GradientFunction* gradient_function,
                       const string& op_name = "");
  // Returns whether any tensor in a list of tensors is being watched and has
  // a trainable dtype.
  bool ShouldRecord(
      absl::Span<const AbstractTensorHandle* const> tensors) const;
  // Unwatches this tensor on the tape. Mainly used for cleanup when deleting
  // eager tensors.

  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;

  virtual absl::Status InputLength(const char* input_name, int* length) = 0;
  virtual absl::Status OutputLength(const char* output_name, int* length) = 0;

  // Set stack trace to be used for potential async error reporting.

pkg go/types, const Float32 BasicKind
pkg go/types, const Float64 = 14
pkg go/types, const Float64 BasicKind
pkg go/types, const Int = 2
pkg go/types, const Int BasicKind
pkg go/types, const Int16 = 4
pkg go/types, const Int16 BasicKind
pkg go/types, const Int32 = 5
pkg go/types, const Int32 BasicKind
pkg go/types, const Int64 = 6
pkg go/types, const Int64 BasicKind
pkg go/types, const Int8 = 3
pkg go/types, const Int8 BasicKind

                               const void* const* values, const size_t* lengths,
                               int num_values, ForwardOperation*);
absl::Status SetAttrFloatList(AbstractOperation*, const char* attr_name,
                              const float* values, int num_values,
                              ForwardOperation*);
absl::Status SetAttrIntList(AbstractOperation*, const char* attr_name,

      const FunctionDef& fdef, const StackTracesMap& stack_traces) = 0;

  // Find and return a added function by its name.
  virtual const FunctionDef* FindFunctionDef(const string& name) const = 0;

  // Find and return a function record added by its name.
  virtual core::RefCountPtr<FunctionRecord> FindRecord(
      const string& name) const = 0;

                          const char* name = "feed",
                          TF_DataType dtype = TF_INT32,
                          const std::vector<int64_t>& dims = {});

TF_Operation* Const(TF_Tensor* t, TF_Graph* graph, TF_Status* s,
                    const char* name = "const");

TF_Operation* ScalarConst(bool v, TF_Graph* graph, TF_Status* s,
                          const char* name = "scalar");

TF_CAPI_EXPORT extern TF_CheckpointReader* TF_NewCheckpointReader(
    const char* filename, TF_Status* status);
TF_CAPI_EXPORT extern void TF_DeleteCheckpointReader(
    TF_CheckpointReader* reader);
TF_CAPI_EXPORT extern int TF_CheckpointReaderHasTensor(
    TF_CheckpointReader* reader, const char* name);
// Get the variable name at the given index
TF_CAPI_EXPORT extern const char* TF_CheckpointReaderGetVariable(

                                  const char* label1, const char* label2);

// APIs for String Gauge with 3 labels.
typedef struct TFE_MonitoringStringGauge3 TFE_MonitoringStringGauge3;
TF_CAPI_EXPORT extern TFE_MonitoringStringGauge3* TFE_MonitoringNewStringGauge3(
    const char* name, TF_Status* out_status, const char* description,
    const char* label1, const char* label2, const char* label3);

  }
}

bool CheckpointReader::HasTensor(const string& name) const {
  if (reader_ != nullptr) {
    return reader_->HasTensor(name, nullptr, nullptr);
  }
  return v2_reader_->Contains(name);
}

const TensorSliceReader::VarToShapeMap&
CheckpointReader::GetVariableToShapeMap() const {
  CHECK(var_to_shape_map_);
  return *var_to_shape_map_;
}

const TensorSliceReader::VarToDataTypeMap&

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