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All ONNX models are evaluated with dynamic shape on coco dataset and images are preprocessed according to the original config file. 'Real-time deep hair matting on mobile devices'.In Python mode (ptyhon code is used to directly load".cpkt" parameters for inferecne), I can inferecne normally when I load the input data without using onnx mode, and the code after loading parameters is added at the end. model=toch.jit.script(model) model.save(“model.pt”) If I use a static input shape: python3 -m tf2onnx.convert --opset 11 --graphdef squeezenet.pb --inputs "Placeholder:0[1,224,224,3]" --outputs "softmax_tensor:0,ArgMax:0" --output squeezenet.onnx. I get a Softmax op at the end of the ONNX graph that takes a 2D input from the Flatten op. As expected, the onnx model has axis=1 on the softmax op. If we do not fix the input shape when generating tensorflow saved_model and convert tensorflow saved_model to onnx, we use onnxruntime.InferenceSession to run thi...In Python mode (ptyhon code is used to directly load".cpkt" parameters for inferecne), I can inferecne normally when I load the input data without using onnx mode, and the code after loading parameters is added at the end. model=toch.jit.script(model) model.save(“model.pt”) Oct 10, 2021 · model, check = simplify (model, input_shapes = input_shapes, dynamic_input_shape = True) else: ... help = 'verify the onnx model output against pytorch output ...