tf.keras.StatelessScope

Scope to prevent any update to Keras Variables.

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.StatelessScope

The values of variables to be used inside the scope should be passed via the state_mapping argument, a list of tuples (k, v) where k is a KerasVariable and v is the intended value for this variable (a backend tensor).

Updated values can be collected on scope exit via value = scope.get_current_value(variable). No updates will be applied in-place to any variables for the duration of the scope.

Example:

state_mapping = [(k, ops.ones(k.shape, k.dtype)) for k in model.weights]
with keras.StatelessScope(state_mapping) as scope:
    outputs = model.some_function(inputs)

# All model variables remain unchanged. Their new values can be
# collected via:
for k in model.weights:
    new_value = scope.get_current_value(k)
    print(f"New value for {k}: {new_value})

Methods

add_loss

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add_update

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get_current_value

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__enter__

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__exit__

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