/home/hx/anaconda3/envs/py38_TensorRT/bin/python /home/hx/TensorRT/Palette-infer-demo/Palette-Image-to-Image-Diffusion-Models-main/pth2onnx.py
/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/nn/functional.py:2515: UserWarning: floordiv is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the ‘trunc’ function NOT ‘floor’). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode=‘trunc’), or for actual floor division, use torch.div(a, b, rounding_mode=‘floor’).
_verify_batch_size([input.size(0) * input.size(1) // num_groups, num_groups] + list(input.size()[2:]))
/home/hx/TensorRT/Palette-infer-demo/Palette-Image-to-Image-Diffusion-Models-main/models/guided_diffusion_modules/unet.py:271: UserWarning: floordiv is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the ‘trunc’ function NOT ‘floor’). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode=‘trunc’), or for actual floor division, use torch.div(a, b, rounding_mode=‘floor’).
ch = width // (3 * self.n_heads)
/home/hx/TensorRT/Palette-infer-demo/Palette-Image-to-Image-Diffusion-Models-main/models/guided_diffusion_modules/unet.py:273: TracerWarning: Converting a tensor to a Python float might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
scale = 1 / math.sqrt(math.sqrt(ch))
/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/onnx/utils.py:461: UserWarning: no signature found for <torch.ScriptMethod object at 0x7fe79c132720>, skipping _decide_input_format
warnings.warn(“%s, skipping _decide_input_format” % e)
Traceback (most recent call last):
File “/home/hx/TensorRT/Palette-infer-demo/Palette-Image-to-Image-Diffusion-Models-main/pth2onnx.py”, line 55, in
torch.onnx.export(unet_script, input, onnx_model, opset_version=13)
File “/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/onnx/init.py”, line 350, in export
return utils.export(
File “/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/onnx/utils.py”, line 163, in export
_export(
File “/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/onnx/utils.py”, line 1074, in _export
graph, params_dict, torch_out = _model_to_graph(
File “/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/onnx/utils.py”, line 727, in _model_to_graph
graph, params, torch_out, module = _create_jit_graph(model, args)
File “/home/hx/anaconda3/envs/py38_TensorRT/lib/python3.8/site-packages/torch/onnx/utils.py”, line 582, in _create_jit_graph
module, params = _C._jit_onnx_list_model_parameters(freezed_m)
RuntimeError:
Couldn’t export Python method.:
The error message did not indicate which operator is incompatible, and I am unable to locate the specific error location.