This renorm argument with BatchNormalization() was available in Tensorflow 1.x which got replaced by training argument in newer Tensorflow 2.x versions which has Python boolean values - True/False.

These Python boolean indicating whether the layer should behave in training mode or in inference mode.

• training=True: The layer will normalize its inputs using the mean and variance of the current batch of inputs.
• training=False: The layer will normalize its inputs using the mean and variance of its moving statistics, learned during training.

Please have a look at the BatchNormlization() API for more details. Thank you