def prepare_inputs()

in optimum_benchmark/backends/onnxruntime/backend.py [0:0]

• 11 lines of code
• 7 McCabe index (conditional complexity)

    def prepare_inputs(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
        if self.split_between_processes:
            with Accelerator().split_between_processes(inputs=inputs, apply_padding=False) as process_inputs:
                inputs = process_inputs

        for key, value in inputs.items():
            if isinstance(value, torch.Tensor):
                inputs[key] = value.to(self.config.device)

        for key in list(inputs.keys()):
            if hasattr(self.pretrained_model, "input_names") and key not in self.pretrained_model.input_names:
                inputs.pop(key)

        return inputs