// temporary storage. You can iterate through the list with TF_StringStreamNext.
// The caller is responsible for freeing the list (see TF_StringStreamDone).
TF_CAPI_EXPORT extern TF_StringStream* TF_GetLocalTempDirectories(void);

// Creates a temporary file name with an extension.
// The caller is responsible for freeing the returned pointer.
TF_CAPI_EXPORT extern char* TF_GetTempFileName(const char* extension);

#include <memory>

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

namespace tensorflow {

// Abstract interface to a context.
//
// This serves as a factory for creating `AbstractOperation`s and for
// registering traced functions.
// Operations creation within a context can only be executed in that context
// (for now at least).

// restricted stand-in for tf.Variable in Python.
class Variable {
 public:
  // Construct a Variable from a resource-dtype TFE_TensorHandle and an
  // 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) {}

//              The distinction between an empty array of operations and no
//              array of operations is necessary to distinguish the case of
//              creating a function with no body (e.g. identity or permutation)
//              and the case of creating a function whose body contains all
//              the nodes in the graph (except for the automatic skipping, see
//              below).

    TF_Status* status);

// Adds a function (created from TF_GraphToFunction or
// TF_FunctionImportFunctionDef) to the context, allowing it to be executed with
// TFE_Execute by creating an op with the same name as the function.
TF_CAPI_EXPORT extern void TFE_ContextAddFunction(TFE_Context* ctx,
                                                  TF_Function* function,

// that provides the filesystem functionality. However, the POSIX filesystem
// needs to be statically registered in some tests and utilities for building
// the API files at the time of creating the pip package. Hence, we need to
// expose this function so that this filesystem can be statically registered
// when needed.
void TF_InitPlugin(TF_FilesystemPluginInfo* info);

                                                    TF_Status* status);

// Get configuration key and value using coordination service.
// The config key must be set before getting its value. Getting value of
// non-existing config keys will result in errors.
// If `timeout_in_ms=0`, this call will block until the key-value is set or the
// worker shuts down.

//   - The number of `input_tensors` should be the same as the number of items
//     in `input_shapes`.
//
// The results are returned in `output_shapes` and
// `output_resource_shapes_and_types`. The caller is responsible for freeing the
// memory in these buffers by calling `TF_DeleteShapeAndTypeList`.
TF_CAPI_EXPORT extern void TFE_InferShapes(
    TFE_Op* op, TF_ShapeAndTypeList* input_shapes, TF_Tensor** input_tensors,

// Operations the tape needs to perform on tensors to do backpropagation. Named
// "vspace" because a subset of these are related to a vector space, such as
// adding gradients, getting zeroes, etc. Currently cannot be implemented
// without using tensorflow python code, hence left unspecified here.
//
// Gradient is the type returned by gradient functions. In Python TF it's either

#define TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_PLUGINS_POSIX_POSIX_FILESYSTEM_HELPER_H_

#include <dirent.h>
#include <sys/stat.h>

namespace tf_posix_filesystem {

// Copies up to `size` of `src` to `dst`, creating destination if needed.
//
// Callers should pass size of `src` in `size` and the permissions of `src` in
// `mode`. The later is only used if `dst` needs to be created.