RSVP for your your local TensorFlow Everywhere event today!

tf.compat.v1.keras.layers.enable_v2_dtype_behavior

View source on GitHub

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.