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import torch.nn as N

# Taken by https://github.com/Holmeyoung/crnn-pytorch/blob/master/models/crnn.py
class BackwardHook(N.Module):
  
    
    def backward_hook(self, module, grad_input, grad_output):
        for g in grad_input:
            g[g != g] = 0   

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const mainFunc = () => {
  console.log("Hello World !")
}

if (require.main === module) {
    mainFunc()
}

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# Show all redis values
echo 'KEYS *' | redis-cli | sed 's/^/GET /' | redis-cli 

# Show all redis dictionaries
echo 'KEYS *' | redis-cli | sed 's/^/HGETALL /' | redis-cli 

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# Switch to 5W mode
sudo /usr/sbin/nvpmodel -m 1

# Switch to MAXN mode
sudo /usr/sbin/nvpmodel -m 0

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import onnx
from onnx_tf.backend import prepare
import numpy as np

if __name__ == "__main__":
    model_path = "goat.onnx"
    onnx_model = onnx.load(model_path)
    onnx.checker.check_model(onnx_model,full_check=True)
    tf_model = prepare(onnx_model)

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import cv2
import os
import numpy as np
from shutil import rmtree

if __name__ == "__main__":

    image_dir = "asdf"

    images = list(reversed(os.listdir(image_dir)))

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sudo dpkg --purge --force-remove-reinstreq $(dpkg --get-selections | grep -v "deinstall" | cut -f1 | grep cuda)

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#!/usr/bin/env python
"""
Bundle the site-packages of the current python environment into a zip file

If you have any wheels at `$(pwd)/wheels`, those will be used instead of
of the locally installed packages. For instance, if my pwd looked like

wheels/
|-- numpy-1.11.2-cp27-cp27mu-manylinux1_x86_64.whl

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$IMAGE_NAME="ASDF"

docker run -it --entrypoint /bin/bash $IMAGE_NAME

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Create a new dockerfile containing:

FROM centos:6
ENV FOO=foofoo
RUN export BAR=barbar
RUN export BAZ=bazbaz && echo "$FOO $BAR $BAZ"
Then build it. The output of the last step is:

Step 4/4 : RUN export BAZ=bazbaz && echo "$FOO $BAR $BAZ"
 ---> Running in eb66196b238d