}

const char* TF_OperationOpType(TF_Operation* oper) {
  return oper->node.type_string().c_str();
}

const char* TF_OperationDevice(TF_Operation* oper) {
  return oper->node.requested_device().c_str();
}

int TF_OperationNumOutputs(TF_Operation* oper) {
  return oper->node.num_outputs();
}

TF_DataType TF_OperationOutputType(TF_Output oper_out) {

    // more than fits in a 32-bit integer.
    size_t requested_read_length;
    if (n > INT32_MAX)
      requested_read_length = INT32_MAX;
    else
      requested_read_length = n;

    // `pread` returns a `ssize_t` on POSIX, but due to interface being
    // cross-platform, return type of `Read` is `int64_t`.
    int64_t r = int64_t{pread(posix_file->fd, dst, requested_read_length,

TEST(CAPI, TestRemoteExecuteUpdateServerDefResourceAccessAsync) {
  TestRemoteExecuteUpdateServerDefResourceAccess(true);
}

void TestRemoteExecuteUpdateServerDefWithFailures(bool async) {
  // Fail fast on GetStatus requests so we can get errors instead of timeout
  // when updating cluster with non-exsitent worker
  tensorflow::setenv("GRPC_FAIL_FAST", "TRUE", /*overwrite=*/1);

  tensorflow::ServerDef server_def = GetServerDef(2);

    if ((p + s.size()) > (static_cast<char*>(storage) + storage_size)) {
      tsl::Set_TF_Status_from_Status(
          status,
          absl::InvalidArgumentError(
              "Not enough storage to hold the requested list of nodes"));
      return;
    }
    memcpy(values[index], s.data(), s.size());
    p += s.size();
    index++;
  }
}

void TF_GetFetchNodesListSize(const TF_GrapplerItem* item, int* num_values,

  EXPECT_TRUE(executed);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_DeleteTensorHandle(retval);

  // Explicit placement still forces the op onto the requested device
  matmul.reset(MatMulOp(context.get(), hcustom0.get(), hcpu.get()));
  TFE_OpSetDevice(matmul.get(), "/job:localhost/replica:0/task:0/device:CPU:0",
                  status.get());

                          void* device_info) {
  const char* requested_placement = TFE_OpGetDevice(original_op, s);
  if (TF_GetCode(s) != TF_OK) return;

  LoggingDevice* dev = reinterpret_cast<LoggingDevice*>(device_info);
  if (dev->strict_scope_placement && *requested_placement == '\0') {
    TF_SetStatus(s, TF_INTERNAL,

    // Inject failure to function instantiation if finding a node that contains
    // the given node name (error_node_) and requested device (error_device_).
    for (const auto node : graph->get()->nodes()) {
      if (node->name().find(error_node_) != string::npos &&
          node->requested_device() == error_device_) {
        return tensorflow::errors::Internal("Injected graph pass error.");
      }
    }

                           TFE_TensorHandle** outputs, TF_Status* status,
                           void* device_info) {
  const char* requested_placement = TFE_OpGetDevice(original_op, status);
  if (*requested_placement == '\0') {
    TF_SetStatus(
        status, TF_INTERNAL,
        "Ops must be placed on the parallel device explicitly, or their inputs "

  TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle(ctx);
  std::vector<TFE_TensorHandle*> handles_task0;
  if (heavy_load_on_streaming_rpc) {
    // Send 50 tensor copy requests to simulate that there have been some RPC
    // requests been enqueued.
    for (int i = 0; i < 50; ++i) {
      handles_task0.push_back(TestMatrixTensorHandle(ctx));
    }
  }

      // Forget the end-of-file flag to allow for clients that poll on the
      // same file.
      gcs_file->buffer_end_is_past_eof = false;
      TF_SetStatus(status, TF_OUT_OF_RANGE, "Read less bytes than requested");
      return copy_size;
    }
    TF_SetStatus(status, TF_OK, "");
    return copy_size;
  }
}

}  // namespace tf_random_access_file

// SECTION 2. Implementation for `TF_WritableFile`