fix tensorflow batchorm default momentum for mobilenet

set_batchnorm_momentum.py

"""
The default momentum of MobileNet (for running average calculation) in tf seems to be very high (0.99?), resulting in huge (and suprising) differences in train vs evaluate loss

https://github.com/keras-team/keras/issues/6977

Setting it to something sensible (e.g. 0.9) fixes this 

https://stackoverflow.com/questions/65415799/fit-works-as-expected-but-then-during-evaluate-model-performs-at-chance/66692755#66692755
"""

def fix_batchnorm(model, new_value=0.9, prefix=''):
  for ii, layer in enumerate(model.layers):
    if hasattr(layer, 'layers'):
      fix_batchnorm(layer, new_value, f'{prefix}Layer {ii}/')
      continue
    elif isinstance(layer, tf.keras.layers.BatchNormalization):
      layer.momentum = new_value

      
...

fix_batchnorm(model)