fairseq/modules/dynamic_convolution.py [200:216]:
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        output = torch.bmm(weight_expanded, x)
        output = output.transpose(0, 1).contiguous().view(T, B, C)
        return output

    def reorder_incremental_state(self, incremental_state, new_order):
        input_buffer = self._get_input_buffer(incremental_state)
        if input_buffer is not None:
            input_buffer = input_buffer.index_select(1, new_order)
            self._set_input_buffer(incremental_state, input_buffer)

    def _get_input_buffer(self, incremental_state):
        return utils.get_incremental_state(self, incremental_state, 'input_buffer')

    def _set_input_buffer(self, incremental_state, new_buffer):
        return utils.set_incremental_state(self, incremental_state, 'input_buffer', new_buffer)

    def extra_repr(self):
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fairseq/modules/lightweight_convolution.py [216:232]:
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        output = torch.bmm(weight_expanded, x)
        output = output.transpose(0, 1).contiguous().view(T, B, C)
        return output

    def reorder_incremental_state(self, incremental_state, new_order):
        input_buffer = self._get_input_buffer(incremental_state)
        if input_buffer is not None:
            input_buffer = input_buffer.index_select(1, new_order)
            self._set_input_buffer(incremental_state, input_buffer)

    def _get_input_buffer(self, incremental_state):
        return utils.get_incremental_state(self, incremental_state, 'input_buffer')

    def _set_input_buffer(self, incremental_state, new_buffer):
        return utils.set_incremental_state(self, incremental_state, 'input_buffer', new_buffer)

    def extra_repr(self):
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