FullyConnectedLayer.cpp b/src/graph/nodes/FullyConnectedLayer.cpp
index 6278227878..1eed69ddaf 100644
--- a/src/graph/nodes/FullyConnectedLayer.cpp
+++ b/src/graph/nodes/FullyConnectedLayer.cpp
@@ -21,18 +21,23 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
-#include "arm_compute/graph/nodes/FullyConnectedLayerNode.h"
-
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/graph/Graph.h"
 #include "arm_compute/graph/INodeVisitor.h"
+#include "arm_compute/graph/nodes/FullyConnectedLayerNode.h"
 
 namespace arm_compute
 {
 namespace graph
 {
-FullyConnectedLayerNode::FullyConnectedLayerNode(unsigned int num_outputs, QuantizationInfo out_quant_info, FullyConnectedLayerInfo fc_info, FastMathHint fast_math_hint)
-    : _num_outputs(num_outputs), _out_quant_info(std::move(out_quant_info)), _info(fc_info), _fast_math_hint(fast_math_hint)
+FullyConnectedLayerNode::FullyConnectedLayerNode(unsigned int            num_outputs,
+                                                 QuantizationInfo        out_quant_info,
+                                                 FullyConnectedLayerInfo fc_info,
+                                                 FastMathHint            fast_math_hint)
+    : _num_outputs(num_outputs),
+      _out_quant_info(std::move(out_quant_info)),
+      _info(fc_info),
+      _fast_math_hint(fast_math_hint)
 {
     _input_edges.resize(3, EmptyEdgeID);
     _outputs.resize(1, NullTensorID);
@@ -60,11 +65,11 @@ TensorDescriptor FullyConnectedLayerNode::compute_weights_descriptor(const Tenso
     unsigned int num_weights    = 1;
     unsigned int num_dimensions = input_descriptor.shape.num_dimensions();
     // Ignore the batch dimension if there is one:
-    if(num_dimensions == 2 || num_dimensions == 4)
+    if (num_dimensions == 2 || num_dimensions == 4)
     {
         num_dimensions--;
     }
-    for(unsigned int i = 0; i < num_dimensions; i++)
+    for (unsigned int i = 0; i < num_dimensions; i++)
     {
         num_weights *= input_descriptor.shape[i];
     }
@@ -73,13 +78,13 @@ TensorDescriptor FullyConnectedLayerNode::compute_weights_descriptor(const Tenso
     weights_descriptor.shape            = TensorShape(num_weights, num_outputs);
 
     // If weights are tranposed, use tranposed shape
-    if(!fc_info.transpose_weights)
+    if (!fc_info.transpose_weights)
     {
         weights_descriptor.shape = TensorShape(num_outputs, num_weights);
     }
 
     // Set quantization info if present
-    if(!weights_quant_info.empty())
+    if (!weights_quant_info.empty())
     {
         weights_descriptor.quant_info = weights_quant_info;
     }
@@ -93,7 +98,7 @@ TensorDescriptor FullyConnectedLayerNode::compute_output_descriptor(const Tensor
 {
     // Note: Only 1D batch space is supported at the moment
     unsigned int batches = input_descriptor.shape[1];
-    if(input_descriptor.shape.num_dimensions() > 2)
+    if (input_descriptor.shape.num_dimensions() > 2)
     {
         batches = input_descriptor.shape[3];
     }
@@ -103,7 +108,7 @@ TensorDescriptor FullyConnectedLayerNode::compute_output_descriptor(const Tensor
     output_descriptor.shape            = TensorShape(num_outputs, batches);
 
     // Set quantization info if present
-    if(!out_quant_info.empty())
+    if (!out_quant_info.empty())
     {
         output_descriptor.quant_info = out_quant_info;
     }
@@ -118,7 +123,7 @@ FullyConnectedLayerInfo FullyConnectedLayerNode::info() const
 
 bool FullyConnectedLayerNode::forward_descriptors()
 {
-    if((input_id(0) != NullTensorID) && (output_id(0) != NullTensorID))
+    if ((input_id(0) != NullTensorID) && (output_id(0) != NullTensorID))
     {
         Tensor *dst = output(0);
         ARM_COMPUTE_ERROR_ON(dst == nullptr);
@@ -147,4 +152,4 @@ void FullyConnectedLayerNode::accept(INodeVisitor &v)
     v.visit(*this);
 }
 } // namespace graph
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute
-- 
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