- pin_memory=True
- sigmoid used in cross_entropy_loss
- set_seed before fold and train
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import logging | |
log = logging.getLogger(__name__) | |
log.setLevel(level=logging.DEBUG) | |
fmtr = logging.Formatter("[%(asctime)s] [%(levelname)-8.8s] %(message)s", "%Y-%m-%d %H:%M:%S") | |
fhdlr = logging.FileHandler(f"log.log", mode='w') | |
fhdlr.setFormatter(fmtr) | |
log.addHandler(fhdlr) |
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def set_seed(seed): | |
random.seed(seed) | |
os.environ['PYTHONHASHSEED'] = str(seed) | |
np.random.seed(seed) | |
torch.manual_seed(seed) | |
torch.cuda.manual_seed(seed) | |
torch.backends.cudnn.deterministic = True |
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Keyboard Shortcut Action | |
Windows key Open or close Start Menu. | |
Windows key + A Open Action center. | |
Windows key + C Open Cortana in listening mode. | |
Windows key + D Display and hide the desktop. | |
Windows key + E Open File Explorer. | |
Windows key + G Open Game bar when a game is open. | |
Windows key + H Open the Share charm. | |
Windows key + I Open Settings. | |
Windows key + K Open the Connect quick action. |
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(fa1043)$ conda install ipykernel | |
(fa1043)$ python -m ipykernel install --user --name fa1043 |
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kjupyter() { | |
docker run --runtime=nvidia --ipc=host -v $PWD:/tmp/working -v /data:/tmp/working/data -w=/tmp/working -p 8888:8888 --rm -it kaggle/python-gpu-build bash -c "pip install tornado==4.5.3; export LD_LIBRARY_PATH=/usr/local/cuda/lib64; pip install jupyter_contrib_nbextensions; pip install jupyter_nbextensions_configurator; jupyter contrib nbextension install --user; jupyter nbextension enable toc2/main --user; jupyter notebook --notebook-dir=/tmp/working --ip='*' --port=8888 --no-browser --allow-root" | |
} |
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