message: added doctest to tf.signal.frame
diff: @@ -68,29 +68,27 @@ def frame(signal, frame_length, frame_step, pad_end=False, pad_value=0, axis=-1,
  For example:
  - ```python
  - # A batch size 3 tensor of 9152 audio samples.
  - audio = tf.random.normal([3, 9152])
  -
  - # Compute overlapping frames of length 512 with a step of 180 (frames overlap
  - # by 332 samples). By default, only 49 frames are generated since a frame
  - # with start position j*180 for j > 48 would overhang the end.
  - frames = tf.signal.frame(audio, 512, 180)
  - frames.shape.assert_is_compatible_with([3, 49, 512])
  -
  - # When pad_end is enabled, the final two frames are kept (padded with zeros).
  - frames = tf.signal.frame(audio, 512, 180, pad_end=True)
  - frames.shape.assert_is_compatible_with([3, 51, 512])
  - ```
  + >>> # A batch size 3 tensor of 9152 audio samples.
  + >>> audio = tf.random.normal([3, 9152])
  + >>>
  + >>> # Compute overlapping frames of length 512 with a step of 180 (frames overlap
  + >>> # by 332 samples). By default, only 49 frames are generated since a frame
  + >>> # with start position j*180 for j > 48 would overhang the end.
  + >>> frames = tf.signal.frame(audio, 512, 180)
  + >>> frames.shape.assert_is_compatible_with([3, 49, 512])
  + >>>
  + >>> # When pad_end is enabled, the final two frames are kept (padded with zeros).
  + >>> frames = tf.signal.frame(audio, 512, 180, pad_end=True)
  + >>> frames.shape.assert_is_compatible_with([3, 51, 512])
  If the dimension along `axis` is N, and `pad_end=False`, the number of frames
  can be computed by:
  ```python
  - frames = 1 + (N - frame_size) // frame_step
  + num_frames = 1 + (N - frame_size) // frame_step
  ```
  If `pad_end=True`, the number of frames can be computed by:
  ```python
  - frames = -(-N // frame_step) # ceiling division
  + num_frames = -(-N // frame_step) # ceiling division
  ```
  Args:
  @@ -106,7 +104,7 @@ def frame(signal, frame_length, frame_step, pad_end=False, pad_value=0, axis=-1,
  name: An optional name for the operation.
  Returns:
  - A `Tensor` of frames with shape `[..., frames, frame_length, ...]`.
  + A `Tensor` of frames with shape `[..., num_frames, frame_length, ...]`.
  Raises:
  ValueError: If `frame_length`, `frame_step`, `pad_value`, or `axis` are not
  