Remove unnecessary namespacing
PiperOrigin-RevId: 294298556 Change-Id: I2c3d1eb46aa150a8165f502c3e6a08b99b4377c9
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fcd06dbbeb
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9759636453
@ -53,8 +53,7 @@ Status EagerOperation::Reset(
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return SetDeviceName(raw_device_name, true);
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}
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tensorflow::Status EagerOperation::MaybeInferSingleInputAttrs(
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TensorHandle* handle) {
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Status EagerOperation::MaybeInferSingleInputAttrs(TensorHandle* handle) {
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if (!op_def_) return Status::OK();
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const auto& input_def = op_def_->input_arg(inference_arg_idx_++);
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@ -78,8 +77,7 @@ tensorflow::Status EagerOperation::MaybeInferSingleInputAttrs(
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}
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void EagerOperation::InferSingleTypeInputListAttrs(
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const tensorflow::OpDef::ArgDef& input_def,
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const tensorflow::DataType dtype, int num_inputs) {
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const OpDef::ArgDef& input_def, const DataType dtype, int num_inputs) {
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if (inference_attrs_.find(input_def.number_attr()) ==
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inference_attrs_.end()) {
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MutableAttrs()->Set(input_def.number_attr(), num_inputs);
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@ -92,24 +90,23 @@ void EagerOperation::InferSingleTypeInputListAttrs(
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}
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void EagerOperation::InferMixedTypeInputListAttrs(
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const tensorflow::OpDef::ArgDef& input_def,
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const std::vector<tensorflow::DataType>& dtypes) {
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const OpDef::ArgDef& input_def, const std::vector<DataType>& dtypes) {
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if (inference_attrs_.find(input_def.type_list_attr()) ==
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inference_attrs_.end()) {
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MutableAttrs()->Set(input_def.type_list_attr(),
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tensorflow::gtl::ArraySlice<const tensorflow::DataType>(
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dtypes.data(), dtypes.size()));
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MutableAttrs()->Set(
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input_def.type_list_attr(),
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gtl::ArraySlice<const DataType>(dtypes.data(), dtypes.size()));
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inference_attrs_.insert(input_def.type_list_attr());
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}
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}
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tensorflow::Status EagerOperation::InferInputListAttrs(int num_inputs) {
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Status EagerOperation::InferInputListAttrs(int num_inputs) {
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if (!op_def_) return Status::OK();
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int start = inference_arg_idx_;
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const auto& input_def = op_def_->input_arg(inference_arg_idx_++);
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if (!input_def.type_list_attr().empty()) {
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std::vector<tensorflow::DataType> dtypes(num_inputs);
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std::vector<DataType> dtypes(num_inputs);
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for (int i = 0; i < num_inputs; ++i) {
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dtypes[i] = inputs_[start + i]->dtype;
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}
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@ -118,13 +115,12 @@ tensorflow::Status EagerOperation::InferInputListAttrs(int num_inputs) {
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!input_def.number_attr().empty()) {
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InferSingleTypeInputListAttrs(input_def, inputs_[start]->dtype, num_inputs);
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} else {
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return tensorflow::errors::InvalidArgument("Invalid input list definition");
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return errors::InvalidArgument("Invalid input list definition");
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}
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return tensorflow::Status::OK();
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return Status::OK();
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}
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tensorflow::Status EagerOperation::SetDeviceName(const char* device,
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const bool reset) {
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Status EagerOperation::SetDeviceName(const char* device, const bool reset) {
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if (device != nullptr && strlen(device) > 0) {
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if (device != raw_device_name_) {
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if (!DeviceNameUtils::ParseFullName(device, &device_parsed_name_)) {
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@ -30,7 +30,7 @@ class EagerOperation {
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public:
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explicit EagerOperation(tensorflow::EagerContext* ctx) : ctx_(*ctx) {}
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~EagerOperation() {
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for (tensorflow::TensorHandle* h : inputs_) {
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for (TensorHandle* h : inputs_) {
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h->Unref();
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}
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}
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@ -39,41 +39,35 @@ class EagerOperation {
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// Clear(), and then Reset(...) with the same arguments that would have
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// been provided to the constructor.
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void Clear() {
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for (tensorflow::TensorHandle* h : inputs_) {
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for (TensorHandle* h : inputs_) {
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h->Unref();
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}
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inputs_.clear();
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ClearInferenceState();
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}
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tensorflow::Status Reset(const char* op, const char* raw_device_name,
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bool remote, EagerExecutor* executor,
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const absl::optional<EagerRemoteFunctionParams>
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remote_func_params = absl::nullopt);
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Status Reset(const char* op, const char* raw_device_name, bool remote,
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EagerExecutor* executor,
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const absl::optional<EagerRemoteFunctionParams>
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remote_func_params = absl::nullopt);
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bool is_function() const { return is_function_; }
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tensorflow::EagerContext& EagerContext() { return ctx_; }
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tensorflow::AttrBuilder* MutableAttrs() { return &attrs_; }
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const tensorflow::AttrBuilder& Attrs() const { return attrs_; }
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AttrBuilder* MutableAttrs() { return &attrs_; }
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const AttrBuilder& Attrs() const { return attrs_; }
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const tensorflow::OpDef* OpDef() const { return op_def_; }
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const tensorflow::gtl::InlinedVector<tensorflow::TensorHandle*, 4>& Inputs()
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const {
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return inputs_;
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}
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tensorflow::gtl::InlinedVector<tensorflow::TensorHandle*, 4>*
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MutableInputs() {
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return &inputs_;
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}
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const gtl::InlinedVector<TensorHandle*, 4>& Inputs() const { return inputs_; }
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gtl::InlinedVector<TensorHandle*, 4>* MutableInputs() { return &inputs_; }
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void AddInput(tensorflow::TensorHandle* h);
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void UpdateInput(int i, tensorflow::TensorHandle* h);
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void ConsumeInput(tensorflow::TensorHandle* h);
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void AddInput(TensorHandle* h);
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void UpdateInput(int i, TensorHandle* h);
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void ConsumeInput(TensorHandle* h);
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const tensorflow::string& Name() const { return attrs_.op_name(); }
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const tensorflow::AttrTypeMap* AttrTypes() const { return attr_types_; }
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const string& Name() const { return attrs_.op_name(); }
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const AttrTypeMap* AttrTypes() const { return attr_types_; }
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tensorflow::Device* Device() const { return device_; }
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void SetDevice(tensorflow::Device* device) {
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@ -87,8 +81,7 @@ class EagerOperation {
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const DeviceNameUtils::ParsedName& GetDeviceParsedName() const {
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return device_parsed_name_;
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}
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tensorflow::Status SetDeviceName(const char* device,
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const bool reset = false);
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Status SetDeviceName(const char* device, const bool reset = false);
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// Indicates whether the op is assigned to a device that is local to the
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// current host.
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@ -116,7 +109,7 @@ class EagerOperation {
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const char* op_name_ = nullptr;
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#endif
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Status MaybeInferSingleInputAttrs(tensorflow::TensorHandle* handle);
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Status MaybeInferSingleInputAttrs(TensorHandle* handle);
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Status InferInputListAttrs(int num_inputs);
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private:
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@ -125,17 +118,15 @@ class EagerOperation {
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inference_arg_idx_ = 0;
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inference_attrs_.clear_no_resize();
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}
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void InferSingleTypeInputListAttrs(const tensorflow::OpDef::ArgDef& input_def,
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const tensorflow::DataType dtype,
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int num_inputs);
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void InferMixedTypeInputListAttrs(
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const tensorflow::OpDef::ArgDef& input_def,
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const std::vector<tensorflow::DataType>& dtypes);
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void InferSingleTypeInputListAttrs(const OpDef::ArgDef& input_def,
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const DataType dtype, int num_inputs);
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void InferMixedTypeInputListAttrs(const OpDef::ArgDef& input_def,
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const std::vector<DataType>& dtypes);
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tensorflow::EagerContext& ctx_;
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tensorflow::AttrBuilder attrs_;
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const tensorflow::AttrTypeMap* attr_types_;
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tensorflow::gtl::InlinedVector<tensorflow::TensorHandle*, 4> inputs_;
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AttrBuilder attrs_;
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const AttrTypeMap* attr_types_;
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gtl::InlinedVector<TensorHandle*, 4> inputs_;
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tensorflow::Device* device_;
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string raw_device_name_;
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string device_name_;
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@ -150,19 +141,18 @@ class EagerOperation {
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const tensorflow::OpDef* op_def_; // op definition from protobuf
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int inference_arg_idx_; // arg definition index for the next input to be
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// added
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tensorflow::gtl::FlatSet<std::string>
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inference_attrs_; // attributes inferred so far
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gtl::FlatSet<std::string> inference_attrs_; // attributes inferred so far
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};
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inline void EagerOperation::AddInput(tensorflow::TensorHandle* h) {
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inline void EagerOperation::AddInput(TensorHandle* h) {
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h->Ref();
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inputs_.push_back(h);
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attrs_.NumInputs(static_cast<int>(inputs_.size()));
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}
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inline void EagerOperation::UpdateInput(int i, tensorflow::TensorHandle* h) {
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tensorflow::TensorHandle** slot = &inputs_[i];
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tensorflow::TensorHandle* existing = *slot;
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inline void EagerOperation::UpdateInput(int i, TensorHandle* h) {
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TensorHandle** slot = &inputs_[i];
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TensorHandle* existing = *slot;
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if (existing != h) {
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h->Ref();
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existing->Unref();
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@ -170,11 +160,10 @@ inline void EagerOperation::UpdateInput(int i, tensorflow::TensorHandle* h) {
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}
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}
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inline void EagerOperation::ConsumeInput(tensorflow::TensorHandle* h) {
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inline void EagerOperation::ConsumeInput(TensorHandle* h) {
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inputs_.push_back(h);
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attrs_.NumInputs(static_cast<int>(inputs_.size()));
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}
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} // namespace tensorflow
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#endif // TENSORFLOW_CORE_COMMON_RUNTIME_EAGER_EAGER_OPERATION_H_
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