this two block don't define in the block.py and don't support float64 when net = tf_slim.batch_norm(net, is_training=is_training)

[davidxiaozhi]

blocks_to_use: "CIFAR_NASA_REDUCTION"
blocks_to_use: "CIFAR_NASA"

this two block don't define in the block.py

[davidxiaozhi]

When setting tf.keras.backend. Set floatx('float64') when training based on images, since the image is float64

 if self._apply_batch_norm:
      net = tf_slim.batch_norm(net, is_training=is_training) # don't support float64 
      # net = tf_slim.batch_norm(net, is_training=is_training, fused=False) #support float64 

There is another way to cast float32 via type casting, but this also doesn't work very well. We recommend modifying block.py to provide a flexible API

[alexgoft]

@davidxiaozhi have you found a solution?