code: def _makeShapeTuple(
      self, batch_size, channel_count, data_rank, data_dim, data_layout
  ):
      data_dims = data_rank * (data_dim,)
      if data_layout == "channels_first":
          shape = (batch_size,) + (channel_count,) + data_dims
      elif data_layout == "channels_last":
          shape = (batch_size,) + data_dims + (channel_count,)
      else:
          raise ValueError("Unknown data format")
      return shape
  
imports: import numpy
  from absl.testing import parameterized
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.kernel_tests.nn_ops import bias_op_base
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the BiasAddDeterministicTest obj's underlying member method code with example usage: obj._makeShapeTuple(batch_size, channel_count, data_rank, data_dim, data_layout) and returns: shape