optimum/neuron/modeling.py [269:287]:
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        )
    )
    def forward(
        self,
        input_ids: torch.Tensor,
        attention_mask: torch.Tensor,
        token_type_ids: Optional[torch.Tensor] = None,
        **kwargs,
    ):
        neuron_inputs = {
            "input_ids": input_ids,
            "attention_mask": attention_mask,
        }
        if token_type_ids is not None:
            neuron_inputs["token_type_ids"] = token_type_ids

        with self.neuron_padding_manager(neuron_inputs) as inputs:
            outputs = self.model(*inputs)  # shape: [batch_size, sequence_length]
            outputs = self.remove_padding(
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optimum/neuron/models/bert/model.py [207:225]:
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        )
    )
    def forward(
        self,
        input_ids: torch.Tensor,
        attention_mask: torch.Tensor,
        token_type_ids: Optional[torch.Tensor] = None,
        **kwargs,
    ):
        neuron_inputs = {
            "input_ids": input_ids,
            "attention_mask": attention_mask,
        }
        if token_type_ids is not None:
            neuron_inputs["token_type_ids"] = token_type_ids

        with self.neuron_padding_manager(neuron_inputs) as inputs:
            outputs = self.model(*inputs)  # shape: [batch_size, num_labels]
            outputs = self.remove_padding(
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