virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

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

  virtual Status InputLength(const char* input_name, int* length) = 0;

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"

// Wraps a pointer to a tensor handle implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying handle object. Instead, call
// TFE_DeleteTensorHandle who calls Release() on the handle pointer and deletes
// the TFE_TensorHandle structure.

#ifndef TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_
#define TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and

  // indication of the dtype of the variable's value.
  //
  // Note that creating this resource-dtype handle can fail, so `Create` is a
  // separate static method which returns a status.
  Variable(TFE_TensorHandle* handle, TF_DataType type)
      : handle_(handle), type_(type) {}

  // Helper for constructing a resource handle and wrapping it in a `Variable`
  // object.
  static Variable* Create(TFE_Context* context, TF_DataType type,

#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value);

// Return a tensor handle containing a int scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, int value);

// Return a tensor handle containing a bool scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, bool value);

// Creates or truncates the given filename and returns a handle to be used for
// appending data to the file. If status is TF_OK, *handle is updated and the
// caller is responsible for freeing it (see TF_CloseWritableFile).
TF_CAPI_EXPORT extern void TF_NewWritableFile(const char* filename,
                                              TF_WritableFileHandle** handle,
                                              TF_Status* status);

//
// auto* reader = TFE_MonitoringNewCounterReader("name");
// test();
// int64_t value = TFE_MonitoringReadCounter1(reader, "label-value");

// Opaque handle to a reader.
typedef struct TFE_MonitoringCounterReader TFE_MonitoringCounterReader;

// Returns a handle to be used for reading values from streamz counter. The
// counter can have been created with any number of labels.
TF_CAPI_EXPORT extern TFE_MonitoringCounterReader*

const char* const kDlTensorCapsuleName = "dltensor";

// Converts eager tensor handle to DLPack (DLManagedTensor*), and return the
// void* for further PyCapsule construction.
TF_CAPI_EXPORT extern void* TFE_HandleToDLPack(TFE_TensorHandle* h,
                                               TF_Status* status);

// Converts DLPack (DLManagedTensor*) to eager tensor handle.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_HandleFromDLPack(void* dlm,

typedef struct TFE_Context TFE_Context;
typedef struct TFE_Op TFE_Op;

namespace tensorflow {
DEFINE_CONVERSION_FUNCTIONS(tensorflow::AbstractOpAttrs, TFE_OpAttrs);

// Set an AttrValue on the op. Doesn't handle the list types.
void SetOpAttrValueScalar(TFE_Context* ctx, TFE_Op* op,
                          const tensorflow::AttrValue& default_value,
                          const char* attr_name, TF_Status* status);

#ifndef TENSORFLOW_C_EAGER_ABSTRACT_OPERATION_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_OPERATION_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/tensor_interface.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {