def _reshape(converter, node: Any, inputs: List[str]) -> Any:
    x_in = converter.outputs[inputs[0]]
    shape = converter.outputs[inputs[1]]
    tensor = shape.attr['value'].tensor
    dtype = shape.attr['dtype'].type
    if (dtype == tf.int32):
        nums = array.array('i', tensor.tensor_content)
    elif (dtype == tf.int64):
        nums = array.array('l', tensor.tensor_content)
    else:
        raise TypeError('Unsupported dtype for reshape shape')
    return converter.protocol.reshape(x_in, list(nums))
def _reshape(converter, node: Any, inputs: List[str]) -> Any:
    x_in = converter.outputs[inputs[0]]
    shape = converter.outputs[inputs[1]]
    tensor = shape.attr['value'].tensor
    dtype = shape.attr['dtype'].type
    if (dtype == tf.int32):
        nums = array.array('i', tensor.tensor_content)
    elif (dtype == tf.int64):
        nums = array.array('l', tensor.tensor_content)
    else:
        raise TypeError('Unsupported dtype for reshape shape')
    return converter.protocol.reshape(x_in, list(nums))