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Returns the summed penalty by applying regularizer to the weights_list.

Adding a regularization penalty over the layer weights and embedding weights can help prevent overfitting the training data. Regularization over layer biases is less common/useful, but assuming proper data preprocessing/mean subtraction, it usually shouldn't hurt much either.

regularizer A function that takes a single Tensor argument and returns a scalar Tensor output.
weights_list List of weights Tensors or Variables to apply regularizer over. Defaults to the GraphKeys.WEIGHTS collection if None.

A scalar representing the overall regularization penalty.

ValueError If regularizer does not return a scalar output, or if we find no weights.