def separable_conv2d_batchnorm(input_layer, filters, strides=1):
output_layer = SeparableConv2DKeras(filters=filters,
kernel_size=3,
strides=strides,
padding='same',
activation='relu')(input_layer)
output_layer = layers.BatchNormalization()(output_layer)
return output_layer
def separable2d_layer(x, filters, kernel_size=3, strides=1, batch_norm=True):
x = SeparableConv2DKeras(filters,
kernel_size,
strides=strides,
padding='same')(x)
if batch_norm:
x = l.BatchNormalization()(x)
return x
