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| from datetime import datetime | |
| from pytz import timezone | |
| import subprocess | |
| import glob | |
| import xml.etree.ElementTree as ET | |
| # replaced time zones | |
| SRC_TZ_ZONES = ['UTC+09:00', 'UTC+01:00'] | |
| # target time zone | |
| TGT_TZ_ZONE = ['Europe/Berlin'] |
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| class MetaGlobalVariables(type): | |
| @property | |
| def HOGE(cls): | |
| return cls._GlobalVariables__hoge # mangling | |
| class GlobalVariables(object, metaclass=MetaGlobalVariables): | |
| __hoge = 'xxxx' | |
| # read OK |
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| # Use Graham's example. | |
| # http://www.phontron.com/slides/nlp-programming-ja-03-ws.pdf | |
| INF = 1e6 | |
| edge_list = [ | |
| None, # e0 | |
| { # e1 | |
| 'id': 1, | |
| 'score': 2.5, | |
| 'begin_node_id': 0, |
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| defaults write com.adobe.illustrator AppleLanguages '("ja")' |
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| import numpy as np | |
| import torch | |
| from torch import nn | |
| class Model(nn.Module): | |
| def __init__(self, vocab_size, embd_size, pre_embd_w=None): | |
| super(Model, self).__init__() | |
| self.embd = nn.Embedding(vocab_size, embd_size, padding_idx=0) |
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| import subprocess | |
| rev = subprocess.check_output(['git', 'describe', '--always']).strip().decode('utf-8') |
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| liens = [line.rstrip('\n') for line in open('file')] |
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| import numpy as np | |
| data = np.array([[40, 35, 80], | |
| [80, 50, 90], | |
| [20, 55, 40], | |
| [94, 80, 88], | |
| [90, 30, 100]]) | |
| print('Input data (N, featuers):', data, data.shape) | |
| N = data.shape[0] | |
| n_dim = data.shape[1] |
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