Method _process_single

modelscope/pipelines/base.py:272–290

(self, input: Input, *args, **kwargs)

        return collate_fn(data, self.device)

    def _process_single(self, input: Input, *args, **kwargs) -> Dict[str, Any]:
        preprocess_params = kwargs.get('preprocess_params', {})
        forward_params = kwargs.get('forward_params', {})
        postprocess_params = kwargs.get('postprocess_params', {})
        self._check_input(input)
        out = self.preprocess(input, **preprocess_params)

        with device_placement(self.framework, self.device_name):
            if self.framework == Frameworks.torch:
                with torch.no_grad():
                    if self._auto_collate:
                        out = self._collate_fn(out)
                    out = self.forward(out, **forward_params)
            else:
                out = self.forward(out, **forward_params)

        out = self.postprocess(out, **postprocess_params)
        self._check_output(out)
        return out

    def _batch(self, data_list):
        batch_data = {}