def forward()

in summarize_from_feedback/models/transformer.py [0:0]

• 13 lines of code
• 3 McCabe index (conditional complexity)

    def forward(self, x, hidden_states=None):
        """
        x:              input tensor
        hidden_state:   list of hidden_states, one for each resblock
                        if None, then becomes [None] * n_layer

        returns
        x:                      The output of the layers
        output_hidden_states:   A list of size self.resblocks with each hidden_state
        """
        if hidden_states is None:
            hidden_states = [None] * len(self.resblocks)
        else:
            hidden_states = hidden_states

        assert len(hidden_states) == len(
            self.resblocks
        ), f"number of hidden states should match number of resblocks: {len(hidden_states)} != {len(self.resblocks)}"

        output_hidden_states = []
        # Blocks
        for l, hidden_state in zip(self.resblocks, hidden_states):
            x, output_hidden_state = l(x, hidden_state=hidden_state)
            output_hidden_states.append(output_hidden_state)

        return x, output_hidden_states