keras-team/keras · error · ValueError

Forward layer and backward layer are expected to have the sa

Error message

Forward layer and backward layer are expected to have the same value for attribute "{a}", got "{forward_value}" for forward layer and "{backward_value}" for backward layer

What it means

Error "Forward layer and backward layer are expected to have the same value for attribute "{a}", got "{forward_value}" for forward layer and "{backward_value}" for backward layer" thrown in keras-team/keras.

Source

Thrown at keras/src/layers/rnn/bidirectional.py:173

    def _verify_layer_config(self):
        """Ensure the forward and backward layers have valid common property."""
        if self.forward_layer.go_backwards == self.backward_layer.go_backwards:
            raise ValueError(
                "Forward layer and backward layer should have different "
                "`go_backwards` value. Received: "
                "forward_layer.go_backwards "
                f"{self.forward_layer.go_backwards}, "
                "backward_layer.go_backwards="
                f"{self.backward_layer.go_backwards}"
            )

        common_attributes = ("stateful", "return_sequences", "return_state")
        for a in common_attributes:
            forward_value = getattr(self.forward_layer, a)
            backward_value = getattr(self.backward_layer, a)
            if forward_value != backward_value:
                raise ValueError(
                    "Forward layer and backward layer are expected to have "
                    f'the same value for attribute "{a}", got '
                    f'"{forward_value}" for forward layer and '
                    f'"{backward_value}" for backward layer'
                )

    def compute_output_shape(self, sequences_shape, initial_state_shape=None):
        output_shape = self.forward_layer.compute_output_shape(sequences_shape)

        if self.return_state:
            output_shape, state_shape = output_shape[0], output_shape[1:]

        if self.merge_mode == "concat":
            output_shape = list(output_shape)
            output_shape[-1] *= 2
            output_shape = tuple(output_shape)
        elif self.merge_mode is None:
            output_shape = [output_shape, output_shape]

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/layers/rnn/bidirectional.py:173 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/f1242714ae6814a3. Report an issue: GitHub.