class_docstr: A Batch of training/evaluation data.
class_docstr_tok: ["A","Batch","of","training\/evaluation","data","."]
docstr: Iterate over sub-batches of this batch.
  
  Args:
    **batches_kwargs: kwargs passed on to lib_util.batches.
  
  Yields:
    An iterator over sub-Batches.
docstr_tok: ["Iterate","over","sub-batches","of","this","batch",".","Args",":","*","*","batches_kwargs",":","kwargs","passed","on","to","lib_util.batches",".","Yields",":","An","iterator","over","sub-Batches","."]
code: def batches(self, **batches_kwargs):
      """Iterate over sub-batches of this batch.
  
      Args:
        **batches_kwargs: kwargs passed on to lib_util.batches.
  
      Yields:
        An iterator over sub-Batches.
      """
      keys, values = list(zip(*list(self.features.items())))
      for batch in lib_util.batches(*values, **batches_kwargs):
          yield Batch(**dict(lib_util.eqzip(keys, batch)))
  
imports: import os
  from magenta.models.coconet import lib_mask
  from magenta.models.coconet import lib_pianoroll
  from magenta.models.coconet import lib_util
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the Batch obj's underlying member method code with example usage: obj.batches() without return types