docstr: Load from the path that contains an onnx file.
docstr_tok: ["Load","from","the","path","that","contains","an","onnx","file","."]
code: def load(path: str) -> TabularNeuralNetTorchOnnxTransformer:
      """Load from the path that contains an onnx file."""
      import onnx
  
      onnx_bytes = onnx.load(os.path.join(path, "model.onnx"))
      return TabularNeuralNetTorchOnnxTransformer(model=onnx_bytes)
  
imports: import os
  import numpy
label_desc: Use image node_id 4 for calling the TabularNeuralNetTorchOnnxCompiler obj's underlying member method code with example usage: obj.load(path) and returns: TabularNeuralNetTorchOnnxTransformer