shubhamagarwal92

from collections import defaultdict

# method 1
my_dict = defaultdict(int)
my_dict[key] += 1

# method 2
my_dict = {}
my_dict[key] = my_dict.get(key, 0) + 1

shubhamagarwal92

tail -f logs.txt
watch -n1 nvidia-smi
htop
watch -n 1 free -h

shubhamagarwal92

# Refer https://fizzylogic.nl/2017/11/06/edit-jupyter-notebooks-over-ssh/

# On server
jupyter notebook --no-browser --port=8080

# On local machine
ssh -N -L 8080:localhost:8080 <remote_user>@<remote_host>

shubhamagarwal92

# https://stackoverflow.com/a/52076633/3776827
# Run as download_drive_file.sh file_id

# where file_id is google drive file id
# https://drive.google.com/file/d/0B-u9nH58139bTy1XRFdqaVEzUGs/view
# Eg. file_id here is  0B-u9nH58139bTy1XRFdqaVEzUGs
curl gdrive.sh | bash -s $1

julia-git

from wordcloud import WordCloud, STOPWORDS
from PIL import Image
import urllib
import requests
import numpy as np
import matplotlib.pyplot as plt

words = 'access guest guest apartment area area bathroom bed bed bed bed bed bedroom block coffee coffee coffee coffee entrance entry francisco free garden guest home house kettle kettle kitchen kitchen kitchen kitchen kitchen kitchenliving located microwave neighborhood new park parking place privacy private queen room san separate seperate shared space space space street suite time welcome'
mask = np.array(Image.open(requests.get('http://www.clker.com/cliparts/O/i/x/Y/q/P/yellow-house-hi.png', stream=True).raw))

peteflorence

Here's a simple implementation of bilinear interpolation on tensors using PyTorch.

I wrote this up since I ended up learning a lot about options for interpolation in both the numpy and PyTorch ecosystems. More generally than just interpolation, too, it's also a nice case study in how PyTorch magically can put very numpy-like code on the GPU (and by the way, do autodiff for you too).

For interpolation in PyTorch, this open issue calls for more interpolation features. There is now a nn.functional.grid_sample() feature but at least at first this didn't look like what I needed (but we'll come back to this later).

In particular I wanted to take an image, W x H x C, and sample it many times at different random locations. Note also that this is different than upsampling which exhaustively samples and also doesn't give us fle

santisbon

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MohamedAlaa

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