(a, indices, axis=None, out=None, mode='clip')
return utils.tensor_to_ndarray(tf.gather(a, indices, axis=axis))
out argument is not supported, and default mode is clip.
out argument is not supported, and default mode is clip.
out argument is not supported and default mode is clip .
def take(a, indices, axis=None, out=None, mode='clip'):
  """out argument is not supported, and default mode is clip."""
  if out is not None:
    raise ValueError('out argument is not supported in take.')

  if mode not in {'raise', 'clip', 'wrap'}:
    raise ValueError("Invalid mode '{}' for take".format(mode))

  a = asarray(a).data
  indices = asarray(indices).data

  if axis is None:
    a = tf.reshape(a, [-1])
    axis = 0

  axis_size = tf.shape(a, indices.dtype)[axis]
  if mode == 'clip':
    indices = tf.clip_by_value(indices, 0, axis_size-1)
  elif mode == 'wrap':
    indices = tf.math.floormod(indices, axis_size)
  else:
    raise ValueError("The 'raise' mode to take is not supported.")

  return utils.tensor_to_ndarray(tf.gather(a, indices, axis=axis))
def take ( a , indices , axis = None , out = None , mode = 'clip' ) : if out is not None : raise ValueError ( 'out argument is not supported in take.' ) if mode not in { 'raise' , 'clip' , 'wrap' } : raise ValueError ( "Invalid mode '{}' for take" . format ( mode ) ) a = asarray ( a ) . data indices = asarray ( indices ) . data if axis is None : a = tf . reshape ( a , [ - 1 ] ) axis = 0 axis_size = tf . shape ( a , indices . dtype ) [ axis ] if mode == 'clip' : indices = tf . clip_by_value ( indices , 0 , axis_size - 1 ) elif mode == 'wrap' : indices = tf . math . floormod ( indices , axis_size ) else : raise ValueError ( "The 'raise' mode to take is not supported." ) return utils . tensor_to_ndarray ( tf . gather ( a , indices , axis = axis ) )