"//tensorflow/c:tf_file_statistics",
        "//tensorflow/c:tf_status",
        "//tensorflow/c/experimental/filesystem:filesystem_interface",
    ],
)

# Since building pip package and API tests require a filesystem, we provide a
# static registration target that they should link against.
cc_library(
    name = "posix_filesystem_static",
    srcs = ["posix_filesystem_static.cc"],
    visibility = ["//visibility:public"],

// this to be called.
TF_CAPI_EXPORT void TF_InitMain(const char* usage, int* argc, char*** argv);

// Platform-specific implementation to return an unused port. (This should used
// in tests only.)
TF_CAPI_EXPORT int TF_PickUnusedPortOrDie(void);

// Fast path method that makes constructing a single scalar tensor require less
// overhead and copies.

  // Accumulate will forward op executions to the tape while the backward
  // function is running; this effectively adds the backward tape to the active
  // set (but does not require complicated callbacks to the language bindings).
  Status ForwardpropFromTape(
      const string& op_type, const std::vector<TapeTensor>& output_tensors,
      const std::function<BackwardFunction*()>& backward_function_getter,

  // parallel.
  //
  // Conceptually this is a thread pool with one thread per device. It requires
  // less synchronization than a thread pool would for this task, since Execute
  // acquires each thread in order (and so only one Execute will schedule
  // blocking collective operations at a time), and avoids some dynamic
  // allocation/scheduling.
  //

        body_nodes->push_back(node);
      } else {
        // This node is referenced in inputs. Currently, we place an
        // artificial restriction and require that when num_opers=-1, such
        // nodes must have a single output.
        if (node->num_outputs() != 1) {
          return InvalidArgument(
              "When `num_opers` is set to -1, nodes referenced in `inputs` "

// Set if `graph` requires shape inference functions.
TF_CAPI_EXPORT extern void TF_SetRequireShapeInferenceFns(TF_Graph* graph,
                                                          bool require);

// Extends `session` with any new operations added to its associated graph.
// Usually this happens automatically in TF_SessionRun. After this is called,