src/transformers/models/vision_encoder_decoder/configuration_vision_encoder_decoder.py/VisionEncoderDecoderDecoderOnnxConfig/generate_dummy_inputs
class VisionEncoderDecoderDecoderOnnxConfig:    def generate_dummy_inputs(
        self,
        tokenizer: "PreTrainedTokenizerBase",
        batch_size: int = -1,
        seq_length: int = -1,
        is_pair: bool = False,
        framework: Optional["TensorType"] = None,
    ) -> Mapping[str, Any]:
        import torch

        common_inputs = OrderedDict()

        dummy_input = super().generate_dummy_inputs(
            tokenizer, batch_size=batch_size, seq_length=seq_length, is_pair=is_pair, framework=framework
        )

        batch, encoder_sequence = dummy_input["input_ids"].shape
        encoder_hidden_states_shape = (batch, encoder_sequence, self._config.encoder_hidden_size)
        common_inputs["input_ids"] = dummy_input.pop("input_ids")
        common_inputs["attention_mask"] = dummy_input.pop("attention_mask")
        common_inputs["encoder_hidden_states"] = torch.zeros(encoder_hidden_states_shape)

        return common_inputs