tf.compat.v1.keras.layers.enable_v2_dtype_behavior

Enable the V2 dtype behavior for Keras layers.

By default, the V2 dtype behavior is enabled in TensorFlow 2, so this function is only useful if tf.compat.v1.disable_v2_behavior has been called. Since mixed precision requires V2 dtype behavior to be enabled, this function allows you to use mixed precision in Keras layers if disable_v2_behavior has been called.

When enabled, the dtype of Keras layers defaults to floatx (which is typically float32) instead of None. In addition, layers will automatically cast floating-point inputs to the layer's dtype.

x = tf.ones((4, 4, 4, 4), dtype='float64')
layer = tf.keras.layers.Conv2D(filters=4, kernel_size=2)
print(layer.dtype)  # float32 since V2 dtype behavior is enabled
float32
y = layer(x)  # Layer casts inputs since V2 dtype behavior is enabled
print(y.dtype.name)
float32

A layer author can opt-out their layer from the automatic input casting by passing autocast=False to the base Layer's constructor. This disables the autocasting part of the V2 behavior for that layer, but not the defaulting to floatx part of the V2 behavior.

When a global tf.keras.mixed_precision.experimental.Policy is set, a Keras layer's dtype will default to the global policy instead of floatx. Layers will automatically cast inputs to the policy's compute_dtype.