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# Based on implementations
# - vae core https://github.com/pytorch/examples/blob/master/vae/main.py
# - miwae https://github.com/yoonholee/pytorch-vae
# - notes on VAE from the article at https://iopscience.iop.org/article/10.3847/PSJ/ab9a52 (but can be taken from elsewhere too)

from __future__ import print_function
import argparse
import torch
import torch.utils.data
from torch import nn, optim

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# https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_gui/py_trackbar/py_trackbar.html#trackbar

import cv2
import numpy as np

class GUIHandler(object):

    def onChangeSend(self,x):

        self.A = cv2.getTrackbarPos('A', self.window_name)

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# v1

import mock
settings = mock.Mock()
settings.foo = 42


# v2
# works even when checking for non-existing entries...

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Safe combination for Windows 10 (crazy, eh?)

GPU: GeForce 1050 Ti

Working:
Cuda 10 -> cuda_10.0.130_411.31_win10
Cudnn for it -> cudnn-10.0-windows10-x64-v7.6.5.32(for CUDA 10.0).zip
Python 3.7.7
Tensorflow-gpu 1.14.0 -> pip3 install --upgrade tensorflow-gpu==1.14.0

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import numpy as np
good_colors = [ #qualitative - http://colorbrewer2.org/#type=qualitative&scheme=Set1&n=6
               (228, 26, 28),  #red
               (55, 126, 184), #blue
               (77, 175, 74),  #lightgreen
               (152, 78, 163), #violet
               (255, 127, 0),  #orange
               (255, 255, 51), #yellow
               (166, 86, 40),  #brown orange
               (247, 129, 191) #pink

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find SOURCEDIR/ -type f | shuf -n $(shuf -i30000-30000 -n1) | tr '\n' '\0' | xargs -0 -n1 cp -t TARGETDIR/

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# add padding to the image to be at 360x360 px
ffmpeg -i image.jpg -qscale 0 -vf "pad=360:360:360:360:color=black" imagePad.jpg

# auto overwrite
ffmpeg -y -i image.jpg -qscale 0 -vf "pad=360:360:360:360:color=black" image.jpg

# for all files in a folder
for file in *.jpg; do ffmpeg -y -i $file -qscale 0 -vf "pad=360:360:360:360:color=black" $file; done

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import librosa
import numpy as np

# Variables setup:
fft_size=2048
window_size=2048 # window size
hop_size=512     # window shift size
sample_rate=44100
lws_L = 5

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# New remote

git remote add newremote https://github.com/user/repo.git
git push newremote master

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import matplotlib, os
if not('DISPLAY' in os.environ):
    matplotlib.use("Agg")

import DataLoader, DataPreprocesser, Dataset, Debugger, Settings, ModelHandler, Evaluator
from timeit import default_timer as timer
from datetime import *

months = ["unk","jan","feb","mar","apr","may","jun","jul","aug","sep","oct","nov","dec"]
month = (months[datetime.now().month])