Comments (10)
@corleonechensiyu @zhuyu-cs onnx-simplifier v0.2.6 is published. It added "--skip-fuse-bn" to avoid these failures. This issue will be closed and the problem should be tracked in onnx/onnx#2677.
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@corleonechensiyu @zhuyu-cs onnx-simplifier v0.2.6 is published. It added "--skip-fuse-bn" to avoid these failures. This issue will be closed and the problem should be tracking in onnx/onnx#2677.
谢谢大老师!
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daquexian dalao!!
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Thanks for your issue! I found it is a bug of onnx optimizers. Would you mind if I share your model with onnx team so that they may try to fix the bug?
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I have posted an issue in ONNX repo: onnx/onnx#2677.
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@corleonechensiyu As a temporary workaround, you can specify --skip-optimization
when runnin onnxsim
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#47 may also help you.
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Related Issues (20)
- [BUG] after simplifing the model swin_tiny_patch4_window7_224 which was created by timm, onnxruntime got errors HOT 1
- [BUG] Message onnx.ModelProto exceeds maximum protobuf size of 2GB error from the latest version HOT 1
- [BUG] After simplification using onnxsim, the model size increased ten times HOT 2
- How to prohibit constant reuse HOT 1
- resnet18 and inception cannot use simplify method HOT 1
- How to prohibit constant reuse HOT 3
- 是否存在选项让simplify只做部分操作,比如只推理shape不做op优化
- Cannot remove shape of ch_PP-OCRv4_rec
- Consecutive squeeze unsqueeze layers could be simplified
- [BUG] unable to install onnxsim 0.4.34/0.4.35 from pypi HOT 5
- [Q&A] 请问可以支持 ConvTranspose + BatchNormalization 的融合吗? HOT 1
- 3 concatenations at the same time? [Request]
- [Request] "ConstantOfShape + Mul(B=0)" is not simplified HOT 1
- [BUG] Simplify removes local functions from the ONNX model HOT 1
- [BUG] onnx.onnx_cpp2py_export.checker.ValidationError: The model does not have an ir_version set properly.
- [BUG] onnx-simplifier==0.4.25 cannot do shape inference in some onnx HOT 3
- [BUG] Shape not supported yet! Tile not supported yet! HOT 1
- ERROR: Could not build wheels for onnxsim, which is required to install pyproject.toml-based projects[BUG]
- [Disscussion] Would mechanism like onnx "register_schema" be helpful in optimizing models with user-defined operators?
- [Request] Preserve input value_info for custom ops
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