message: Update tf.nn.[max,avg]_pool to specify that it accepts list/tuple stride and kernel arguments, not tensor arguments.
  If you actually specify a tensor argument here, you get the error:
  TypeError: Expected list for 'ksize' argument to 'avg_pool' Op, not <tf.Tensor 'Const_1:0' shape=(4,) dtype=int32>.
diff: @@ -2100,11 +2100,10 @@ def avg_pool(value, ksize, strides, padding, data_format="NHWC", name=None):
  Args:
  value: A 4-D `Tensor` of shape `[batch, height, width, channels]` and type
  `float32`, `float64`, `qint8`, `quint8`, or `qint32`.
  - ksize: A 1-D int Tensor of 4 elements.
  - The size of the window for each dimension of the input tensor.
  - strides: A 1-D int Tensor of 4 elements
  - The stride of the sliding window for each dimension of the
  - input tensor.
  + ksize: A list or tuple of 4 ints. The size of the window for each dimension
  + of the input tensor.
  + strides: A list or tuple of 4 ints. The stride of the sliding window for
  + each dimension of the input tensor.
  padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
  See the @{tf.nn.convolution$comment here}
  data_format: A string. 'NHWC' and 'NCHW' are supported.
  @@ -2130,10 +2129,10 @@ def max_pool(value, ksize, strides, padding, data_format="NHWC", name=None):
  Args:
  value: A 4-D `Tensor` of the format specified by `data_format`.
  - ksize: A 1-D int Tensor of 4 elements. The size of the window for
  + ksize: A list or tuple of 4 ints. The size of the window for each dimension
  + of the input tensor.
  + strides: A list or tuple of 4 ints. The stride of the sliding window for
  each dimension of the input tensor.
  - strides: A 1-D int Tensor of 4 elements. The stride of the sliding
  - window for each dimension of the input tensor.
  padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm.
  See the @{tf.nn.convolution$comment here}
  data_format: A string. 'NHWC', 'NCHW' and 'NCHW_VECT_C' are supported.
  