class_docstr: MovingMnist.
docstr: Generate MovingMnist sequences.
  
  Args:
    data_path (str): Path to the data file
  
  Yields:
    20 x 64 x 64 x 1 uint8 numpy arrays
docstr_tok: ["Generate","MovingMnist","sequences",".","Args",":","data_path","(","str",")",":","Path","to","the","data","file","Yields",":","20","x","64","x","64","x","1","uint8","numpy","arrays"]
code: def _generate_examples(self, data_path):
      """Generate MovingMnist sequences.
  
      Args:
        data_path (str): Path to the data file
  
      Yields:
        20 x 64 x 64 x 1 uint8 numpy arrays
      """
      with tf.io.gfile.GFile(data_path, "rb") as fp:
          images = np.load(fp)
      images = np.transpose(images, (1, 0, 2, 3))
      images = np.expand_dims(images, axis=-1)
      for i, sequence in enumerate(images):
          yield i, dict(image_sequence=sequence)
  
file_path: datasets/tensorflow_datasets/video/moving_mnist.py
imports: import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
  from tensorflow_datasets.video.moving_sequence import image_as_moving_sequence
label_desc: Use image node_id 3 for calling the MovingMnist obj's underlying member method code with example usage: obj._generate_examples(data_path) without return types