Comments (3)
I have the same problem when i apply quantization to the conv layers' weight.
from deep-compression-pytorch.
@chen-ming2019 明哥,实在没办法了,我没您的联系方式,我想问您一下ECO代码的训练集的准确度,希望您能回复我一下,我得到的是top1=78%,top5=91.5%,我看您top1都达到91%,我想询问您一下具体细节!万分感谢!!!
from deep-compression-pytorch.
@chen-ming2019 明哥,实在没办法了,我没您的联系方式,我想问您一下ECO代码的训练集的准确度,希望您能回复我一下,我得到的是top1=78%,top5=91.5%,我看您top1都达到91%,我想询问您一下具体细节!万分感谢!!!
实在不好意思,我回答不了你的问题,但是希望你可以帮我看看我的问题,我目前代码没有调通。我的错误是:
PS C:\PycharmProjects\HS_Compression\Deep-Compression-PyTorch-master> python weight_share.py saves/model_after_retraining.ptmodel
Traceback (most recent call last):
File "C:\PycharmProjects\HS_Compression\Deep-Compression-PyTorch-master\weight_share.py", line 8, in
import util
File "C:\PycharmProjects\HS_Compression\Deep-Compression-PyTorch-master\util.py", line 8, in
from torchvision import datasets, transforms
ModuleNotFoundError: No module named 'torchvision'
但是我确实已经有了“torchvision”这个模块了
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Related Issues (13)
- Model Size Problem HOT 2
- AttributeError: 'ReLU' object has no attribute 'weight'
- problem in dataloader HOT 2
- dimension error
- weight_shared.py run false
- Why after huffman_encode, why the parameters increase? HOT 1
- Using Deep-Compression in MobileNet-V2
- running bug: HOT 1
- pytorch version HOT 1
- Using LeNet5 HOT 1
- Darknet weights Pruning, Quantisation and Huffman Encoding!
- Custom architecture HOT 1
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