[codemod][caffe2] Run clang-format - 5/7

Summary: This directory is opted-in to clang-format but is not format-clean. This blocks continuous formatting from being enabled on fbcode, and causes hassle for other codemods that leave inconsistent formatting. This diff runs clang-format, which is widely used and considered safe. If you are unhappy with the formatting of a particular block, please *accept this diff* and then in a stacked commit undo the change and wrap that code in `// clang-format off` and `// clang-format on`, or `/* clang-format off */` and `/* clang-format on */`. drop-conflicts Test Plan: sandcastleit Reviewed By: jerryzh168 Differential Revision: D22311706 fbshipit-source-id: 1ca59a82e96156a4a5dfad70ba3e64d44c5e762a
Knightfire1998 · Jun 30, 2020 · 0ddaaf6 · 0ddaaf6
1 parent 29aef8f
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Showing 50 changed files with 341 additions and 257 deletions.
diff --git a/caffe2/mpi/mpi_common.h b/caffe2/mpi/mpi_common.h
@@ -15,12 +15,16 @@ inline void CheckInitializedMPI() {
   CAFFE_ENFORCE(flag, "MPI does not seem to have been initialized.");
 }
 
-template <typename T> class MPIDataTypeWrapper;
-
-#define MPI_DATATYPE_WRAPPER(c_type, mpi_type)                                 \
-  template<> class MPIDataTypeWrapper<c_type> {                                \
-   public:                                                                     \
-    inline static MPI_Datatype type() { return mpi_type; }                     \
+template <typename T>
+class MPIDataTypeWrapper;
+
+#define MPI_DATATYPE_WRAPPER(c_type, mpi_type) \
+  template <>                                  \
+  class MPIDataTypeWrapper<c_type> {           \
+   public:                                     \
+    inline static MPI_Datatype type() {        \
+      return mpi_type;                         \
+    }                                          \
   };
 
 MPI_DATATYPE_WRAPPER(char, MPI_CHAR)
@@ -150,6 +154,6 @@ void MPISetupPeers(
     const int replicas,
     const string& role,
     const string& job_path);
-}  // namespace caffe2
+} // namespace caffe2
 
-#endif  // CAFFE2_MPI_MPI_COMMON_H_
+#endif // CAFFE2_MPI_MPI_COMMON_H_
diff --git a/caffe2/mpi/mpi_ops.h b/caffe2/mpi/mpi_ops.h
@@ -243,6 +243,6 @@ class MPIReceiveTensorOp final : public Operator<Context> {
   OUTPUT_TAGS(OUTPUT, SRC_OUT, TAG_OUT);
 };
 
-}  // namespace caffe2
+} // namespace caffe2
 
-#endif  // CAFFE2_MPI_MPI_OPS_H_
+#endif // CAFFE2_MPI_MPI_OPS_H_
diff --git a/caffe2/observers/runcnt_observer.h b/caffe2/observers/runcnt_observer.h
@@ -9,7 +9,8 @@ namespace caffe2 {
 
 class RunCountNetObserver;
 
-class CAFFE2_API RunCountOperatorObserver final : public ObserverBase<OperatorBase> {
+class CAFFE2_API RunCountOperatorObserver final
+    : public ObserverBase<OperatorBase> {
  public:
   explicit RunCountOperatorObserver(OperatorBase* op) = delete;
   RunCountOperatorObserver(OperatorBase* op, RunCountNetObserver* netObserver);
@@ -26,9 +27,10 @@ class CAFFE2_API RunCountOperatorObserver final : public ObserverBase<OperatorBa
   RunCountNetObserver* netObserver_;
 };
 
-class CAFFE2_API RunCountNetObserver final : public OperatorAttachingNetObserver<
-                                      RunCountOperatorObserver,
-                                      RunCountNetObserver> {
+class CAFFE2_API RunCountNetObserver final
+    : public OperatorAttachingNetObserver<
+          RunCountOperatorObserver,
+          RunCountNetObserver> {
  public:
   explicit RunCountNetObserver(NetBase* subject_)
       : OperatorAttachingNetObserver<

diff --git a/caffe2/observers/time_observer.h b/caffe2/observers/time_observer.h
@@ -28,8 +28,9 @@ class CAFFE2_API TimeCounter {
   int iterations_ = 0;
 };
 
-class CAFFE2_API TimeOperatorObserver final : public TimeCounter,
-                                              public ObserverBase<OperatorBase> {
+class CAFFE2_API TimeOperatorObserver final
+    : public TimeCounter,
+      public ObserverBase<OperatorBase> {
  public:
   explicit TimeOperatorObserver(OperatorBase* subject) = delete;
   explicit TimeOperatorObserver(

diff --git a/caffe2/onnx/backend.h b/caffe2/onnx/backend.h
@@ -113,8 +113,8 @@ ::google::protobuf::RepeatedField<::google::protobuf::int64>
 OnnxAttributes::get(const std::string& key) const;
 
 template <>
-::google::protobuf::RepeatedField<float>
-OnnxAttributes::get(const std::string& key) const;
+::google::protobuf::RepeatedField<float> OnnxAttributes::get(
+    const std::string& key) const;
 
 template <>
 const TensorProto* OnnxAttributes::get(const std::string& key) const;
@@ -137,7 +137,7 @@ class CAFFE2_API Caffe2Backend {
   // from releasing the object
   Caffe2Backend(DummyName* dummy = nullptr) {
     if (dummy) {
-      dummy_ = std::shared_ptr<DummyName>(dummy, [](DummyName *){});
+      dummy_ = std::shared_ptr<DummyName>(dummy, [](DummyName*) {});
     } else {
       dummy_ = std::make_shared<DummyName>();
     }
@@ -173,7 +173,9 @@ class CAFFE2_API Caffe2Backend {
       bool include_initializers,
       const std::vector<Caffe2Ops>& extras);
 
-  void CheckOpSchemaArguments(const caffe2::OpSchema& schema, const caffe2::OperatorDef& op);
+  void CheckOpSchemaArguments(
+      const caffe2::OpSchema& schema,
+      const caffe2::OperatorDef& op);
 
   Caffe2Ops OnnxNodeToCaffe2Ops(
       const ModelProto& init_model,
@@ -217,16 +219,19 @@ class CAFFE2_API Caffe2Backend {
 
   Caffe2Ops CreateSlice(OnnxNode* onnx_node, const ConversionContext& ctx);
 
-  std::string PreprocessSliceIndexTensor(OnnxNode* onnx_node,
-                                                        Caffe2Ops& ret,
-                                                        std::string indices_tensor,
-                                                        std::string axes_tensor,
-                                                        std::string rank_tensor,
-                                                        std::string zero_tensor,
-                                                        std::string one_tensor,
-                                                        int default_value);
-
-  Caffe2Ops CreateDynamicSlice(OnnxNode* onnx_node, const ConversionContext& ctx);
+  std::string PreprocessSliceIndexTensor(
+      OnnxNode* onnx_node,
+      Caffe2Ops& ret,
+      std::string indices_tensor,
+      std::string axes_tensor,
+      std::string rank_tensor,
+      std::string zero_tensor,
+      std::string one_tensor,
+      int default_value);
+
+  Caffe2Ops CreateDynamicSlice(
+      OnnxNode* onnx_node,
+      const ConversionContext& ctx);
 
   Caffe2Ops CreateSplit(OnnxNode* onnx_node, const ConversionContext& ctx);
 
@@ -240,7 +245,9 @@ class CAFFE2_API Caffe2Backend {
 
   Caffe2Ops CreateNonZeroOp(OnnxNode* onnx_node, const ConversionContext& ctx);
 
-  Caffe2Ops CreateMultinomialOp(OnnxNode* onnx_node, const ConversionContext& ctx);
+  Caffe2Ops CreateMultinomialOp(
+      OnnxNode* onnx_node,
+      const ConversionContext& ctx);
 
   Caffe2Ops CreateBatchNormalization(
       OnnxNode* onnx_node,

diff --git a/caffe2/onnx/backend_rep.h b/caffe2/onnx/backend_rep.h
@@ -7,7 +7,8 @@
 #include <string>
 #include <vector>
 
-namespace caffe2 { namespace onnx {
+namespace caffe2 {
+namespace onnx {
 class CAFFE2_API Caffe2BackendRep {
  public:
   void Run(
@@ -45,4 +46,5 @@ class CAFFE2_API Caffe2BackendRep {
   std::vector<std::string> uninitialized_inputs_;
   std::unique_ptr<caffe2::Predictor> predictor_{nullptr};
 };
-}}
+} // namespace onnx
+} // namespace caffe2
diff --git a/caffe2/onnx/device.h b/caffe2/onnx/device.h
@@ -3,21 +3,24 @@
 #include <functional>
 #include <string>
 
-namespace caffe2 { namespace onnx {
+namespace caffe2 {
+namespace onnx {
 
-enum class DeviceType {CPU=0, CUDA=1};
+enum class DeviceType { CPU = 0, CUDA = 1 };
 
 struct Device {
   Device(const std::string& spec);
   DeviceType type;
   int device_id{-1};
 };
 
-}}
+} // namespace onnx
+} // namespace caffe2
 
 namespace std {
-template <> struct hash<caffe2::onnx::DeviceType> {
-  std::size_t operator()(const caffe2::onnx::DeviceType &k) const {
+template <>
+struct hash<caffe2::onnx::DeviceType> {
+  std::size_t operator()(const caffe2::onnx::DeviceType& k) const {
     return std::hash<int>()(static_cast<int>(k));
   }
 };

diff --git a/caffe2/onnx/onnx_exporter.h b/caffe2/onnx/onnx_exporter.h
@@ -52,6 +52,7 @@ class CAFFE2_API OnnxExporter {
       const std::unordered_map<std::string, caffe2::TensorShape>& shapes);
 
   void InitOpToTensorProto(const caffe2::OperatorDef& def, TensorProto* tensor);
+
  private:
   ConvertedResult CommonCaffe2OpToOnnxNodes(const caffe2::OperatorDef& def);
 

diff --git a/caffe2/operators/accuracy_op.h b/caffe2/operators/accuracy_op.h
@@ -18,7 +18,7 @@ class AccuracyOp final : public Operator<Context> {
   bool RunOnDevice() override;
 
  protected:
-  int top_k_; 
+  int top_k_;
   INPUT_TAGS(PREDICTION, LABEL);
 };
 

diff --git a/caffe2/operators/affine_channel_op.h b/caffe2/operators/affine_channel_op.h
@@ -71,8 +71,7 @@ class AffineChannelOp final : public Operator<Context> {
     const int N = X.dim32(0);
     const int C = X.dim32(ndim - 1);
     const int HxW = X.numel() / (N * C);
-    auto* Y =
-        Output(0, X.sizes(), at::dtype<T>());
+    auto* Y = Output(0, X.sizes(), at::dtype<T>());
     math::AffineChannel<T, Context, StorageOrder::NHWC>(
         N,
         C,

diff --git a/caffe2/operators/bbox_transform_op.h b/caffe2/operators/bbox_transform_op.h
@@ -3,8 +3,8 @@
 #ifndef BBOX_TRANSFORM_OP_H_
 #define BBOX_TRANSFORM_OP_H_
 
-#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/context.h"
+#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/logging.h"
 #include "caffe2/core/operator.h"
 #include "caffe2/utils/math.h"

diff --git a/caffe2/operators/box_with_nms_limit_op.h b/caffe2/operators/box_with_nms_limit_op.h
@@ -3,8 +3,8 @@
 #ifndef BOX_WITH_NMS_AND_LIMIT_OP_H_
 #define BOX_WITH_NMS_AND_LIMIT_OP_H_
 
-#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/context.h"
+#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/operator.h"
 
 C10_DECLARE_EXPORT_CAFFE2_OP_TO_C10(BoxWithNMSLimit)

diff --git a/caffe2/operators/cast_op.h b/caffe2/operators/cast_op.h
@@ -1,12 +1,12 @@
 #pragma once
 
 #include "caffe2/core/context.h"
+#include "caffe2/core/logging.h"
 #include "caffe2/core/operator.h"
+#include "caffe2/core/types.h"
 #include "caffe2/utils/cast.h"
 #include "caffe2/utils/conversions.h"
 #include "caffe2/utils/math.h"
-#include "caffe2/core/logging.h"
-#include "caffe2/core/types.h"
 
 namespace caffe2 {
 
@@ -52,4 +52,4 @@ class CastOp : public Operator<Context> {
   bool (CastOp::*body_)();
 };
 
-}  // namespace caffe2
+} // namespace caffe2
diff --git a/caffe2/operators/collect_and_distribute_fpn_rpn_proposals_op.h b/caffe2/operators/collect_and_distribute_fpn_rpn_proposals_op.h
@@ -1,8 +1,8 @@
 #ifndef CAFFE2_OPERATORS_COLLECT_AND_DISTRIBUTE_FPN_RPN_PROPOSALS_OP_H_
 #define CAFFE2_OPERATORS_COLLECT_AND_DISTRIBUTE_FPN_RPN_PROPOSALS_OP_H_
 
-#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/context.h"
+#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/operator.h"
 #include "caffe2/utils/eigen_utils.h"
 #include "caffe2/utils/math.h"

diff --git a/caffe2/operators/conditional_op.h b/caffe2/operators/conditional_op.h
@@ -19,6 +19,6 @@ class ConditionalOp final : public Operator<Context> {
   bool RunOnDevice() override;
 };
 
-} // caffe2
+} // namespace caffe2
 
 #endif
diff --git a/caffe2/operators/conv_transpose_op_mobile.h b/caffe2/operators/conv_transpose_op_mobile.h
@@ -17,7 +17,9 @@ class ConvTransposeMobileOp final : public ConvTransposeUnpoolBase<Context> {
   USE_CONV_TRANSPOSE_UNPOOL_BASE_FUNCTIONS(Context);
   ConvTransposeMobileOp(const OperatorDef& operator_def, Workspace* ws)
       : ConvTransposeUnpoolBase<Context>(operator_def, ws) {
-    OPERATOR_NEEDS_FEATURE(order_ == StorageOrder::NCHW, "Only NCHW order is supported right now.");
+    OPERATOR_NEEDS_FEATURE(
+        order_ == StorageOrder::NCHW,
+        "Only NCHW order is supported right now.");
     OPERATOR_NEEDS_FEATURE(
         this->pad_l() == 0, "operator does not handle row width padding");
     OPERATOR_NEEDS_FEATURE(
@@ -29,8 +31,8 @@ class ConvTransposeMobileOp final : public ConvTransposeUnpoolBase<Context> {
   bool RunOnDeviceWithOrderNHWC() override;
 
  private:
-  // We store a numThreasds per-worker  tiles of Y, and numThreads per-worker threadBuffer for the
-  // gemm output, laid out in that order.
+  // We store a numThreasds per-worker  tiles of Y, and numThreads per-worker
+  // threadBuffer for the gemm output, laid out in that order.
   Tensor threadBuffer_{CPU};
 
   // Input: X, W, b

diff --git a/caffe2/operators/create_scope_op.h b/caffe2/operators/create_scope_op.h
@@ -149,7 +149,7 @@ class CAFFE2_API WorkspaceStack {
   int top_;
   std::vector<std::shared_ptr<Workspace>> workspaces_;
 };
-}
+} // namespace detail
 
 template <class Context>
 class CreateScopeOp final : public Operator<Context> {

diff --git a/caffe2/operators/deform_conv_op_impl.h b/caffe2/operators/deform_conv_op_impl.h
@@ -136,7 +136,22 @@ bool DeformConvOp<T, Context>::RunOnDeviceWithOrderNCHW() {
     bias_data = Input(BIAS).template data<T>();
   }
 
-  auto f = [this, &filter_offset, &bias_data, &X, &buffer_shape, &N, &Xdata, &offset_data, &M, &filter, &output_image_size, &kernel_dim, &Ydata, &input_offset, &offset_offset, &output_offset] (Tensor* col_buffer) {
+  auto f = [this,
+            &filter_offset,
+            &bias_data,
+            &X,
+            &buffer_shape,
+            &N,
+            &Xdata,
+            &offset_data,
+            &M,
+            &filter,
+            &output_image_size,
+            &kernel_dim,
+            &Ydata,
+            &input_offset,
+            &offset_offset,
+            &output_offset](Tensor* col_buffer) {
     col_buffer->Resize(buffer_shape);
     T* col_buffer_data = col_buffer->template mutable_data<T>();
     // Im2col, followed by gemm.
@@ -196,8 +211,7 @@ bool DeformConvGradientOp<T, Context>::RunOnDeviceWithOrderNCHW() {
   auto& offset = Input(OFFSET);
   auto& filter = Input(FILTER);
   auto& dY = Input(OUTPUT_GRAD);
-
-
+
   const int N = X.dim32(0), C = X.dim32(1);
 
   const vector<int> input_dims = this->GetDims(X);
@@ -303,7 +317,6 @@ bool DeformConvGradientOp<T, Context>::RunOnDeviceWithOrderNCHW() {
 
   T* dbias_data = nullptr;
   if (!no_bias_) {
-
     auto* dbias = Output(BIAS_OR_INPUT_GRAD, {M}, at::dtype<T>());
     if (bias_multiplier_.numel() != output_image_size) {
       // If the helper bias multiplier is not M, reshape and fill it with one.
@@ -323,8 +336,8 @@ bool DeformConvGradientOp<T, Context>::RunOnDeviceWithOrderNCHW() {
 
   T* dXdata = nullptr;
   if (OutputSize() == 4 || (no_bias_ && (OutputSize() == 3))) {
-
-    auto* dX = Output(no_bias_ ? BIAS_OR_INPUT_GRAD : INPUT_GRAD, X.sizes(), at::dtype<T>());
+    auto* dX = Output(
+        no_bias_ ? BIAS_OR_INPUT_GRAD : INPUT_GRAD, X.sizes(), at::dtype<T>());
     dXdata = dX->template mutable_data<T>();
     math::Set<T, Context>(dX->numel(), 0, dXdata, &context_);
   }

diff --git a/caffe2/operators/elementwise_linear_op.h b/caffe2/operators/elementwise_linear_op.h
@@ -38,4 +38,4 @@ class ElementwiseLinearGradientOp final : public Operator<Context> {
 
 } // namespace caffe2
 
-#endif  // CAFFE2_OPERATORS_ELEMENTWISE_LINEAR_OP_H_
+#endif // CAFFE2_OPERATORS_ELEMENTWISE_LINEAR_OP_H_
Original file line number	Diff line number	Diff line change
Expand Up		@@ -38,4 +38,4 @@ class ElementwiseLinearGradientOp final : public Operator<Context> {

		} // namespace caffe2

		#endif // CAFFE2_OPERATORS_ELEMENTWISE_LINEAR_OP_H_
		#endif // CAFFE2_OPERATORS_ELEMENTWISE_LINEAR_OP_H_