format files

src/framework/op_registry.h

@@ -108,7 +108,7 @@ class OpRegistry {
       __op_registrar_##op_type##_##device_name(#op_type);                  \
   int TouchOpRegistrar_##op_type##_##device_name() {                       \
     __op_registrar_##op_type##_##device_name.Touch();                      \
-    printf(" registering !! \n");        \
+    printf(" registering !! \n");                                          \
     return 0;                                                              \
   }
 

src/io/executor.cpp

@@ -355,8 +355,9 @@ std::shared_ptr<framework::Tensor> Executor<Dtype, P>::Predict(
     const auto &pInfo = profile[i];
     uint64_t timeCost = pInfo.runEnd - pInfo.runBegin;
     _tp[ops[i]->Type()] += timeCost;
-  //    fprintf(pf, "%d\t%s\t%d\t%llu\t%llu\t%llu\n", i, ops[i]->Type().c_str(),
-  //            pInfo.tid, pInfo.runBegin, pInfo.runEnd, timeCost);
+    //    fprintf(pf, "%d\t%s\t%d\t%llu\t%llu\t%llu\n", i,
+    //    ops[i]->Type().c_str(),
+    //            pInfo.tid, pInfo.runBegin, pInfo.runEnd, timeCost);
   }
   //  fclose(pf);
 

src/io/paddle_mobile.cpp

@@ -75,7 +75,7 @@ void PaddleMobile<Dtype, P>::Clear() {
 }
 
 template <typename Dtype, Precision P>
-PaddleMobile<Dtype, P>::~PaddleMobile(){
+PaddleMobile<Dtype, P>::~PaddleMobile() {
   executor_ = nullptr;
   loader_ = nullptr;
 }

src/io/paddle_mobile.h

@@ -61,6 +61,7 @@ class PaddleMobile {
   void Clear();
 
   ~PaddleMobile();
+
  private:
   std::shared_ptr<Loader<Dtype, P>> loader_;
   std::shared_ptr<Executor<Dtype, P>> executor_;

src/ios_io/PaddleMobile.h

 /* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
- 
+
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
- 
+
  http://www.apache.org/licenses/LICENSE-2.0
- 
+
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

src/ios_io/PaddleMobile.mm

 /* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
- 
+
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
- 
+
  http://www.apache.org/licenses/LICENSE-2.0
- 
+
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

src/operators/fetch_op.cpp

@@ -29,5 +29,3 @@ REGISTER_OPERATOR_MALI_GPU(fetch, ops::FetchOp);
 #endif
 #ifdef PADDLE_MOBILE_FPGA
 #endif
-
-

src/operators/fetch_op.h

@@ -44,7 +44,6 @@ class FetchOp : public framework::OperatorBase<DeviceType> {
   FetchParam param_;
 };
 
-
 }  // namespace operators
 }  // namespace paddle_mobile
 

src/operators/fusion_conv_add.cpp

@@ -48,8 +48,7 @@ void FusionConvAddOp<Dtype, T>::InferShape() const {
 #ifdef PADDLE_MOBILE_CPU
 
 #ifndef CONV_ADD_REGISTER
-framework::FusionOpRegistrar convadd_registrar(
-        new FusionConvAddMatcher());
+framework::FusionOpRegistrar convadd_registrar(new FusionConvAddMatcher());
 #define CONV_ADD_REGISTER
 #endif
 

src/operators/im2sequence_op.h

@@ -59,4 +59,3 @@ USE_OP_CPU(im2sequence);
 #endif
 
 #endif
-

src/operators/kernel/central-arm-func/batchnorm_arm_func.h

@@ -231,37 +231,35 @@ void BatchnormCompute(const BatchNormParam &param) {
   }
 #endif
   float *inv_std_ptr = new float[C];
-    for (int i = 0; i < C; i++) {
-      inv_std_ptr[i] =
-          1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5));
-    }
-
-    Tensor new_scale;
-    auto new_scale_ptr =
-        new_scale.mutable_data<float>(framework::make_ddim({C}));
-    Tensor new_bias;
-    auto new_bias_ptr = new_bias.mutable_data<float>(framework::make_ddim({C}));
+  for (int i = 0; i < C; i++) {
+    inv_std_ptr[i] =
+        1 / static_cast<float>(pow((variance_ptr[i] + epsilon), 0.5));
+  }
 
-    /// ((x - est_mean) * (inv_var) * scale + bias equal to
-    /// (x * inv_var * scale) + (bias - est_mean * inv_var * scale)
-    for (int i = 0; i < C; i++) {
-      new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i];
-      new_bias_ptr[i] =
-          bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i];
-      {
-        for (int n = 0; n < N; n++) {
-          for (int h = 0; h < H; h++) {
-            int tmp_index = n * stride0 + i * stride1 + h * stride2;
-            for (int w = 0; w < W; w++) {
-              int index = tmp_index + w;
-              out_ptr[index] =
-                  input_x_ptr[index] * new_scale_ptr[i] + new_bias_ptr[i];
-            }
+  Tensor new_scale;
+  auto new_scale_ptr = new_scale.mutable_data<float>(framework::make_ddim({C}));
+  Tensor new_bias;
+  auto new_bias_ptr = new_bias.mutable_data<float>(framework::make_ddim({C}));
+
+  /// ((x - est_mean) * (inv_var) * scale + bias equal to
+  /// (x * inv_var * scale) + (bias - est_mean * inv_var * scale)
+  for (int i = 0; i < C; i++) {
+    new_scale_ptr[i] = inv_std_ptr[i] * scale_ptr[i];
+    new_bias_ptr[i] = bias_ptr[i] - mean_ptr[i] * inv_std_ptr[i] * scale_ptr[i];
+    {
+      for (int n = 0; n < N; n++) {
+        for (int h = 0; h < H; h++) {
+          int tmp_index = n * stride0 + i * stride1 + h * stride2;
+          for (int w = 0; w < W; w++) {
+            int index = tmp_index + w;
+            out_ptr[index] =
+                input_x_ptr[index] * new_scale_ptr[i] + new_bias_ptr[i];
           }
         }
       }
     }
-    delete[] inv_std_ptr;
+  }
+  delete[] inv_std_ptr;
 }
 
 }  // namespace operators

src/operators/math/gemm.cpp

@@ -129,14 +129,13 @@ void PackMatrixB_(int k, int n, int n_tail, const float *B, int ldb,
     }
 #else
     for (i = 0; i < k; ++i) {
-        Bij = &B(i, j);
-        *buffer++ = *Bij;
-        *buffer++ = *(Bij + 1);
-        *buffer++ = *(Bij + 2);
-        *buffer++ = *(Bij + 3);
-      }
+      Bij = &B(i, j);
+      *buffer++ = *Bij;
+      *buffer++ = *(Bij + 1);
+      *buffer++ = *(Bij + 2);
+      *buffer++ = *(Bij + 3);
+    }
 #endif
-
   }
   if (n_tail != 0) {
     for (i = 0; i < k; ++i) {

src/operators/math/pool_2x2.cpp

@@ -102,7 +102,7 @@ void Pool2x2Avg(vector<int> strides, vector<int> paddings, const Tensor *input,
 #if __ARM_NEON
 
 #ifdef ARMV7
-const int batch_size = input->dims()[0];
+  const int batch_size = input->dims()[0];
 
   const int input_height = input->dims()[2];
 
@@ -173,7 +173,7 @@ const int batch_size = input->dims()[0];
   }
 #else
 
-  //TODO(): to imp other asm
+// TODO(): to imp other asm
 
 #endif
 

src/operators/math/pooling.cpp

@@ -57,7 +57,7 @@ class PoolFunctor<CPU, PoolProcess, T> {
     T *output_data = output->mutable_data<T>();
 
     for (int i = 0; i < batch_size; i++) {
-      #pragma omp parallel for
+      // <TRICKY-CLANG-FORMAT-PRAGMA-FIX> #pragma omp parallel for
       for (int c = 0; c < output_channels; ++c) {
         for (int ph = 0; ph < output_height; ++ph) {
           int hstart = ph * stride_height - padding_height;

src/operators/transpose_op.h

@@ -50,7 +50,6 @@ class TransposeOp : public framework::OperatorWithKernel<
 }  // namespace operators
 }  // namespace paddle_mobile
 
-
 #ifdef PADDLE_MOBILE_CPU
 USE_OP_CPU(transpose);
 #endif

test/common/test_openmp.cpp

@@ -17,7 +17,7 @@ limitations under the License. */
 
 int main(void) {
 #ifdef PADDLE_MOBILE_USE_OPENMP
-  #pragma omp parallel num_threads(2)
+  // <TRICKY-CLANG-FORMAT-PRAGMA-FIX> #pragma omp parallel num_threads(2)
   {
     //        int thread_id = omp_get_thread_num();
     //        int nthreads = omp_get_num_threads();