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boto3==1.13.5
category-encoders==2.1.0
distributed==2.15.2
elasticsearch-dsl==7.0.0
fdict==0.8.1
fire==0.3.1
funcy==1.13
google-api-python-client==1.7.11
google-auth-oauthlib==0.4.0
gspread==3.1.0
@yabebalFantaye
yabebalFantaye / semantic_transfer_learning.py
Created August 4, 2017 14:07 — forked from prats226/semantic_transfer_learning.py
Sentiment classification using transfer learning
import collections, math, random, numpy
import tensorflow as tf
from sklearn.cross_validation import train_test_split
sentences = """hated the movie it was stupid;\ni hated it so boring;\nawesome the movie was inspiring;\nhated it what a disaster;\nwe hated the movie they were idiotic;\nhe was stupid, hated her;\nstupid movie is boring;\ninspiring ourselves, awesome;\ninspiring me, brilliant;\nwe hated it they were rubbish;\nany inspiring movie is amazing;\nit was stupid what a disaster;\nits stupid, rubbish;\nstupid, idiotic!;\nawesome great movie;\nboring, must be hated;\nhe was boring the movie was stupid;\nboring movie was a disaster;\nboth boring and rubbish;\nso boring and idiotic;\ngreat to amazing;\ndisaster, more than hated;\nbetween disaster and stupid;\ndisaster, so boring;\nawesome movie, brilliant;\ntoo awesome she was amazing;\nhe was brilliant loved it;\ndisaster, only idiotic;\nrubbish movie hated him;\nit was rubbish, why so stupid?;\nrubbish, too boring;\nrubbish, disaster!;\nrubbish, very
#!/bin/bash
#SBATCH
if [[ "$SLURM_PROCID" = "0" ]]; then
ssh -R 0.0.0.0:9999:localhost:8888 -f -N login-0-1
jupyter notebook
elif [[ "$SLURM_PROCID" = "1" ]]; then
ipcontroller --ip='*'
elif [[ "$SLURM_PROCID" = "2" ]]; then
mpirun --bind-to=none -n "$((SLURM_NTASKS-2))" ipengine
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