format: apply clang-format and autopep

.clang-format

@@ -0,0 +1,5 @@
+---
+BasedOnStyle: Google
+---
+Language: Cpp
+ColumnLimit: 80

byteps/_keras/__init__.py

@@ -99,4 +99,4 @@ def load_model(keras, wrap_optimizer, filepath, custom_optimizers, custom_object
     if custom_objects is not None:
         byteps_objects.update(custom_objects)
 
-    return keras.models.load_model(filepath, custom_objects=byteps_objects)
+    return keras.models.load_model(filepath, custom_objects=byteps_objects)

byteps/_keras/callbacks.py

@@ -112,7 +112,7 @@ def _adjust_learning_rate(self, epoch):
             # See the paper cited above for more information about momentum correction.
             self.restore_momentum = self.backend.get_value(self.model.optimizer.momentum)
             self.backend.set_value(self.model.optimizer.momentum,
-                        self.restore_momentum * new_lr / old_lr)
+                                   self.restore_momentum * new_lr / old_lr)
 
     def _restore_momentum_if_needed(self):
         if self.restore_momentum:
@@ -168,4 +168,4 @@ def on_epoch_end(self, epoch, logs=None):
         if epoch == self.end_epoch - 1 and self.verbose > 0:
             new_lr = self.backend.get_value(self.model.optimizer.lr)
             print('\nEpoch %d: finished gradual learning rate warmup to %g.' %
-                  (epoch + 1, new_lr))
+                  (epoch + 1, new_lr))

byteps/common/common.cc

@@ -14,8 +14,8 @@
 // limitations under the License.
 // =============================================================================
 
-#include <sstream>
 #include <cassert>
+#include <sstream>
 
 #include "common.h"
 #include "logging.h"
@@ -30,9 +30,7 @@ Status::Status(StatusType type, std::string reason) {
   reason_ = reason;
 }
 
-Status Status::OK() {
-  return Status();
-}
+Status Status::OK() { return Status(); }
 
 Status Status::UnknownError(std::string message) {
   return Status(StatusType::UNKNOWN_ERROR, message);
@@ -50,29 +48,17 @@ Status Status::InvalidArgument(std::string message) {
   return Status(StatusType::INVALID_ARGUMENT, message);
 }
 
-Status Status::InProgress() {
-  return Status(StatusType::IN_PROGRESS, "");
-}
+Status Status::InProgress() { return Status(StatusType::IN_PROGRESS, ""); }
 
-bool Status::ok() const {
-  return type_ == StatusType::OK;
-}
+bool Status::ok() const { return type_ == StatusType::OK; }
 
-bool Status::in_progress() const {
-  return type_ == StatusType::IN_PROGRESS;
-}
+bool Status::in_progress() const { return type_ == StatusType::IN_PROGRESS; }
 
-StatusType Status::type() const {
-  return type_;
-}
+StatusType Status::type() const { return type_; }
 
-const std::string& Status::reason() const {
-  return reason_;
-}
+const std::string& Status::reason() const { return reason_; }
 
-void TensorShape::AddDim(int64_t dim) {
-  shape_.push_back(dim);
-}
+void TensorShape::AddDim(int64_t dim) { shape_.push_back(dim); }
 
 void TensorShape::AppendShape(TensorShape& other) {
   for (auto dim : other.shape_) {
@@ -93,9 +79,7 @@ const std::string TensorShape::DebugString() const {
   return args.str();
 }
 
-int TensorShape::dims() const {
-  return (int)shape_.size();
-}
+int TensorShape::dims() const { return (int)shape_.size(); }
 
 int64_t TensorShape::dim_size(int idx) const {
   assert(idx >= 0);
@@ -157,5 +141,5 @@ int getDataTypeLength(int dtype) {
   return 4;
 }
 
-} // namespace common
-} // namespace byteps
+}  // namespace common
+}  // namespace byteps

byteps/common/common.h

@@ -17,15 +17,15 @@
 #ifndef BYTEPS_COMMON_H
 #define BYTEPS_COMMON_H
 
+#include <cuda_runtime.h>
+#include <nccl.h>
+#include <atomic>
 #include <functional>
 #include <memory>
+#include <mutex>
 #include <string>
 #include <unordered_map>
-#include <atomic>
 #include <vector>
-#include <mutex>
-#include <nccl.h>
-#include <cuda_runtime.h>
 
 namespace byteps {
 namespace common {
@@ -54,25 +54,41 @@ enum DataType {
 // List of supported frameworks.
 enum Framework { TENSORFLOW, PYTORCH, MXNET };
 
-enum StatusType { OK, UNKNOWN_ERROR, PRECONDITION_ERROR, ABORTED, INVALID_ARGUMENT, IN_PROGRESS };
+enum StatusType {
+  OK,
+  UNKNOWN_ERROR,
+  PRECONDITION_ERROR,
+  ABORTED,
+  INVALID_ARGUMENT,
+  IN_PROGRESS
+};
 
 enum DeviceType { CPU, GPU };
 
-enum QueueType { COORDINATE_REDUCE, REDUCE, COPYD2H,
-                 PCIE_REDUCE, COORDINATE_PUSH, PUSH, PULL,
-                 COPYH2D, COORDINATE_BROADCAST, BROADCAST,
-                 QUEUE_NUM_AND_NOT_A_REAL_QUEUE_TYPE_AND_MUST_BE_THE_LAST };
+enum QueueType {
+  COORDINATE_REDUCE,
+  REDUCE,
+  COPYD2H,
+  PCIE_REDUCE,
+  COORDINATE_PUSH,
+  PUSH,
+  PULL,
+  COPYH2D,
+  COORDINATE_BROADCAST,
+  BROADCAST,
+  QUEUE_NUM_AND_NOT_A_REAL_QUEUE_TYPE_AND_MUST_BE_THE_LAST
+};
 
-const int QueueNum = (int)QUEUE_NUM_AND_NOT_A_REAL_QUEUE_TYPE_AND_MUST_BE_THE_LAST;
+const int QueueNum =
+    (int)QUEUE_NUM_AND_NOT_A_REAL_QUEUE_TYPE_AND_MUST_BE_THE_LAST;
 
 const std::vector<std::string> LogStrings = {
-  "COORDINATE_REDUCE", "REDUCE", "COPYD2H",
-  "PCIE_REDUCE", "COORDINATE_PUSH", "PUSH", "PULL",
-  "COPYH2D", "COORDINATE_BROADCAST", "BROADCAST"
-};
+    "COORDINATE_REDUCE",    "REDUCE",   "COPYD2H", "PCIE_REDUCE",
+    "COORDINATE_PUSH",      "PUSH",     "PULL",    "COPYH2D",
+    "COORDINATE_BROADCAST", "BROADCAST"};
 
 class Status {
-public:
+ public:
   Status();
   static Status OK();
   static Status UnknownError(std::string message);
@@ -85,14 +101,14 @@ class Status {
   StatusType type() const;
   const std::string& reason() const;
 
-private:
+ private:
   StatusType type_ = StatusType::OK;
   std::string reason_ = "";
   Status(StatusType type, std::string reason);
 };
 
 class TensorShape {
-public:
+ public:
   void AddDim(int64_t dim);
   void AppendShape(TensorShape& other);
 
@@ -109,36 +125,36 @@ class TensorShape {
     return shape_ != rhs.shape_;
   }
 
-private:
+ private:
   std::vector<int64_t> shape_;
 };
 
 class ReadyEvent {
-public:
+ public:
   virtual bool Ready() const = 0;
   virtual ~ReadyEvent() = default;
 };
 
 typedef struct BytePSContext {
-    bool initialized;
-    std::mutex init_mutex;
-    // tensor name
-    std::string tensor_name;
-    // using ps::Key = uint64_t
-    uint64_t declared_key;
-    // the actual keys being used
-    std::vector<uint64_t> key_list;
-    // a copy on CPU
-    void* cpubuff;
-    // GPU ptr if the tensor is on CPU
-    void* gpu_ptr;
-    // CPU buffer for cross-PCIe-switch merging
-    std::vector<void*> pcie_cpubuff;
-    size_t buff_len;
+  bool initialized;
+  std::mutex init_mutex;
+  // tensor name
+  std::string tensor_name;
+  // using ps::Key = uint64_t
+  uint64_t declared_key;
+  // the actual keys being used
+  std::vector<uint64_t> key_list;
+  // a copy on CPU
+  void* cpubuff;
+  // GPU ptr if the tensor is on CPU
+  void* gpu_ptr;
+  // CPU buffer for cross-PCIe-switch merging
+  std::vector<void*> pcie_cpubuff;
+  size_t buff_len;
 } BPSContext;
 
 class Tensor {
-public:
+ public:
   virtual const DataType dtype() const = 0;
   virtual const TensorShape shape() const = 0;
   virtual const void* data() const = 0;
@@ -194,7 +210,9 @@ struct TensorTableEntry {
 using TensorTable = std::unordered_map<std::string, TensorTableEntry>;
 
 enum class RequestType {
-  kDefaultPushPull, kRowSparsePushPull, kCompressedPushPull
+  kDefaultPushPull,
+  kRowSparsePushPull,
+  kCompressedPushPull
 };
 
 int GetCommandType(RequestType requestType, int d);
@@ -203,7 +221,7 @@ ncclDataType_t getNcclDataType(DataType dtype);
 
 int getDataTypeLength(int dtype);
 
-} // namespace common
-} // namespace byteps
+}  // namespace common
+}  // namespace byteps
 
-#endif // BYTEPS_COMMON_H
+#endif  // BYTEPS_COMMON_H