add clang-format-precommit (#59)

* clang-format-precommit

* update

.clang-format

@@ -0,0 +1,4 @@
+# Run manually to reformat a file:
+# clang-format -i --style=file <file>
+BasedOnStyle: Google
+DerivePointerAlignment: false

.pre-commit-config.yaml

@@ -5,4 +5,10 @@ repos:
     name: copyright_checker
     entry: python ./scripts/pre-commit/copyright.py
     language: system
-    files: \.(cc|cpp|h|py|sh)$
+    files: \.(cc|cpp|h|py|sh)$
+- repo: https://github.com/pre-commit/mirrors-clang-format
+  rev: v10.0.1
+  hooks:
+  - id: clang-format
+    name: clang-format
+

mhlo_builder/mlir/mhlo/builder/mlir_shape_builder.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "mlir/mhlo/builder/mlir_shape_builder.h"
 
 #include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"

mhlo_builder/mlir/mhlo/builder/mlir_type_utils.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "mlir/mhlo/builder/mlir_type_utils.h"
 
 #include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"

mhlo_builder/mlir/mhlo/builder/slice.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/mhlo/builder/mlir_shape_builder.h"

mhlo_builder/mlir/mhlo/builder/standard.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "mlir/mhlo/builder/standard.h"
 
 #include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"

pytorch_blade/src/common_utils/logging.h

@@ -13,9 +13,8 @@
 
 #include "c10/util/Logging.h"
 
-#define DLOG(...)                                       \
+#define DLOG(...)                                      \
   if (std::getenv("TORCH_BLADE_DEBUG_LOG") != nullptr) \
   LOG(__VA_ARGS__)
 
 #define LOG_ASSERT(condition) FATAL_IF(condition)
-

pytorch_blade/src/common_utils/macros.h

@@ -16,17 +16,16 @@
   void operator=(const TypeName&) = delete;
 
 #define TorchBladeDeclNewFlag(T, Name) \
-  T Set##Name(T);                       \
+  T Set##Name(T);                      \
   T& Get##Name();
 
 #define TorchBladeDefNewFlag(T, Name) \
-  T& Get##Name() {                     \
-    thread_local T flag;               \
-    return flag;                       \
-  }                                    \
-  T Set##Name(T flag) {                \
-    T old_flag = Get##Name();          \
-    Get##Name() = flag;                \
-    return old_flag;                   \
+  T& Get##Name() {                    \
+    thread_local T flag;              \
+    return flag;                      \
+  }                                   \
+  T Set##Name(T flag) {               \
+    T old_flag = Get##Name();         \
+    Get##Name() = flag;               \
+    return old_flag;                  \
   }
-

pytorch_blade/src/compiler/jit/torch/alias_analysis.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "alias_analysis.h"
 
 namespace torch {

pytorch_blade/src/compiler/jit/torch/alias_analysis.h

@@ -21,4 +21,3 @@ bool isMutableType(const torch::jit::TypePtr& type);
 bool isMutableType(const torch::jit::Value* v);
 } // namespace blade
 } // namespace torch
-

pytorch_blade/src/compiler/mlir/converters/impl/broadcast.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include <mlir-hlo/Dialect/mhlo/IR/hlo_ops.h> // from tf repo
 #include <mlir/Dialect/StandardOps/IR/Ops.h> // from tf repo
 #include <mlir/mhlo/builder/broadcast.h>

pytorch_blade/src/compiler/mlir/converters/impl/utils.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "compiler/mlir/converters/impl/utils.h"
 
 #include "common_utils/logging.h"

pytorch_blade/src/compiler/mlir/runtime/ral_context.h

@@ -94,4 +94,3 @@ class RalContext {
 
 } // namespace blade
 } // namespace torch
-

pytorch_blade/src/pybind.cpp

@@ -9,7 +9,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-
 #include "pybind.h"
 
 #include <mutex>

tao/tao_bridge/errors.h

@@ -12,10 +12,9 @@
 #ifndef TAO_TAO_BRIDGE_ERRORS_H_
 #define TAO_TAO_BRIDGE_ERRORS_H_
 
+#include "tensorflow/core/lib/core/status.h"
 #include "tensorflow/core/platform/default/logging.h"
 #include "tensorflow/stream_executor/lib/statusor.h"
-#include "tensorflow/core/lib/core/status.h"
-
 
 namespace tensorflow {
 namespace tao {

tao/tao_bridge/executable.h

@@ -55,15 +55,9 @@ struct OutputDescription {
 
   OutputType type = kDefault;
 
-  bool is_constant() {
-    return type == kConstant;
-  }
-  bool is_resource() {
-    return type == kResource;
-  }
-  bool is_default() {
-    return type == kDefault;
-  }
+  bool is_constant() { return type == kConstant; }
+  bool is_resource() { return type == kResource; }
+  bool is_default() { return type == kDefault; }
 
   tensorflow::TensorShape shape;
   tensorflow::Tensor constant_value;
@@ -90,9 +84,7 @@ struct ConstantDescription {
 // Manage all buffers used during computation
 struct BufferAllocations {
   using Index = BufferAllocation::Index;
-  Index num_allocations() const {
-    return allocations.size();
-  }
+  Index num_allocations() const { return allocations.size(); }
   Index num_parameters() const {
     return allocation_id_to_parameter_index.size();
   }
@@ -136,8 +128,9 @@ struct BufferAllocations {
   }
 
   se::DeviceMemoryBase GetDeviceAddress(const BufferSlice& slice) const {
-    return se::DeviceMemoryBase(static_cast<char*>(
-      allocations.at(slice.id).ptr) + slice.offset, slice.size);
+    return se::DeviceMemoryBase(
+        static_cast<char*>(allocations.at(slice.id).ptr) + slice.offset,
+        slice.size);
   }
 
   void clear_buffers() {
@@ -164,9 +157,7 @@ struct BufferAllocations {
 struct ProfileState {
   int64 execution_time_in_us = -1;
 
-  bool is_valid() {
-    return execution_time_in_us > 0;
-  }
+  bool is_valid() { return execution_time_in_us > 0; }
 };
 
 class ExecutableRunOptions {
@@ -175,26 +166,19 @@ class ExecutableRunOptions {
     ctx_ = ctx;
     return *this;
   }
-  OpKernelContext* ctx() const {
-    return ctx_;
-  }
+  OpKernelContext* ctx() const { return ctx_; }
 
   ExecutableRunOptions& set_num_constant_args(int num) {
     num_constant_args_ = num;
     return *this;
   }
-  int num_constant_args() const {
-    return num_constant_args_;
-  }
+  int num_constant_args() const { return num_constant_args_; }
 
-  ExecutableRunOptions& set_variables(
-      std::map<int, OptionalTensor> variables) {
+  ExecutableRunOptions& set_variables(std::map<int, OptionalTensor> variables) {
     variables_ = std::move(variables);
     return *this;
   }
-  const std::map<int, OptionalTensor>& variables() const {
-    return variables_;
-  }
+  const std::map<int, OptionalTensor>& variables() const { return variables_; }
 
   ExecutableRunOptions& set_profile_state(ProfileState* state) {
     profile_state_ = state;
@@ -220,9 +204,7 @@ class Executable {
   // 2, Parse TaoCompilerResult and prepare to run
   virtual Status Init();
 
-  std::string compiled_result_file() const {
-    return compiled_result_file_;
-  }
+  std::string compiled_result_file() const { return compiled_result_file_; }
 
   virtual void DumpToFile(const std::string& filename) const;
 
@@ -243,8 +225,12 @@ class Executable {
                                 BufferAllocations& allocations,
                                 std::vector<Tensor>& output_tensors);
 
-  virtual Status StartProfiler(const ExecutableRunOptions& options) { return Status::OK(); }
-  virtual Status StopProfiler(const ExecutableRunOptions& options) { return Status::OK(); }
+  virtual Status StartProfiler(const ExecutableRunOptions& options) {
+    return Status::OK();
+  }
+  virtual Status StopProfiler(const ExecutableRunOptions& options) {
+    return Status::OK();
+  }
 
   const TaoCompilerResult& tao_compiler_result() const {
     CHECK(compiled_result_.get() != nullptr);
@@ -256,18 +242,14 @@ class Executable {
     return *compiled_result_;
   }
 
-  RalTfContext* ral_context() {
-    return ral_ctx_.get();
-  }
+  RalTfContext* ral_context() { return ral_ctx_.get(); }
 
   std::unique_ptr<RalTfContext>& mutable_ral_context() { return ral_ctx_; }
 
   BufferAllocations& buffers() { return buffers_; }
   const BufferAllocations& buffers() const { return buffers_; }
 
-  std::vector<Tensor>& output_tensors() {
-    return output_tensors_;
-  }
+  std::vector<Tensor>& output_tensors() { return output_tensors_; }
   std::unique_ptr<TaoCompilerResult> compiled_result_;
 
  private:
@@ -286,36 +268,37 @@ class ExecutableFactory {
  public:
   using ExecutableConstructor =
       std::function<std::unique_ptr<Executable>(const std::string&)>;
-  std::unique_ptr<Executable> NewExecutable(
-      const std::string& device_type, const std::string& proto_file);
+  std::unique_ptr<Executable> NewExecutable(const std::string& device_type,
+                                            const std::string& proto_file);
   static ExecutableFactory& Global();
-  bool RegisterExecutable(
-      const std::string& device_type, ExecutableConstructor);
+  bool RegisterExecutable(const std::string& device_type,
+                          ExecutableConstructor);
+
  private:
   ExecutableFactory() = default;
   std::unordered_map<std::string, ExecutableConstructor> constructors_;
 };
 
 struct Executableregistrar {
   using ExecutableConstructor = ExecutableFactory::ExecutableConstructor;
-  Executableregistrar(
-      const std::string& device_type, ExecutableConstructor ctor) {
-    ExecutableFactory::Global().RegisterExecutable(
-        device_type, ctor);
+  Executableregistrar(const std::string& device_type,
+                      ExecutableConstructor ctor) {
+    ExecutableFactory::Global().RegisterExecutable(device_type, ctor);
   }
 };
 
 #define TAO_REGISTER_EXECUTABLE(device, ctor) \
-    TAO_REGISTER_EXECUTABLE_IMPL(device, ctor, __COUNTER__)
+  TAO_REGISTER_EXECUTABLE_IMPL(device, ctor, __COUNTER__)
 
-#define TAO_REGISTER_EXECUTABLE_IMPL(device, ctor, ctr) \
-    Executableregistrar INTERNAL_REGISTER_TAO_EXECUBALE_NAME(ctr) TF_ATTRIBUTE_UNUSED (device, ctor)
+#define TAO_REGISTER_EXECUTABLE_IMPL(device, ctor, ctr)         \
+  Executableregistrar INTERNAL_REGISTER_TAO_EXECUBALE_NAME(ctr) \
+      TF_ATTRIBUTE_UNUSED(device, ctor)
 
 // __COUNTER__ must go through another macro to be properly expanded
 #define INTERNAL_REGISTER_TAO_EXECUBALE_NAME(ctr) ___##ctr##__object_
 
-} // namespace tao
+}  // namespace tao
 
-} // namespace tensorflow
+}  // namespace tensorflow
 
-#endif // TAO_TAO_BRIDGE_EXECUTABLE_H_
+#endif  // TAO_TAO_BRIDGE_EXECUTABLE_H_

tao/tao_bridge/kernels/tao_profiling_guided_compilation.cc

@@ -12,6 +12,7 @@
 #include "tao_bridge/kernels/tao_profiling_guided_compilation.h"
 
 #include <sys/time.h>
+
 #include "tensorflow/core/util/env_var.h"
 
 namespace tensorflow {

tao/tao_bridge/ops/tao_ops.cc

@@ -85,4 +85,4 @@ REGISTER_OP("DiscLaunch")
 DiscLaunchOp using DISC as the backend.)");
 #endif
 
-} // namespace tensorflow
+}  // namespace tensorflow

tao/tao_bridge/passes/defunctionalize_control_flow.cc

@@ -10,6 +10,7 @@
 // limitations under the License.
 
 #include "tao_bridge/passes/defunctionalize_control_flow.h"
+
 #include "tao_bridge/tf/lower_if_op.h"
 #include "tao_bridge/tf/lower_while_op.h"
 #include "tensorflow/core/framework/function.h"

tao/tao_bridge/passes/functionalize_cond.h

@@ -19,6 +19,7 @@ limitations under the License.
 #define TAO_TAO_BRIDGE_PASSES_FUNCTIONALIZE_COND_H_
 
 #include <deque>
+
 #include "tao_bridge/common.h"
 #include "tao_bridge/tf/statusor.h"
 #include "tensorflow/core/framework/function.h"

tao/tao_bridge/passes/tao_bace_reformat_pass.cc

@@ -86,7 +86,7 @@ Status TaoBaCEReformatPass::Run(const GraphOptimizationPassOptions& options) {
       AttrValue new_value;
       auto* new_tensor_proto = new_value.mutable_tensor();
       new_tensor_proto->set_version_number(tensor_proto.version_number());
-      if(!tensor_proto.tensor_content().empty()) {
+      if (!tensor_proto.tensor_content().empty()) {
         new_const.AsProtoTensorContent(new_tensor_proto);
       } else {
         new_const.AsProtoField(new_tensor_proto);

tao/tao_bridge/passes/tao_clone_constants_for_better_clustering.h

@@ -17,6 +17,7 @@ limitations under the License.
 #define TENSORFLOW_COMPILER_JIT_CLONE_CONSTANTS_FOR_BETTER_CLUSTERING_H_
 
 #include <unordered_set>
+
 #include "tao_bridge/passes/tao_optimization_pass.h"
 #include "tensorflow/core/common_runtime/optimization_registry.h"
 #include "tensorflow/core/lib/core/status.h"

tao/tao_bridge/passes/tao_encapsulate_subgraphs_pass.cc

@@ -2381,12 +2381,12 @@ Status Encapsulator::MakePrunedGraphCopyAndInline(
     std::unique_ptr<FunctionBody> fbody;
 #endif
 
-    TF_RETURN_IF_ERROR(
-        FunctionDefToBodyHelper(*fdef, node->attrs(), library,
-                                [library](const string& op, const OpDef** sig) {
-                                  return library->LookUpOpDef(op, sig);
-                                },
-                                &fbody));
+    TF_RETURN_IF_ERROR(FunctionDefToBodyHelper(
+        *fdef, node->attrs(), library,
+        [library](const string& op, const OpDef** sig) {
+          return library->LookUpOpDef(op, sig);
+        },
+        &fbody));
 
 #if defined TF_1_12
     InlineFunctionBody(*library, pruned_graph->get(), node, fbody, {});