Comments (1)
Please refer to #10. In the evaluation phase there're no batchnorms after pooling layers for fair comparison with existing models.
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Related Issues (20)
- Approximate Architecture Gradient
- Imagenet mobile setting
- Can not reproduce the search result on PTB dataset (Fig3)? HOT 5
- The discrepancy between DARTS and ENAS for RNN cell searching
- Indentation bugs HOT 1
- Why are stem.0.weight different in pretrained and searched CIFAR-10 architectures?
- Questions about DARTS
- Can you tell me how to calculate Search Cost? HOT 1
- When running train,py, why can't I get the same high accuracy as in train_search.py
- Training time on colab HOT 2
- About alpha HOT 1
- RuntimeError: cannot pin 'torch.cuda.DoubleTensor' on GPU on version 0.10.0
- About utils.accuracy
- Broken pipe issue HOT 1
- try to visulize the genotype but got error HOT 1
- Not much comments in code. HOT 2
- Implementation compatible with the recent PyTorch and CUDA version
- Can only achieve 93% accuracy on CIFAR10
- Please upadate codes for latest version of PyTorch
- confuse about the train_search/train/test
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