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I have a few issue when running the example
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$ time python3 compress_classifier.py -a alexnet --lr 0.005 -p 50 ../../../data.imagenet -j 44 --epochs 90 --pretrained --compress=../sensitivity-pru…
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We need to find some good options for the classifier to reach a baseline acceptable accuracy:
- [x] Try vgg16, pretrained on imagenet
- [x] Try vgg16, training from scratch
- [ ] Try vgg16, pretrai…
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Hello， thank u for the effective method and clean code!
I try to change your code to run on ImageNet-LT, but get a not so good result.
The config is as follow:
```jsonscript
NAME: 'BBN.ImageNet.co…
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I tried to build a classifier for NeuralHash: It gets NeuralHash as input and outputs class and probability.
I hashed all images of ILSVRC2012 dataset and trained the simple NN model.
Performanc…
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When passing the mean image matrix in the default mean file, i.e. _ilsvrc_2012_mean.npy_, as `mean` to `caffe.Classifier` in _https://github.com/BVLC/caffe/blob/master/python/classify.py_ (master bran…
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I’ve been trying to get the code to work, and it doesn’t seem to produce the results claimed in the paper. After correcting the issues I raised in #2 the code will run, but it will not produce the cor…
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`python
python msunas.py --sec_obj flops --n_gpus 1 --gpu 1 --n_workers 4 --n_epochs 5 --dataset cifar10 --n_classes 10 --data ./data --predictor as --supernet_path data/ofa_mbv3_d234_e346_k357_w1.0 …
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I am struggling to find the implementation for the Fine-Affine experiments shown in Table 1, which seem to be the main contribution of the paper. Could you please help me with this?
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I using alexnet_bn_wrpn in the imagenet dataset. But the result in epoch 36 is lower than Dorefa or PACT or fp32.
This is my config file:
quantizers:
wrpn_quantizer:
class: WRPNQuantizer
…
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Hi, I want to train this for a custom dataset for my research purpose? Can you tell me which scripts I need to run for training a scratch model after modifying dataloader?
tfc-0 updated
5 months ago