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# Working example for my blog post at:
# https://danijar.github.io/structuring-your-tensorflow-models
import functools
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data


def doublewrap(function):
    """
    A decorator decorator, allowing to use the decorator to be used without

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词的分类

• 实词：名词、动词、形容词、状态词、区别词、数词、量词、代词
• 虚词：副词、介词、连词、助词、拟声词、叹词。

ICTPOS3.0词性标记集

n 名词

nr 人名

ansvver

#  pandas输出格式
import pandas as pd
pd.set_option('display.height', 1000)
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
pd.set_option('display.expand_frame_repr', False)

# 设置数据格式，避免比较大的数据以科学计数法显示
pd.set_option('display.float_format', lambda x: '%.3f' % x)

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#!/usr/bin/env python
# coding: utf-8

def dict2dot(foo, bar):
    for k, v in foo.items():
        if not isinstance(v, dict):
            bar[k] = v
            continue
        for kk, vv in v.items():
            dict2dot({'{}.{}'.format(k, kk): vv}, bar)

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import bisect

class NFA(object):
  EPSILON = object()
  ANY = object()
  
  def __init__(self, start_state):
    self.transitions = {}
    self.final_states = set()
    self._start_state = start_state

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# List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

# Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

# Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(valuelist)]

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Python Cheatsheet
=================

 ################################ Input & Output ###############################
name = input('please enter your name: ')
print('hello,', name)
ageStr = input('please enter your age: ')
age = int(ageStr)

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#!/usr/bin/python

import smtplib
from email.MIMEMultipart import MIMEMultipart
from email.MIMEBase import MIMEBase
from email.MIMEText import MIMEText
from email import Encoders
import os

gmail_user = "your_email@gmail.com"