From f92d68456dec30cdcfa16f49eedfbacfcaa89c5c Mon Sep 17 00:00:00 2001 From: ervinzhang Date: Tue, 4 Aug 2020 13:52:23 -0400 Subject: [PATCH] fixed clang format --- .../ccsrc/minddata/dataset/api/de_tensor.cc | 239 +++++++++--------- .../ccsrc/minddata/dataset/api/execute.cc | 1 - .../ccsrc/minddata/dataset/include/execute.h | 1 - 3 files changed, 117 insertions(+), 124 deletions(-) diff --git a/mindspore/ccsrc/minddata/dataset/api/de_tensor.cc b/mindspore/ccsrc/minddata/dataset/api/de_tensor.cc index 9f6148e724..23ac1dd1c8 100644 --- a/mindspore/ccsrc/minddata/dataset/api/de_tensor.cc +++ b/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 &shape) { - return new DETensor(data_type, shape); + return new DETensor(data_type, shape); } MSTensor *DETensor::CreateTensor(const std::string &path) { - std::shared_ptr t; - (void) dataset::Tensor::CreateFromFile(path, &t); - return new DETensor(std::move(t)); + std::shared_ptr t; + (void)dataset::Tensor::CreateFromFile(path, &t); + return new DETensor(std::move(t)); } DETensor::DETensor(TypeId data_type, const std::vector &shape) { - std::vector 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(s);}); - dataset::Tensor::CreateEmpty(dataset::TensorShape(t_shape), MSTypeToDEType(data_type), &this->tensor_impl_); + std::vector 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(s); }); + dataset::Tensor::CreateEmpty(dataset::TensorShape(t_shape), MSTypeToDEType(data_type), &this->tensor_impl_); } DETensor::DETensor(std::shared_ptr 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 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 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 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 DETensor::shape() const { - MS_ASSERT(this->tensor_impl_ != nullptr); - std::vector t_shape = this->tensor_impl_->shape().AsVector(); - std::vector 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(s);}); - return shape; + MS_ASSERT(this->tensor_impl_ != nullptr); + std::vector t_shape = this->tensor_impl_->shape().AsVector(); + std::vector 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(s); }); + return shape; } size_t DETensor::set_shape(const std::vector &shape) { - MS_ASSERT(this->tensor_impl_ != nullptr); - std::vector 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(s);}); - dataset::Status rc = this->tensor_impl_->Reshape(dataset::TensorShape(t_shape)); - return shape.size(); + MS_ASSERT(this->tensor_impl_ != nullptr); + std::vector 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(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{}(SizeToInt(this->data_type())); - hash_value = hash_combine(hash_value, std::hash{}(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{}(shape[i]))); - } - return hash_value; + MS_ASSERT(this->tensor_impl_ != nullptr); + auto shape = this->shape(); + std::size_t hash_value = std::hash{}(SizeToInt(this->data_type())); + hash_value = hash_combine(hash_value, std::hash{}(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{}(shape[i]))); + } + return hash_value; } size_t DETensor::Size() const { diff --git a/mindspore/ccsrc/minddata/dataset/api/execute.cc b/mindspore/ccsrc/minddata/dataset/api/execute.cc index 6e00aaa25b..bf34529fe9 100644 --- a/mindspore/ccsrc/minddata/dataset/api/execute.cc +++ b/mindspore/ccsrc/minddata/dataset/api/execute.cc @@ -49,7 +49,6 @@ std::shared_ptr Execute::operator()(std::shared_ptr(std::move(de_output)); } - } // namespace api } // namespace dataset } // namespace mindspore diff --git a/mindspore/ccsrc/minddata/dataset/include/execute.h b/mindspore/ccsrc/minddata/dataset/include/execute.h index b3a7ea297f..c2028fbb12 100644 --- a/mindspore/ccsrc/minddata/dataset/include/execute.h +++ b/mindspore/ccsrc/minddata/dataset/include/execute.h @@ -44,7 +44,6 @@ class Execute { std::shared_ptr op_; }; - } // namespace api } // namespace dataset } // namespace mindspore