fixed clang format

mindspore/ccsrc/minddata/dataset/api/de_tensor.cc

@@ -8,169 +8,164 @@
 namespace mindspore {
 namespace tensor {
 dataset::DataType MSTypeToDEType(TypeId data_type) {
-    switch (data_type) {
-        case kNumberTypeBool:
-            return dataset::DataType(dataset::DataType::DE_BOOL);
-        case kNumberTypeInt8:
-            return dataset::DataType(dataset::DataType::DE_INT8);
-        case kNumberTypeUInt8:
-            return dataset::DataType(dataset::DataType::DE_UINT8);
-        case kNumberTypeInt16:
-            return dataset::DataType(dataset::DataType::DE_INT16);
-        case kNumberTypeUInt16:
-            return dataset::DataType(dataset::DataType::DE_UINT16);
-        case kNumberTypeInt32:
-            return dataset::DataType(dataset::DataType::DE_INT32);
-        case kNumberTypeUInt32:
-            return dataset::DataType(dataset::DataType::DE_UINT32);
-        case kNumberTypeInt64:
-            return dataset::DataType(dataset::DataType::DE_INT64);
-        case kNumberTypeUInt64:
-            return dataset::DataType(dataset::DataType::DE_UINT64);
-        case kNumberTypeFloat16:
-            return dataset::DataType(dataset::DataType::DE_FLOAT16);
-        case kNumberTypeFloat32:
-            return dataset::DataType(dataset::DataType::DE_FLOAT32);
-        case kNumberTypeFloat64:
-            return dataset::DataType(dataset::DataType::DE_FLOAT64);
-        default:
-            // maybe throw?
-            return dataset::DataType(dataset::DataType::DE_UNKNOWN);
-    }
+  switch (data_type) {
+    case kNumberTypeBool:
+      return dataset::DataType(dataset::DataType::DE_BOOL);
+    case kNumberTypeInt8:
+      return dataset::DataType(dataset::DataType::DE_INT8);
+    case kNumberTypeUInt8:
+      return dataset::DataType(dataset::DataType::DE_UINT8);
+    case kNumberTypeInt16:
+      return dataset::DataType(dataset::DataType::DE_INT16);
+    case kNumberTypeUInt16:
+      return dataset::DataType(dataset::DataType::DE_UINT16);
+    case kNumberTypeInt32:
+      return dataset::DataType(dataset::DataType::DE_INT32);
+    case kNumberTypeUInt32:
+      return dataset::DataType(dataset::DataType::DE_UINT32);
+    case kNumberTypeInt64:
+      return dataset::DataType(dataset::DataType::DE_INT64);
+    case kNumberTypeUInt64:
+      return dataset::DataType(dataset::DataType::DE_UINT64);
+    case kNumberTypeFloat16:
+      return dataset::DataType(dataset::DataType::DE_FLOAT16);
+    case kNumberTypeFloat32:
+      return dataset::DataType(dataset::DataType::DE_FLOAT32);
+    case kNumberTypeFloat64:
+      return dataset::DataType(dataset::DataType::DE_FLOAT64);
+    default:
+      return dataset::DataType(dataset::DataType::DE_UNKNOWN);
+  }
 }
 
 TypeId DETypeToMSType(dataset::DataType data_type) {
-    switch (data_type.value()) {
-        case dataset::DataType::DE_BOOL:
-            return mindspore::TypeId::kNumberTypeBool;
-        case dataset::DataType::DE_INT8:
-            return mindspore::TypeId::kNumberTypeInt8;
-        case dataset::DataType::DE_UINT8:
-            return mindspore::TypeId::kNumberTypeUInt8;
-        case dataset::DataType::DE_INT16:
-            return mindspore::TypeId::kNumberTypeInt16;
-        case dataset::DataType::DE_UINT16:
-            return mindspore::TypeId::kNumberTypeUInt16;
-        case dataset::DataType::DE_INT32:
-            return mindspore::TypeId::kNumberTypeInt32;
-        case dataset::DataType::DE_UINT32:
-            return mindspore::TypeId::kNumberTypeUInt32;
-        case dataset::DataType::DE_INT64:
-            return mindspore::TypeId::kNumberTypeInt64;
-        case dataset::DataType::DE_UINT64:
-            return mindspore::TypeId::kNumberTypeUInt64;
-        case dataset::DataType::DE_FLOAT16:
-            return mindspore::TypeId::kNumberTypeFloat16;
-        case dataset::DataType::DE_FLOAT32:
-            return mindspore::TypeId::kNumberTypeFloat32;
-        case dataset::DataType::DE_FLOAT64:
-            return mindspore::TypeId::kNumberTypeFloat64;
-        default:
-            // maybe throw?
-            return kTypeUnknown;
-    }
+  switch (data_type.value()) {
+    case dataset::DataType::DE_BOOL:
+      return mindspore::TypeId::kNumberTypeBool;
+    case dataset::DataType::DE_INT8:
+      return mindspore::TypeId::kNumberTypeInt8;
+    case dataset::DataType::DE_UINT8:
+      return mindspore::TypeId::kNumberTypeUInt8;
+    case dataset::DataType::DE_INT16:
+      return mindspore::TypeId::kNumberTypeInt16;
+    case dataset::DataType::DE_UINT16:
+      return mindspore::TypeId::kNumberTypeUInt16;
+    case dataset::DataType::DE_INT32:
+      return mindspore::TypeId::kNumberTypeInt32;
+    case dataset::DataType::DE_UINT32:
+      return mindspore::TypeId::kNumberTypeUInt32;
+    case dataset::DataType::DE_INT64:
+      return mindspore::TypeId::kNumberTypeInt64;
+    case dataset::DataType::DE_UINT64:
+      return mindspore::TypeId::kNumberTypeUInt64;
+    case dataset::DataType::DE_FLOAT16:
+      return mindspore::TypeId::kNumberTypeFloat16;
+    case dataset::DataType::DE_FLOAT32:
+      return mindspore::TypeId::kNumberTypeFloat32;
+    case dataset::DataType::DE_FLOAT64:
+      return mindspore::TypeId::kNumberTypeFloat64;
+    default:
+      return kTypeUnknown;
+  }
 }
 
 MSTensor *DETensor::CreateTensor(TypeId data_type, const std::vector<int> &shape) {
-    return new DETensor(data_type, shape);
+  return new DETensor(data_type, shape);
 }
 
 MSTensor *DETensor::CreateTensor(const std::string &path) {
-    std::shared_ptr<dataset::Tensor> t;
-    (void) dataset::Tensor::CreateFromFile(path, &t);
-    return new DETensor(std::move(t));
+  std::shared_ptr<dataset::Tensor> t;
+  (void)dataset::Tensor::CreateFromFile(path, &t);
+  return new DETensor(std::move(t));
 }
 
 DETensor::DETensor(TypeId data_type, const std::vector<int> &shape) {
-    std::vector<dataset::dsize_t> t_shape;
-    t_shape.reserve(shape.size());
-    std::transform(shape.begin(), shape.end(),
-                   std::back_inserter(t_shape),
-                   [](int s) -> dataset::dsize_t {return static_cast<dataset::dsize_t>(s);});
-    dataset::Tensor::CreateEmpty(dataset::TensorShape(t_shape), MSTypeToDEType(data_type), &this->tensor_impl_);
+  std::vector<dataset::dsize_t> t_shape;
+  t_shape.reserve(shape.size());
+  std::transform(shape.begin(), shape.end(), std::back_inserter(t_shape),
+                 [](int s) -> dataset::dsize_t { return static_cast<dataset::dsize_t>(s); });
+  dataset::Tensor::CreateEmpty(dataset::TensorShape(t_shape), MSTypeToDEType(data_type), &this->tensor_impl_);
 }
 
 DETensor::DETensor(std::shared_ptr<dataset::Tensor> tensor_ptr) { this->tensor_impl_ = std::move(tensor_ptr); }
 
 MSTensor *DETensor::ConvertToLiteTensor() {
-    // static MSTensor::CreateTensor is only for the LiteTensor
-    MSTensor *tensor = MSTensor::CreateTensor(this->data_type(), this->shape());
-    MS_ASSERT(tensor->Size() == this->Size());
-    memcpy_s(tensor->MutableData(), tensor->Size(), this->MutableData(), this->Size());
-    return tensor;
+  // static MSTensor::CreateTensor is only for the LiteTensor
+  MSTensor *tensor = MSTensor::CreateTensor(this->data_type(), this->shape());
+  MS_ASSERT(tensor->Size() == this->Size());
+  memcpy_s(tensor->MutableData(), tensor->Size(), this->MutableData(), this->Size());
+  return tensor;
 }
 
 std::shared_ptr<dataset::Tensor> DETensor::tensor() const {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    return this->tensor_impl_;
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  return this->tensor_impl_;
 }
 
 TypeId DETensor::data_type() const {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    return DETypeToMSType(this->tensor_impl_->type());
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  return DETypeToMSType(this->tensor_impl_->type());
 }
 
 TypeId DETensor::set_data_type(TypeId data_type) {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    if (data_type != this->data_type()) {
-        std::shared_ptr<dataset::Tensor> temp;
-        dataset::Tensor::CreateFromMemory(this->tensor_impl_->shape(), MSTypeToDEType(data_type), 
-                                          this->tensor_impl_->GetBuffer(), &temp);
-        this->tensor_impl_ = temp;
-    }
-    return data_type;
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  if (data_type != this->data_type()) {
+    std::shared_ptr<dataset::Tensor> temp;
+    dataset::Tensor::CreateFromMemory(this->tensor_impl_->shape(), MSTypeToDEType(data_type),
+                                      this->tensor_impl_->GetBuffer(), &temp);
+    this->tensor_impl_ = temp;
+  }
+  return data_type;
 }
 
 std::vector<int> DETensor::shape() const {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    std::vector<dataset::dsize_t> t_shape = this->tensor_impl_->shape().AsVector();
-    std::vector<int> shape;
-    shape.reserve(t_shape.size());
-    std::transform(t_shape.begin(), t_shape.end(),
-                   std::back_inserter(shape),
-                   [](dataset::dsize_t s) -> int {return static_cast<int>(s);});
-    return shape;
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  std::vector<dataset::dsize_t> t_shape = this->tensor_impl_->shape().AsVector();
+  std::vector<int> shape;
+  shape.reserve(t_shape.size());
+  std::transform(t_shape.begin(), t_shape.end(), std::back_inserter(shape),
+                 [](dataset::dsize_t s) -> int { return static_cast<int>(s); });
+  return shape;
 }
 
 size_t DETensor::set_shape(const std::vector<int> &shape) {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    std::vector<dataset::dsize_t> t_shape;
-    t_shape.reserve(shape.size());
-    std::transform(shape.begin(), shape.end(),
-                   std::back_inserter(t_shape),
-                   [](int s) -> dataset::dsize_t {return static_cast<dataset::dsize_t>(s);});
-    dataset::Status rc = this->tensor_impl_->Reshape(dataset::TensorShape(t_shape));
-    return shape.size();
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  std::vector<dataset::dsize_t> t_shape;
+  t_shape.reserve(shape.size());
+  std::transform(shape.begin(), shape.end(), std::back_inserter(t_shape),
+                 [](int s) -> dataset::dsize_t { return static_cast<dataset::dsize_t>(s); });
+  dataset::Status rc = this->tensor_impl_->Reshape(dataset::TensorShape(t_shape));
+  return shape.size();
 }
 
 int DETensor::DimensionSize(size_t index) const {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    int dim_size = -1;
-    auto shape = this->shape();
-    if (index < shape.size()) {
-        dim_size = shape[index];
-    } else {
-        MS_LOG(ERROR) << "Dimension index is wrong: " << index;
-    }
-    return dim_size;
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  int dim_size = -1;
+  auto shape = this->shape();
+  if (index < shape.size()) {
+    dim_size = shape[index];
+  } else {
+    MS_LOG(ERROR) << "Dimension index is wrong: " << index;
+  }
+  return dim_size;
 }
 
 int DETensor::ElementsNum() const {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    return this->tensor_impl_->Size();
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  return this->tensor_impl_->Size();
 }
 
 std::size_t DETensor::hash() const {
-    MS_ASSERT(this->tensor_impl_ != nullptr);
-    auto shape = this->shape();
-    std::size_t hash_value = std::hash<int>{}(SizeToInt(this->data_type()));
-    hash_value = hash_combine(hash_value, std::hash<size_t>{}(shape.size()));
-    // hash all elements may costly, so only take at most 4 elements into account based on
-    // some experiments.
-    for (size_t i = 0; (i < shape.size()) && (i < 4); ++i) {
-        hash_value = hash_combine(hash_value, (std::hash<int>{}(shape[i])));
-    }
-    return hash_value;
+  MS_ASSERT(this->tensor_impl_ != nullptr);
+  auto shape = this->shape();
+  std::size_t hash_value = std::hash<int>{}(SizeToInt(this->data_type()));
+  hash_value = hash_combine(hash_value, std::hash<size_t>{}(shape.size()));
+  // hash all elements may costly, so only take at most 4 elements into account based on
+  // some experiments.
+  for (size_t i = 0; (i < shape.size()) && (i < 4); ++i) {
+    hash_value = hash_combine(hash_value, (std::hash<int>{}(shape[i])));
+  }
+  return hash_value;
 }
 
 size_t DETensor::Size() const {

mindspore/ccsrc/minddata/dataset/api/execute.cc

@@ -49,7 +49,6 @@ std::shared_ptr<tensor::MSTensor> Execute::operator()(std::shared_ptr<tensor::MS
   return std::make_shared<tensor::DETensor>(std::move(de_output));
 }
 
-
 }  // namespace api
 }  // namespace dataset
 }  // namespace mindspore

mindspore/ccsrc/minddata/dataset/include/execute.h

@@ -44,7 +44,6 @@ class Execute {
   std::shared_ptr<TensorOperation> op_;
 };
 
-
 }  // namespace api
 }  // namespace dataset
 }  // namespace mindspore