code: def run_onnx_torch(onnx_model, inputs):
      import torch
      from onnx2torch import convert
  
      torch_model = convert(onnx_model).float()
      with torch.no_grad():
          torch_out = torch_model(
              *[torch.tensor(x) for x in inputs.values()]
          )
      return torch_out
  
file_path: tinygrad/test/models/test_onnx.py
imports: import os
  import time
  import unittest
  import numpy
  import onnx
  from extra.onnx import get_run_onnx
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import CI, fetch, temp
label_desc: Use image node_id 1 for calling a global function with example usage: run_onnx_torch(onnx_model, inputs) and returns: torch_out