models/src/parallel_wavegan/models/melgan.py [195:234]:
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    def remove_weight_norm(self):
        """Remove weight normalization module from all of the layers."""

        def _remove_weight_norm(m):
            try:
                logging.debug(f"Weight norm is removed from {m}.")
                torch.nn.utils.remove_weight_norm(m)
            except ValueError:  # this module didn't have weight norm
                return

        self.apply(_remove_weight_norm)

    def apply_weight_norm(self):
        """Apply weight normalization module from all of the layers."""

        def _apply_weight_norm(m):
            if isinstance(m, torch.nn.Conv1d) or isinstance(
                m, torch.nn.ConvTranspose1d
            ):
                torch.nn.utils.weight_norm(m)
                logging.debug(f"Weight norm is applied to {m}.")

        self.apply(_apply_weight_norm)

    def reset_parameters(self):
        """Reset parameters.

        This initialization follows official implementation manner.
        https://github.com/descriptinc/melgan-neurips/blob/master/mel2wav/modules.py

        """

        def _reset_parameters(m):
            if isinstance(m, torch.nn.Conv1d) or isinstance(
                m, torch.nn.ConvTranspose1d
            ):
                m.weight.data.normal_(0.0, 0.02)
                logging.debug(f"Reset parameters in {m}.")

        self.apply(_reset_parameters)
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models/src/parallel_wavegan/models/melgan.py [468:507]:
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    def remove_weight_norm(self):
        """Remove weight normalization module from all of the layers."""

        def _remove_weight_norm(m):
            try:
                logging.debug(f"Weight norm is removed from {m}.")
                torch.nn.utils.remove_weight_norm(m)
            except ValueError:  # this module didn't have weight norm
                return

        self.apply(_remove_weight_norm)

    def apply_weight_norm(self):
        """Apply weight normalization module from all of the layers."""

        def _apply_weight_norm(m):
            if isinstance(m, torch.nn.Conv1d) or isinstance(
                m, torch.nn.ConvTranspose1d
            ):
                torch.nn.utils.weight_norm(m)
                logging.debug(f"Weight norm is applied to {m}.")

        self.apply(_apply_weight_norm)

    def reset_parameters(self):
        """Reset parameters.

        This initialization follows official implementation manner.
        https://github.com/descriptinc/melgan-neurips/blob/master/mel2wav/modules.py

        """

        def _reset_parameters(m):
            if isinstance(m, torch.nn.Conv1d) or isinstance(
                m, torch.nn.ConvTranspose1d
            ):
                m.weight.data.normal_(0.0, 0.02)
                logging.debug(f"Reset parameters in {m}.")

        self.apply(_reset_parameters)
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