}

  // Create a variable using `ctx_0`.
  // Replace worker1 using a new worker, and update the contexts.
  // Read the variable using `ctx_1`. This read should succeed.
  //
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var");

                          remote_device) != device_names.end());
  }

  // Create a variable using `ctx_0`.
  // Read the variable using `ctx_1`. This read should succeed.
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var2");

        // Contract is we always delete input_values[i].
        return false;
      }
      // Note: session->session is not modified if Extend() fails, so
      // we only set last_num_graph_nodes if it succeeds.
      session->last_num_graph_nodes = num_nodes;
    } else {
      session->graph->mu.unlock();
    }
  }
  return true;
}

}  // namespace tensorflow

#
# Usage: get_test_list.sh OUTPUT BAZEL_TEST_COMMAND...
# Writes the list of tests that would be run from BAZEL_TEST_COMMAND to OUTPUT.
# Hides all extra output and always exits with success for now.

OUTPUT=$1
shift

    error_msg: (String) String with one and only one '%s'. Formatted with each
      invalid response upon check_success(input) failure.
    suppress_default_error: (Bool) Suppress the above error message in favor of
      one from the check_success function.
    resolve_symlinks: (Bool) Translate symbolic links into the real filepath.
    n_ask_attempts: (Integer) Number of times to query for valid input before

          # replace just the digest portion in it
          sed -i"" "/\"$1\"/ s/sha256:[[:alnum:]]*/$digest/g" tensorflow/tools/toolchains/remote_config/configs.bzl
          echo "success."
        }
        # See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/toolchains/remote_config/configs.bzl
        # This is a mapping of name_container_map keys under sigbuild_tf_configs

  const auto& debug_str = DebugString(func->record->fdef());
  *len = debug_str.size();
  char* ret = static_cast<char*>(malloc(*len + 1));
  memcpy(ret, debug_str.c_str(), *len + 1);
  return ret;
}

// On success, returns a set of TF_Function instances from `text_proto` of
// GraphDef type. These functions must be deleted by calling TF_DeleteFunction.
//
// If `mutate_proto_func` is non-NULL, run it over each FunctionDef proto,

// most likely need to call `TF_FinishOperation` instead.
TF_CAPI_EXPORT extern TF_Operation* TF_FinishOperationLocked(
    TF_OperationDescription* desc, TF_Status* status);

// If this function succeeds:
//   * *status is set to an OK value,
//   * a TF_Operation is added to the graph,
//   * a non-null value pointing to the added operation is returned --
//     this value is valid until the underlying graph is deleted.

      failure.text = failure_msg
    else:
      properties = ElemTree.SubElement(testcase, 'properties')
      success_msg = 'Build completed successfully.\n' f'See {url} for details.'
      ElemTree.SubElement(properties, 'property',
                          name='description',
                          value=success_msg)
      if command:
        ElemTree.SubElement(properties, 'property',

}

TF_Function* TF_FunctionImportFunctionDef(const void* proto, size_t proto_len,
                                          TF_Status* status) {
  tensorflow::FunctionDef fdef;
  bool success = fdef.ParseFromArray(proto, proto_len);
  if (!success) {
    status->status = InvalidArgument(
        "Invalid FunctionDef given to TF_FunctionImportFunctionDef");
    return nullptr;
  }

  TF_Function* func = new TF_Function();