EVOLUTION-MANAGER
Edit File: state_ops_internal.h
// This file is MACHINE GENERATED! Do not edit. #ifndef TENSORFLOW_CC_OPS_STATE_OPS_INTERNAL_H_ #define TENSORFLOW_CC_OPS_STATE_OPS_INTERNAL_H_ // This file is MACHINE GENERATED! Do not edit. #include "tensorflow/cc/framework/ops.h" #include "tensorflow/cc/framework/scope.h" #include "tensorflow/core/framework/tensor.h" #include "tensorflow/core/framework/tensor_shape.h" #include "tensorflow/core/framework/types.h" #include "tensorflow/core/lib/gtl/array_slice.h" namespace tensorflow { namespace ops { namespace internal { // NOTE: This namespace has internal TensorFlow details that // are not part of TensorFlow's public API. /// @defgroup state_ops_internal State Ops Internal /// @{ /// Computes element-wise maximum. /// /// Arguments: /// * scope: A Scope object /// * ref: A mutable Tensor. Should be from a Variable node. /// * indices: A Tensor. Must be one of the following types: int32, int64. /// A tensor of indices into ref. /// * updates: A Tensor. Must have the same type as ref. A tensor of updated values /// to add to ref. /// /// Optional attributes (see `Attrs`): /// * use_locking: An optional bool. Defaults to True. If True, the assignment will /// be protected by a lock; otherwise the behavior is undefined, /// but may exhibit less contention. /// /// Returns: /// * `Output`: Same as ref. Returned as a convenience for operations that want /// to use the updated values after the update is done. class ScatterNdMax { public: /// Optional attribute setters for ScatterNdMax struct Attrs { /// An optional bool. Defaults to True. If True, the assignment will /// be protected by a lock; otherwise the behavior is undefined, /// but may exhibit less contention. /// /// Defaults to false TF_MUST_USE_RESULT Attrs UseLocking(bool x) { Attrs ret = *this; ret.use_locking_ = x; return ret; } bool use_locking_ = false; }; ScatterNdMax(const ::tensorflow::Scope& scope, ::tensorflow::Input ref, ::tensorflow::Input indices, ::tensorflow::Input updates); ScatterNdMax(const ::tensorflow::Scope& scope, ::tensorflow::Input ref, ::tensorflow::Input indices, ::tensorflow::Input updates, const ScatterNdMax::Attrs& attrs); operator ::tensorflow::Output() const { return output_ref; } operator ::tensorflow::Input() const { return output_ref; } ::tensorflow::Node* node() const { return output_ref.node(); } static Attrs UseLocking(bool x) { return Attrs().UseLocking(x); } Operation operation; ::tensorflow::Output output_ref; }; /// Computes element-wise minimum. /// /// Arguments: /// * scope: A Scope object /// * ref: A mutable Tensor. Should be from a Variable node. /// * indices: A Tensor. Must be one of the following types: int32, int64. /// A tensor of indices into ref. /// * updates: A Tensor. Must have the same type as ref. A tensor of updated values /// to add to ref. /// /// Optional attributes (see `Attrs`): /// * use_locking: An optional bool. Defaults to True. If True, the assignment will /// be protected by a lock; otherwise the behavior is undefined, /// but may exhibit less contention. /// /// Returns: /// * `Output`: Same as ref. Returned as a convenience for operations that want /// to use the updated values after the update is done. class ScatterNdMin { public: /// Optional attribute setters for ScatterNdMin struct Attrs { /// An optional bool. Defaults to True. If True, the assignment will /// be protected by a lock; otherwise the behavior is undefined, /// but may exhibit less contention. /// /// Defaults to false TF_MUST_USE_RESULT Attrs UseLocking(bool x) { Attrs ret = *this; ret.use_locking_ = x; return ret; } bool use_locking_ = false; }; ScatterNdMin(const ::tensorflow::Scope& scope, ::tensorflow::Input ref, ::tensorflow::Input indices, ::tensorflow::Input updates); ScatterNdMin(const ::tensorflow::Scope& scope, ::tensorflow::Input ref, ::tensorflow::Input indices, ::tensorflow::Input updates, const ScatterNdMin::Attrs& attrs); operator ::tensorflow::Output() const { return output_ref; } operator ::tensorflow::Input() const { return output_ref; } ::tensorflow::Node* node() const { return output_ref.node(); } static Attrs UseLocking(bool x) { return Attrs().UseLocking(x); } Operation operation; ::tensorflow::Output output_ref; }; } // namespace internal } // namespace ops } // namespace tensorflow #endif // TENSORFLOW_CC_OPS_STATE_OPS_INTERNAL_H_