// returned and both error counters are set to zero.
//
// Otherwise, while traversing the tree, undeleted_file_count and
// undeleted_dir_count are updated if an entry of the corresponding type could
// not be deleted. The returned error status represents the reason that any one
// of these entries could not be deleted.
//
// Typical status codes:

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_CONTEXT_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_CONTEXT_H_

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/experimental/gradients/tape/tape_operation.h"

namespace tensorflow {
namespace gradients {
class TapeContext : public AbstractContext {
 public:
  explicit TapeContext(AbstractContext*, Tape*, const GradientRegistry&);

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_OPERATION_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_OPERATION_H_

#include "tensorflow/c/eager/abstract_operation.h"
#include "tensorflow/c/eager/gradients.h"

namespace tensorflow {
namespace gradients {
class TapeOperation : public AbstractOperation {
 public:
  explicit TapeOperation(AbstractOperation*, Tape*, const GradientRegistry&);
  void Release() override;

                 absl::Span<const int64_t> shape, const TF_DataType dtype)
      : device_(device),
        tensors_(std::move(tensors)),
        shape_(std::vector<int64_t>(shape.begin(), shape.end())),
        dtype_(dtype) {}
  ParallelTensor(const ParallelDevice& device,
                 std::vector<TensorHandlePtr> tensors, const TF_DataType dtype)
      : device_(device),
        tensors_(std::move(tensors)),

//
// Implicit copies onto `device_name` are allowed, replicating the value once
// per device in `underlying_devices`. Implicit copies off of the device throw
// an error.
//
// All component tensors must have the same dtype. Currently they must also have
// the same shape, although this requirement may be relaxed in the future.
//
// `device_name` must not name an existing physical or custom device (see

      tensorflow::PartialTensorShape* shape) const = 0;

  // Returns tensor (full) type.
  // While there is no immediate plan to deprecate dtype and shape in favor
  // of only using full type type information, this is a future possibility.
  //
  // Note that map_dtype_to_child_of_tensor() from core/framework/types.h
  // can be used to set a FullTypeDef based on dtype in a derived class if
  // appropriate.

TF_CAPI_EXPORT extern void TF_CreateAndSetPjRtCApiClient(
    const char* device_type, TF_Status* status, PJRT_NamedValue* create_options,
    int num_options);

// Resets the PjRt client for a device. After this, `TF_GetPjRtCClient` will
// returns an error for that device.
TF_CAPI_EXPORT extern void TF_ResetPjRtCClient(const char* device_type,
                                               TF_Status* status);

// which subclass it actually is. The user is responsible to use the right
// type of AbstractTensor in their context (do not pass an MlirTensor to a
// GraphContext and vice-versa).
class TracingTensorHandle : public AbstractTensorHandle {
 protected:
  explicit TracingTensorHandle(AbstractTensorHandleKind kind)
      : AbstractTensorHandle(kind) {}

 public:
  // For LLVM style RTTI.

typedef struct TF_Filesystem_Option_Value {
  int type_tag;    // type of values in the values union
  int num_values;  // number of values
  TF_Filesystem_Option_Value_Union*
      values;  // owned (plugins must make a copy if storing this)
} TF_Filesystem_Option_Value;

typedef enum TF_Filesystem_Option_Type {
  TF_Filesystem_Option_Type_Int = 0,
  TF_Filesystem_Option_Type_Real,
  TF_Filesystem_Option_Type_Buffer,

#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/test.h"

using ::tensorflow::string;

typedef std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)>
    unique_tensor_ptr;

TF_Tensor* BoolTensor(int32_t v);

// Create a tensor with values of type TF_INT8 provided by `values`.