class_docstr: Extend Glow for video.
docstr: Get the frames used as input to the model.
  
  Args:
    input_frames: 5-D Tensor, (NTHWC)
    target_frames: 5-D Tensor, (NTHWC)
  Returns:
    frames: 5-D Tensor used as input to the model.
code: def get_all_frames(self, input_frames, target_frames):
      """Get the frames used as input to the model.
  
      Args:
        input_frames: 5-D Tensor, (NTHWC)
        target_frames: 5-D Tensor, (NTHWC)
      Returns:
        frames: 5-D Tensor used as input to the model.
      """
      if self.is_predicting:
          all_frames = input_frames
      elif self.is_training:
          all_frames = tf.concat((input_frames, target_frames), axis=1)
          all_frames = common_video.extract_random_video_patch(
              all_frames, self.hparams.num_train_frames
          )
      # Measure the mean bit-per-pixel of the target_frames during eval.
      else:
          all_frames = tf.concat((input_frames, target_frames), axis=1)
      if self.hparams.cond_first_frame:
          first_frame = all_frames[:, 0:1, :, :, :]
          all_frames = tf.concat((first_frame, all_frames), axis=1)
      return all_frames
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from six.moves import range
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.layers import modalities
  from tensor2tensor.models.research import glow
  from tensor2tensor.models.research import glow_ops
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  import tensorflow_probability
label_desc: Use image node_id 14 for calling the NextFrameGlow obj's underlying member method code with example usage: obj.get_all_frames(input_frames, target_frames) and returns: all_frames