Comments (1)
I solve the problem.
Backend default is channel last. (B, H, W, C)
axis is an argument of BatchNorm and Concatenate.
axis = 1 refers to channel first (B, C, H, W)
axis = 3 refers to channel last (B, H, W, C)
I set channel last for input shape.
img_input = layers.Input(shape=(512, 512, 3), name='data')
But I set channel first for batchnorm and concatenate.
x = layers.BatchNormalization(name='bn_data', **{'axis': 1, 'momentum': 0.99, 'epsilon': 2e-5, 'center': True, 'scale': False})(img_input)
from classification_models.
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from classification_models.