Comments (6)
Show me the source code, I will check where the error is.
from torch-model-compression.
Hello, you may try the patch in https://github.com/THU-MIG/torch-model-compression/pull/6/files#diff-cd7d0b02724faaf1716aee410c2cc83b91a053f1f6e8dc9475761156a69a6286R50-R52
from torch-model-compression.
I've merged #6, so you may run git pull
on your local repo and reinstall it.
from torch-model-compression.
I've merged #6, so you may run
git pull
on your local repo and reinstall it.
Thanks for your in-time reply. I tried to pull the latest code and retrain, but got such error message:
Traceback (most recent call last):
File "tasks/prune_helmet.py", line 158, in
solver.run()
File "/home/bengui/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torchpruner-0.0.1-py3.6.egg/torchslim/slim_solver.py", line 327, in run
File "/home/bengui/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/optim/lr_scheduler.py", line 67, in wrapper
return wrapped(*args, **kwargs)
File "/home/bengui/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
return func(*args, **kwargs)
File "/home/bengui/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/optim/sgd.py", line 106, in step
buf.mul_(momentum).add_(d_p, alpha=1 - dampening)
RuntimeError: The size of tensor a (96) must match the size of tensor b (88) at non-singleton dimension 0
from torch-model-compression.
pull the latest code, and try it again. The error has been fixed.
from torch-model-compression.
pull the latest code, and try it again. The error has been fixed.
I tried it again and the error had been fixed.
from torch-model-compression.
Related Issues (20)
- Does there any params and speed comparasion on common models? HOT 2
- examples中prune.py运行报错 HOT 7
- self.index_mapping 代表什么意思?它是用来作什么的? HOT 1
- torchslim中在cifar10上的示例代码输出为64维,而不是10维 HOT 3
- 是否有相关的文章支持 HOT 2
- 有没有实验yolo系列QAT感知量化训练模型? HOT 1
- About how to import self-built models for compression HOT 1
- 关于resnet和自建模型prune时遇到的相同报错 HOT 1
- 剪枝时前面的层数正常,最后几层在对齐masks same size时报错
- Can the QAT-quantized model calculate inference speed? HOT 1
- 关于ResRep模型性能对比 HOT 4
- About parameter Settings during training HOT 4
- yolov5 resrep剪枝 HOT 5
- qat量化能够导出onnx,能够在tensorrt上进行部署吗? HOT 3
- resnet50剪枝报错 HOT 1
- How to quantize and compress the trained model??? HOT 1
- 剪枝分割网络报错-bisenetv2 HOT 17
- demo中剪枝后预测结果差距很大? HOT 15
- BiSeNet是否已经支持 HOT 1
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from torch-model-compression.