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, 81 insertions, 62 deletions

diff --git a/src/cpu/kernels/fuse_batch_normalization/nhwc/neon/impl.h b/src/cpu/kernels/fuse_batch_normalization/nhwc/neon/impl.h
index 6f0386276f..5b74a7aef6 100644
--- a/src/cpu/kernels/fuse_batch_normalization/nhwc/neon/impl.h
+++ b/src/cpu/kernels/fuse_batch_normalization/nhwc/neon/impl.h
@@ -25,6 +25,7 @@
 #define SRC_CORE_NEON_KERNELS_FUSE_BATCH_NORMALIZATION_IMPL_H
 
 #include "arm_compute/core/Helpers.h"
+
 #include "src/core/NEON/wrapper/wrapper.h"
 
 namespace arm_compute
@@ -32,8 +33,16 @@ namespace arm_compute
 namespace cpu
 {
 template <typename T>
-void fused_batch_normalization_dwc_nhwc(const ITensor *dwc_weights, const ITensor *dwc_bias, ITensor *fused_weights, ITensor *fused_bias,
-                                        const ITensor *bn_mean, const ITensor *bn_var, const ITensor *bn_beta, const ITensor *bn_gamma, float epsilon, const Window &window)
+void fused_batch_normalization_dwc_nhwc(const ITensor *dwc_weights,
+                                        const ITensor *dwc_bias,
+                                        ITensor       *fused_weights,
+                                        ITensor       *fused_bias,
+                                        const ITensor *bn_mean,
+                                        const ITensor *bn_var,
+                                        const ITensor *bn_beta,
+                                        const ITensor *bn_gamma,
+                                        float          epsilon,
+                                        const Window  &window)
 {
     using ScalarType   = T;
     const int size     = 16 / dwc_weights->info()->element_size();
@@ -53,13 +62,20 @@ void fused_batch_normalization_dwc_nhwc(const ITensor *dwc_weights, const ITenso
     Iterator dwc_w_in(dwc_weights, win);
     Iterator dwc_w_out(run_in_place_weights ? dwc_weights : fused_weights, win);
 
-    const auto dwc_bias_in  = (dwc_bias != nullptr ? reinterpret_cast<ScalarType *>(dwc_bias->ptr_to_element(Coordinates(0, 0))) : nullptr);
-    auto       dwc_bias_out = (run_in_place_bias ? dwc_bias_in : reinterpret_cast<ScalarType *>(fused_bias->ptr_to_element(Coordinates(0, 0))));
+    const auto dwc_bias_in =
+        (dwc_bias != nullptr ? reinterpret_cast<ScalarType *>(dwc_bias->ptr_to_element(Coordinates(0, 0))) : nullptr);
+    auto dwc_bias_out =
+        (run_in_place_bias ? dwc_bias_in
+                           : reinterpret_cast<ScalarType *>(fused_bias->ptr_to_element(Coordinates(0, 0))));
 
     const auto input_mean  = reinterpret_cast<const ScalarType *>(bn_mean->ptr_to_element(Coordinates(0, 0)));
     const auto input_var   = reinterpret_cast<const ScalarType *>(bn_var->ptr_to_element(Coordinates(0, 0)));
-    const auto input_gamma = (bn_gamma != nullptr) ? reinterpret_cast<const ScalarType *>(bn_gamma->ptr_to_element(Coordinates(0, 0))) : nullptr;
-    const auto input_beta  = (bn_beta != nullptr) ? reinterpret_cast<const ScalarType *>(bn_beta->ptr_to_element(Coordinates(0, 0))) : nullptr;
+    const auto input_gamma = (bn_gamma != nullptr)
+                                 ? reinterpret_cast<const ScalarType *>(bn_gamma->ptr_to_element(Coordinates(0, 0)))
+                                 : nullptr;
+    const auto input_beta  = (bn_beta != nullptr)
+                                 ? reinterpret_cast<const ScalarType *>(bn_beta->ptr_to_element(Coordinates(0, 0)))
+                                 : nullptr;
 
     auto       mean_vec     = wrapper::vdup_n(ScalarType(0), ExactTagType{});
     auto       var_vec      = wrapper::vdup_n(ScalarType(0), ExactTagType{});
@@ -73,81 +89,84 @@ void fused_batch_normalization_dwc_nhwc(const ITensor *dwc_weights, const ITenso
     auto beta               = ScalarType(0.0);
     auto dwc_bias_in_scalar = ScalarType(0);
 
-    execute_window_loop(win, [&](const Coordinates & id)
-    {
-        int x = window_start_x;
-        for(; x <= (window_end_x - window_step_x); x += window_step_x)
+    execute_window_loop(
+        win,
+        [&](const Coordinates &id)
         {
-            var_vec = wrapper::vloadq(input_var + x);
-            if(input_gamma != nullptr)
-            {
-                gamma_vec = wrapper::vloadq(input_gamma + x);
-            }
-
-            if((id[2] == 0) && (id[1] == 0))
+            int x = window_start_x;
+            for (; x <= (window_end_x - window_step_x); x += window_step_x)
             {
-                mean_vec = wrapper::vloadq(input_mean + x);
-
-                // Construct vectors
-                if(input_beta != nullptr)
+                var_vec = wrapper::vloadq(input_var + x);
+                if (input_gamma != nullptr)
                 {
-                    beta_vec = wrapper::vloadq(input_beta + x);
+                    gamma_vec = wrapper::vloadq(input_gamma + x);
                 }
 
-                if(dwc_bias_in != nullptr)
+                if ((id[2] == 0) && (id[1] == 0))
                 {
-                    dwc_bias_vec = wrapper::vloadq(dwc_bias_in + x);
+                    mean_vec = wrapper::vloadq(input_mean + x);
+
+                    // Construct vectors
+                    if (input_beta != nullptr)
+                    {
+                        beta_vec = wrapper::vloadq(input_beta + x);
+                    }
+
+                    if (dwc_bias_in != nullptr)
+                    {
+                        dwc_bias_vec = wrapper::vloadq(dwc_bias_in + x);
+                    }
+
+                    auto dwc_bias_tmp_vec = wrapper::vmul(wrapper::vsub(dwc_bias_vec, mean_vec),
+                                                          wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec)));
+                    dwc_bias_tmp_vec      = wrapper::vadd(wrapper::vmul(dwc_bias_tmp_vec, gamma_vec), beta_vec);
+                    wrapper::vstore(dwc_bias_out + x, dwc_bias_tmp_vec);
                 }
 
-                auto dwc_bias_tmp_vec = wrapper::vmul(wrapper::vsub(dwc_bias_vec, mean_vec), wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec)));
-                dwc_bias_tmp_vec      = wrapper::vadd(wrapper::vmul(dwc_bias_tmp_vec, gamma_vec), beta_vec);
-                wrapper::vstore(dwc_bias_out + x, dwc_bias_tmp_vec);
-            }
-
-            auto dwc_w_in_ptr  = reinterpret_cast<const ScalarType *>(dwc_w_in.ptr());
-            auto dwc_w_out_ptr = reinterpret_cast<ScalarType *>(dwc_w_out.ptr());
+                auto dwc_w_in_ptr  = reinterpret_cast<const ScalarType *>(dwc_w_in.ptr());
+                auto dwc_w_out_ptr = reinterpret_cast<ScalarType *>(dwc_w_out.ptr());
 
-            auto wn  = wrapper::vloadq(dwc_w_in_ptr + x);
-            rvar_vec = wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec));
-            wn       = wrapper::vmul(wn, rvar_vec);
-            wn       = wrapper::vmul(wn, gamma_vec);
+                auto wn  = wrapper::vloadq(dwc_w_in_ptr + x);
+                rvar_vec = wrapper::vinvsqrt(wrapper::vadd(var_vec, epsilon_vec));
+                wn       = wrapper::vmul(wn, rvar_vec);
+                wn       = wrapper::vmul(wn, gamma_vec);
 
-            // Store results
-            wrapper::vstore(dwc_w_out_ptr + x, wn);
-        }
-
-        // Compute left-over elements
-        for(; x < window_end_x; ++x)
-        {
-            auto var = input_var[x];
-            if(input_gamma != nullptr)
-            {
-                gamma = input_gamma[x];
+                // Store results
+                wrapper::vstore(dwc_w_out_ptr + x, wn);
             }
 
-            if(id[2] == 0 && id[1] == 0)
+            // Compute left-over elements
+            for (; x < window_end_x; ++x)
             {
-                auto mean = input_mean[x];
-                if(input_beta != nullptr)
+                auto var = input_var[x];
+                if (input_gamma != nullptr)
                 {
-                    beta = input_beta[x];
+                    gamma = input_gamma[x];
                 }
-                if(dwc_bias_in != nullptr)
+
+                if (id[2] == 0 && id[1] == 0)
                 {
-                    dwc_bias_in_scalar = dwc_bias_in[x];
+                    auto mean = input_mean[x];
+                    if (input_beta != nullptr)
+                    {
+                        beta = input_beta[x];
+                    }
+                    if (dwc_bias_in != nullptr)
+                    {
+                        dwc_bias_in_scalar = dwc_bias_in[x];
+                    }
+
+                    auto dwc_bias_tmp_scalar = (dwc_bias_in_scalar - mean) / std::sqrt(var + ScalarType(epsilon));
+                    dwc_bias_out[x]          = (dwc_bias_tmp_scalar * gamma) + beta;
                 }
 
-                auto dwc_bias_tmp_scalar = (dwc_bias_in_scalar - mean) / std::sqrt(var + ScalarType(epsilon));
-                dwc_bias_out[x]          = (dwc_bias_tmp_scalar * gamma) + beta;
-            }
-
-            const auto dwc_w_in_ptr  = reinterpret_cast<const ScalarType *>(dwc_w_in.ptr());
-            auto       dwc_w_out_ptr = reinterpret_cast<ScalarType *>(dwc_w_out.ptr());
+                const auto dwc_w_in_ptr  = reinterpret_cast<const ScalarType *>(dwc_w_in.ptr());
+                auto       dwc_w_out_ptr = reinterpret_cast<ScalarType *>(dwc_w_out.ptr());
 
-            *(dwc_w_out_ptr + x) = *(dwc_w_in_ptr + x) / std::sqrt(var + ScalarType(epsilon)) * gamma;
-        }
-    },
-    dwc_w_in, dwc_w_out);
+                *(dwc_w_out_ptr + x) = *(dwc_w_in_ptr + x) / std::sqrt(var + ScalarType(epsilon)) * gamma;
+            }
+        },
+        dwc_w_in, dwc_w_out);
 }
 } // namespace cpu
 } // namespace arm_compute