// Creates a new in-process TensorFlow server configured using a serialized
// ServerDef protocol buffer provided via `proto` and `proto_len`.
//
// The server will not serve any requests until TF_ServerStart is invoked.
// The server will stop serving requests once TF_ServerStop or
// TF_DeleteServer is invoked.
TF_CAPI_EXPORT extern TF_Server* TF_NewServer(const void* proto,
                                              size_t proto_len,

    if (max_age_ == 0) {
      return compute_func(key, value, status);
    }

    // Note: we hold onto mu_ for the rest of this function. In practice, this
    // is okay, as stat requests are typically fast, and concurrent requests are
    // often for the same file. Future work can split this up into one lock per
    // key if this proves to be a significant performance bottleneck.
    absl::MutexLock lock(&mu_);

#ifndef TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_
#define TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_

// Run a function containing a MatMul op and check its output.
// If heavy_load_on_streaming_rpc is true, send some rpc requests before the one
// which creates a remote input, to simulate a scenario that the remote input
// is not ready when we start running an op or a function.
void TestRemoteExecuteSilentCopies(bool async, bool remote, bool func,

                                                 TF_Status* status);

// Sync pending nodes in local executors (including the context default executor
// and thread executors) and streaming requests to remote executors, and get the
// combined status.
TF_CAPI_EXPORT extern void TFE_ContextAsyncWait(TFE_Context* ctx,
                                                TF_Status* status);

/// argument to allocate memory. After `TF_InitPlugin` finishes, core
/// TensorFlow uses the information present in this to initialize filesystems
/// for the URI schemes that the plugin requests.
///
/// All pointers defined in this structure point to memory allocated by the DSO
/// using an allocator provided by core TensorFlow when calling `TF_InitPlugin`.
///