original_docstring: Decodes a record to a TensorFlow example.
  			
docstring: Decodes a record to a TensorFlow example.
docstring_tokens: Decodes a record to a TensorFlow example .
code: def _decode_record(record, name_to_features):
  			"""Decodes a record to a TensorFlow example.
  			"""
  			example = tf.parse_single_example(record, name_to_features)
  
  			# tf.Example only supports tf.int64, but the TPU only supports tf.int32.
  			# So cast all int64 to int32.
  			for name in list(example.keys()):
  				t = example[name]
  				if t.dtype == tf.int64:
  					t = tf.to_int32(t)
  				example[name] = t
  
  			return example
code_tokens: def _decode_record ( record , name_to_features ) : example = tf . parse_single_example ( record , name_to_features ) for name in list ( example . keys ( ) ) : t = example [ name ] if t . dtype == tf . int64 : t = tf . to_int32 ( t ) example [ name ] = t return example
short_docstring: Decodes a record to a TensorFlow example.
short_docstring_tokens: Decodes a record to a TensorFlow example .
comment: """Decodes a record to a TensorFlow example.
  			"""$SEP$# tf.Example only supports tf.int64, but the TPU only supports tf.int32.$SEP$# So cast all int64 to int32.