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>

1 files changed, 29 insertions, 25 deletions

diff --git a/arm_compute/core/utils/misc/InfoHelpers.h b/arm_compute/core/utils/misc/InfoHelpers.h
index ced0d24b56..1d1b4ea8d7 100644
--- a/arm_compute/core/utils/misc/InfoHelpers.h
+++ b/arm_compute/core/utils/misc/InfoHelpers.h
@@ -53,10 +53,12 @@ inline bool is_relu(ActivationLayerInfo activation_info)
  */
 inline bool is_relu6(ActivationLayerInfo activation_info)
 {
-    const bool is_lu_bounded_relu = activation_info.activation() == ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU
-                                    && activation_info.a() == 6.f && activation_info.b() == 0.f;
-    const bool is_bounded_relu = activation_info.activation() == ActivationLayerInfo::ActivationFunction::BOUNDED_RELU
-                                 && activation_info.a() == 6.f;
+    const bool is_lu_bounded_relu =
+        activation_info.activation() == ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU &&
+        activation_info.a() == 6.f && activation_info.b() == 0.f;
+    const bool is_bounded_relu =
+        activation_info.activation() == ActivationLayerInfo::ActivationFunction::BOUNDED_RELU &&
+        activation_info.a() == 6.f;
     return activation_info.enabled() && (is_lu_bounded_relu || is_bounded_relu);
 }
 
@@ -68,34 +70,37 @@ inline bool is_relu6(ActivationLayerInfo activation_info)
  *
  */
 template <typename T>
-inline void build_lstm_params_tensor_info(const LSTMParams<T>     &lstm_params,
-                                          LSTMParams<ITensorInfo> *lstm_params_info)
+inline void build_lstm_params_tensor_info(const LSTMParams<T> &lstm_params, LSTMParams<ITensorInfo> *lstm_params_info)
 {
-    if(lstm_params.has_peephole_opt())
+    if (lstm_params.has_peephole_opt())
     {
         ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.cell_to_forget_weights(), lstm_params.cell_to_output_weights());
-        lstm_params_info->set_peephole_params(lstm_params.cell_to_forget_weights()->info(), lstm_params.cell_to_output_weights()->info());
+        lstm_params_info->set_peephole_params(lstm_params.cell_to_forget_weights()->info(),
+                                              lstm_params.cell_to_output_weights()->info());
     }
-    if(lstm_params.has_projection())
+    if (lstm_params.has_projection())
     {
         ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.projection_weights());
-        lstm_params_info->set_projection_params(lstm_params.projection_weights()->info(),
-                                                lstm_params.projection_bias() != nullptr ? lstm_params.projection_bias()->info() : nullptr);
+        lstm_params_info->set_projection_params(
+            lstm_params.projection_weights()->info(),
+            lstm_params.projection_bias() != nullptr ? lstm_params.projection_bias()->info() : nullptr);
     }
-    if(!lstm_params.has_cifg_opt())
+    if (!lstm_params.has_cifg_opt())
     {
-        ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.input_to_input_weights(), lstm_params.recurrent_to_input_weights(), lstm_params.input_gate_bias());
+        ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.input_to_input_weights(), lstm_params.recurrent_to_input_weights(),
+                                     lstm_params.input_gate_bias());
 
-        ITensorInfo *cell_to_input_weights_info = (lstm_params.has_peephole_opt()) ? lstm_params.cell_to_input_weights()->info() : nullptr;
-        lstm_params_info->set_cifg_params(lstm_params.input_to_input_weights()->info(), lstm_params.recurrent_to_input_weights()->info(),
-                                          cell_to_input_weights_info, lstm_params.input_gate_bias()->info());
+        ITensorInfo *cell_to_input_weights_info =
+            (lstm_params.has_peephole_opt()) ? lstm_params.cell_to_input_weights()->info() : nullptr;
+        lstm_params_info->set_cifg_params(lstm_params.input_to_input_weights()->info(),
+                                          lstm_params.recurrent_to_input_weights()->info(), cell_to_input_weights_info,
+                                          lstm_params.input_gate_bias()->info());
     }
-    if(lstm_params.use_layer_norm())
+    if (lstm_params.use_layer_norm())
     {
-        ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.forget_layer_norm_weights(),
-                                     lstm_params.output_layer_norm_weights(),
+        ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.forget_layer_norm_weights(), lstm_params.output_layer_norm_weights(),
                                      lstm_params.cell_layer_norm_weights());
-        if(!lstm_params.has_cifg_opt())
+        if (!lstm_params.has_cifg_opt())
         {
             ARM_COMPUTE_ERROR_ON_NULLPTR(lstm_params.input_layer_norm_weights());
         }
@@ -103,15 +108,14 @@ inline void build_lstm_params_tensor_info(const LSTMParams<T>     &lstm_params,
         ITensorInfo *forget_info = lstm_params.forget_layer_norm_weights()->info();
         ITensorInfo *cell_info   = lstm_params.cell_layer_norm_weights()->info();
         ITensorInfo *output_info = lstm_params.output_layer_norm_weights()->info();
-        ITensorInfo *input_info  = lstm_params.has_cifg_opt() ? nullptr : lstm_params.input_layer_norm_weights()->info();
+        ITensorInfo *input_info = lstm_params.has_cifg_opt() ? nullptr : lstm_params.input_layer_norm_weights()->info();
 
         lstm_params_info->set_layer_normalization_params(input_info, forget_info, cell_info, output_info);
     }
 
-    lstm_params_info->set_matmul_scale_params(lstm_params.input_intermediate_scale(),
-                                              lstm_params.forget_intermediate_scale(),
-                                              lstm_params.cell_intermediate_scale(),
-                                              lstm_params.output_intermediate_scale());
+    lstm_params_info->set_matmul_scale_params(
+        lstm_params.input_intermediate_scale(), lstm_params.forget_intermediate_scale(),
+        lstm_params.cell_intermediate_scale(), lstm_params.output_intermediate_scale());
 
     lstm_params_info->set_hidden_state_params(lstm_params.hidden_state_zero(), lstm_params.hidden_state_scale());
 }