#include "tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.h"
#include "tensorflow/c/tf_status.h"

void ParseGCSPath(const std::string& fname, bool object_empty_ok,
                  std::string* bucket, std::string* object, TF_Status* status);

namespace tf_random_access_file {
void Cleanup(TF_RandomAccessFile* file);

TF_CAPI_EXPORT extern void TF_CreateDir(const char* dirname, TF_Status* status);

// Deletes the specified directory. Typical status codes are:
//  * TF_OK - successfully deleted the directory
//  * TF_FAILED_PRECONDITION - the directory is not empty
TF_CAPI_EXPORT extern void TF_DeleteDir(const char* dirname, TF_Status* status);

// Deletes the specified directory and all subdirectories and files underneath

typedef struct TF_SessionOptions TF_SessionOptions;

// Return a new options object.
TF_CAPI_EXPORT extern TF_SessionOptions* TF_NewSessionOptions(void);

// Set the target in TF_SessionOptions.options.
// target can be empty, a single entry, or a comma separated list of entries.
// Each entry is in one of the following formats :
// "local"
// ip:port
// host:port
TF_CAPI_EXPORT extern void TF_SetTarget(TF_SessionOptions* options,

  // Consumes the internal state of the tape (so cannot be called more than
  // once) and produces the gradient of the target tensors with respect to the
  // source tensors. The output gradients are used if not empty and not
  // null. The result is populated with one tensor per target element.
  // When running backward functions, builds zeros-like tensors for
  // incoming grads which are nullptrs, unless `build_default_zeros_grads`

  // value records whether the graph has been mutated since the corresponding
  // session has been run (this is detected in RecordMutation function). If the
  // string is empty, no mutation has occurred. Otherwise the string is a
  // description of the mutation suitable for returning to the user.
  //
  // Sessions are added to this map in TF_NewSession, and removed in
  // TF_DeleteSession.

// "fifo_queue_dequeue_<tensor_id>", to be executed by this API call.

// Caller must call TF_DeleteTensor() over the returned tensor. If the queue is
// empty, this call is blocked.
//
// Tensors are enqueued via the corresponding TF enqueue op.
// TODO(hongm): Add support for `timeout_ms`.
TF_CAPI_EXPORT extern TF_Tensor* TF_DequeueNamedTensor(TF_Session* session,

#endif

// Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This
// is for performance optimization by reusing an exiting unused op rather than
// creating a new op every time. If `raw_device_name` is `NULL` or empty, it
// does not set the device name. If it's not `NULL`, then it attempts to parse
// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster
// than separately calling it because if the existing op has the same

  // once unless the tape is persistent) and produces the gradient of the target
  // tensors with respect to the source tensors. The output gradients are used
  // if not empty and not null. The result is populated with one tensor per
  // target element.
  Status ComputeGradient(
      AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> targets,

                  TF_Status* s, const char* name = "min");

TF_Operation* Mul(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name = "mul");

// If `op_device` is non-empty, set the created op on that device.
TF_Operation* MinWithDevice(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                            const string& op_device, TF_Status* s,

  /// Deletes the empty directory specified by `path`.
  ///
  /// Plugins:
  ///   * Must set `status` to `TF_OK` if directory was deleted.
  ///   * Must set `status` to `TF_NOT_FOUND` if `path` doesn't exist.
  ///   * Must set `status` to `TF_FAILED_PRECONDITION` if `path` does not point
  ///     to a directory, if `path` is invalid, or if directory is not empty.