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import json
def read_json(path, encoding = 'utf-8'):
    with open(path, encoding = encoding) as f:
        return json.load(f)
def write_json(data, path, encoding = 'utf-8'):
    with open(path, 'w', encoding = encoding) as f:
        return json.dump(data, f)

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local_account@local_hostname$ ssh -L 12345:0.0.0.0:12345 remote_account@remote_hostname
remote_account@remote_hostname$ python -m http.server 12345
# open http://localhost:12345/ on local computer browser

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Usage (Official Repo):
https://github.com/magnumripper/JohnTheRipper

Ubuntu Install Guide: 
https://github.com/magnumripper/JohnTheRipper/blob/bleeding-jumbo/doc/INSTALL-UBUNTU

Other install guides can be found in:
https://github.com/magnumripper/JohnTheRipper/blob/bleeding-jumbo/doc/
https://github.com/magnumripper/JohnTheRipper/blob/bleeding-jumbo/doc/INSTALL
https://github.com/magnumripper/JohnTheRipper/blob/bleeding-jumbo/doc/INSTALL-FEDORA

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reference: https://stackoverflow.com/a/52112850/10214604

$apt install r-base

$vim 1.r

r = getOption("repos")
r["CRAN"] = "http://cran.us.r-project.org"
options(repos = r)

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from argparse import ArgumentParser
def main(args):
  
if __name__ == '__main__':
	parser = ArgumentParser()
	parser.add_argument('--int', type=int, default=0, help='')
	parser.add_argument('--str', type=str, default='', help='')
  parser.add_argument('--action', action='store_true', help='')
	args = parser.parse_args()
  # args = parser.parse_args('') if in jupyter notebook

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import random
import numpy as np
import torch
def set_seed(seed):
	random.seed(seed)
	np.random.seed(seed)
	torch.manual_seed(seed)
	torch.cuda.manual_seed_all(seed)
	torch.backends.cudnn.deterministic = True
	torch.backends.cudnn.benchmark = False

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"""

讓encoder能disentangleword跟style才會學得好 像fontgan那樣
相同的word/style的embedding要接近，用F.pairwise_distance 
然後要能decode出來，用l1_loss，
"""
class Encoder(nn.Module):
    def __init__():
        self.encoder = Encoder()
        self.style = nn.Linear()