(image)
Returns the dimensions of an image tensor.
    Args:
      image: A 3-D Tensor of shape `[height, width, channels]`.
    Returns:
      A list of `[height, width, channels]` corresponding to the dimensions of the
        input image.  Dimensions that are statically known are python integers,
        otherwise they are integer scalar tensors.
Returns the dimensions of an image tensor.
    Args:
      image: A 3-D Tensor of shape `[height, width, channels]`.
    Returns:
      A list of `[height, width, channels]` corresponding to the dimensions of the
        input image.  Dimensions that are statically known are python integers,
        otherwise they are integer scalar tensors.
Returns the dimensions of an image tensor . Args : image : A 3 - D Tensor of shape [ height width channels ] . Returns : A list of [ height width channels ] corresponding to the dimensions of the input image . Dimensions that are statically known are python integers otherwise they are integer scalar tensors .
def _ImageDimensions(image):
    """Returns the dimensions of an image tensor.
    Args:
      image: A 3-D Tensor of shape `[height, width, channels]`.
    Returns:
      A list of `[height, width, channels]` corresponding to the dimensions of the
        input image.  Dimensions that are statically known are python integers,
        otherwise they are integer scalar tensors.
    """
    if image.get_shape().is_fully_defined():
        return image.get_shape().as_list()
    else:
        static_shape = image.get_shape().with_rank(3).as_list()
        dynamic_shape = array_ops.unstack(array_ops.shape(image), 3)
        return [s if s is not None else d
                for s, d in zip(static_shape, dynamic_shape)]
def _ImageDimensions ( image ) : if image . get_shape ( ) . is_fully_defined ( ) : return image . get_shape ( ) . as_list ( ) else : static_shape = image . get_shape ( ) . with_rank ( 3 ) . as_list ( ) dynamic_shape = array_ops . unstack ( array_ops . shape ( image ) , 3 ) return [ s if s is not None else d for s , d in zip ( static_shape , dynamic_shape ) ]