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Use Keras-style variable management.
tf.compat.v1.layers.experimental.set_keras_style()
All tf.layers and tf RNN cells created after keras style ha been enabled use Keras-style variable management. Creating such layers with a scope= argument is disallowed, and reuse=True is disallowed.
The purpose of this function is to allow users of existing layers to slowly transition to Keras layers API without breaking existing functionality.
For more details, see the documentation for keras_style_scope.
Note, once keras style has been set, it is set globally for the entire program and cannot be unset.
Example:
set_keras_style()
model_1 = RNNModel(name="model_1")
model_2 = RNNModel(name="model_2")
# model_1 and model_2 are guaranteed to create their own variables.
output_1, next_state_1 = model_1(input, state)
output_2, next_state_2 = model_2(input, state)
assert len(model_1.weights) > 0
assert len(model_2.weights) > 0
assert(model_1.weights != model_2.weights)