尝试使用ONNX转换this pytorch模型时出现此错误。我搜索过github,这个错误以前在1.1.0版本中出现过,但显然已经被纠正了。现在我使用的是torch 1.4.0。(python 3.6.9),我看到了这个错误。
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/init.py", line 148, in export
strip_doc_string, dynamic_axes, keep_initializers_as_inputs)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 66, in export
dynamic_axes=dynamic_axes, keep_initializers_as_inputs=keep_initializers_as_inputs)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 416, in _export
fixed_batch_size=fixed_batch_size)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 296, in _model_to_graph
fixed_batch_size=fixed_batch_size, params_dict=params_dict)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 135, in _optimize_graph
graph = torch._C._jit_pass_onnx(graph, operator_export_type)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/init.py", line 179, in _run_symbolic_function
return utils._run_symbolic_function(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/utils.py", line 657, in _run_symbolic_function
return op_fn(g, *inputs, **attrs)
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/symbolic_helper.py", line 128, in wrapper
args = [_parse_arg(arg, arg_desc) for arg, arg_desc in zip(args, arg_descriptors)]
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/symbolic_helper.py", line 128, in
args = [_parse_arg(arg, arg_desc) for arg, arg_desc in zip(args, arg_descriptors)]
File "/usr/local/lib/python3.6/dist-packages/torch/onnx/symbolic_helper.py", line 81, in _parse_arg
"', since it's not constant, please try to make "
RuntimeError: Failed to export an ONNX attribute 'onnx::Gather', since it's not constant, please try to make things (e.g., kernel size) static if possible如何修复它?我也尝试了最新的夜间构建,同样的错误也出现了。
我的代码:
from model import BiSeNet
import torch.onnx
import torch
net = BiSeNet(19)
net.cuda()
net.load_state_dict(torch.load('/content/drive/My Drive/Collab/fp/res/cp/79999_iter.pth'))
net.eval()
dummy = torch.rand(1,3,512,512).cuda()
torch.onnx.export(net, dummy, "Model.onnx", input_names=["image"], output_names=["output"])在引发运行时错误之前,我向symbolic_helper.py添加了print (v.node ()),以查看是什么导致了该错误。
这是输出:%595 : Long() = onnx::Gather[axis=0](%592, %594) # /content/drive/My Drive/Collab/fp/model.py:111:0
在model.py的第111行是:avg = F.avg_pool2d(feat32, feat32.size()[2:])
此source表明pytorch中的tensor.size方法无法被onnx识别,需要修改为常量。
发布于 2021-01-01 01:40:08
我曾经在使用以下命令导出时遇到过类似的错误
torch.onnx.export(model, x, ONNX_FILE_PATH)
我通过如下所示指定opset_version来修复它:
torch.onnx.export(model, x, ONNX_FILE_PATH, opset_version = 11)
发布于 2020-05-22 01:56:17
您可以:
print(feat32.size()[2:])并替换为:
F.avg_pool2d(feat32, feat32.size()[2:]) 通过以下方式:
F.avg_pool2d(feat32, your_print_contant_result)发布于 2020-06-03 16:53:48
我也为同样的问题而苦苦挣扎。
在我的情况下,不支持F.adaptive_avg_pool2d。您必须尝试其他操作。
我希望这能帮到你。
谢谢
https://stackoverflow.com/questions/60682622
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