src/transformers/models/deberta_v2/configuration_deberta_v2.py/DebertaV2OnnxConfig/generate_dummy_inputs
class DebertaV2OnnxConfig:    def generate_dummy_inputs(
        self,
        preprocessor: Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"],
        batch_size: int = -1,
        seq_length: int = -1,
        num_choices: int = -1,
        is_pair: bool = False,
        framework: Optional["TensorType"] = None,
        num_channels: int = 3,
        image_width: int = 40,
        image_height: int = 40,
        tokenizer: "PreTrainedTokenizerBase" = None,
    ) -> Mapping[str, Any]:
        dummy_inputs = super().generate_dummy_inputs(preprocessor=preprocessor, framework=framework)
        if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
            del dummy_inputs["token_type_ids"]
        return dummy_inputs