class_docstr: Base context class that contains runtime information for any Determined
  workflow that uses the ``tf.keras`` API.
class_docstr_tok: ["Base","context","class","that","contains","runtime","information","for","any","Determined","workflow","that","uses","the","``","tf.keras","``","API","."]
docstr: Return the per-slot batch size. When a model is trained with a single GPU, this is equal to
  the global batch size. When multi-GPU training is used, this is equal to the global batch
  size divided by the number of GPUs used to train the model.
docstr_tok: ["Return","the","per-slot","batch","size",".","When","a","model","is","trained","with","a","single","GPU",",","this","is","equal","to","the","global","batch","size",".","When","multi-GPU","training","is","used",",","this","is","equal","to","the","global","batch","size","divided","by","the","number","of","GPUs","used","to","train","the","model","."]
code: def get_per_slot_batch_size(self) -> int:
      """
      Return the per-slot batch size. When a model is trained with a single GPU, this is equal to
      the global batch size. When multi-GPU training is used, this is equal to the global batch
      size divided by the number of GPUs used to train the model.
      """
      return self._per_slot_batch_size
  
imports: import inspect
  import logging
  from typing import Any, Callable, Dict, List, NamedTuple, Optional, Union, cast
  import tensorflow
  import determined
  from determined import errors, keras, util
  from determined.common import check
  from determined.horovod import hvd
label_desc: Use image node_id 3 for calling the TFKerasTrialContext obj's underlying member method code with example usage: obj.get_per_slot_batch_size() and returns: self