original_docstring: 
          Takes in the inputs and creates a batch variation of them.
          :param inputs: This is an array or tuple of inputs that will be converted to their batch form.
          :return: The outputs converted to their batch form.
          
docstring: Takes in the inputs and creates a batch variation of them.
docstring_tokens: Takes in the inputs and creates a batch variation of them .
code: def create_batched_inputs(self, inputs):
          """
          Takes in the inputs and creates a batch variation of them.
          :param inputs: This is an array or tuple of inputs that will be converted to their batch form.
          :return: The outputs converted to their batch form.
          """
          outputs = tuple(inputs)
          if self.batch_size > self.mini_batch_size:
              ds = tf.data.Dataset.from_tensor_slices(tuple(inputs)).batch(self.mini_batch_size)
              self.iterator = ds.make_initializable_iterator()
              outputs = self.iterator.get_next()
          return outputs
code_tokens: def create_batched_inputs ( self , inputs ) : outputs = tuple ( inputs ) if self . batch_size > self . mini_batch_size : ds = tf . data . Dataset . from_tensor_slices ( tuple ( inputs ) ) . batch ( self . mini_batch_size ) self . iterator = ds . make_initializable_iterator ( ) outputs = self . iterator . get_next ( ) return outputs
short_docstring: Takes in the inputs and creates a batch variation of them.
short_docstring_tokens: Takes in the inputs and creates a batch variation of them .
comment: """
          Takes in the inputs and creates a batch variation of them.
          :param inputs: This is an array or tuple of inputs that will be converted to their batch form.
          :return: The outputs converted to their batch form.
          """