misc.py 文件源码

def normalize_num_type(num_type):
    """
    Work out what a sensible type for the array is. if the default type
    is float32, downcast 64bit float to float32. For ints, assume int32
    """
    if isinstance(num_type, tf.DType):
        num_type = num_type.as_numpy_dtype.type

    if num_type in [np.float32, np.float64]:  # pylint: disable=E1101
        num_type = settings.float_type
    elif num_type in [np.int16, np.int32, np.int64]:
        num_type = settings.int_type
    else:
        raise ValueError('Unknown dtype "{0}" passed to normalizer.'.format(num_type))

    return num_type


# def types_array(tensor, shape=None):
#     shape = shape if shape is not None else tensor.shape.as_list()
#     return np.full(shape, tensor.dtype).tolist()