af461df627ef660d1a71b6981dedb4e4b504ba9a,txtgen/modules/connectors/connectors.py,StochasticConnector,_build,#StochasticConnector#Any#,256

Before Change

                raise ValueError(
                    "Gaussian connector requires tuple input tensors.")

            if len(inputs) == 2:
                input_mu, input_log_var = inputs
                output = sampler(input_mu, input_log_var)

            elif len(inputs) == 3:
                input_mu, input_log_var, context = inputs
                sample = sampler(input_mu, input_log_var)
                output = tf.concat([sample, context], axis=1)
            else:
                raise ValueError("Gaussian connector supports either "
                                 "(mu, logvar) or (mu, logvar, context)")

        else:
            raise ValueError("Unsupported distribution")

        self._add_internal_trainable_variables()

After Change

            the decoder state.
        

        output = inputs.sample()

        try:
            nest.assert_same_structure(inputs, self._decoder_state_size)
        except (ValueError, TypeError):

Instances