├── .gitignore
├── README.md
├── callbacks
    ├── __init__.py
    └── telegram_callback.py
└── requerments.txt


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/README.md:
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 1 | ## Keras callback in Telegram
 2 | Telegram-bot callback for your Keras model  
 3 | 
 4 | This module allows your model to send learning history to your chat in Telegram messenger.  
 5 | 
 6 | ### Configure your Telegram Callback
 7 | To start use this callback you need fo register bot in telegram and get your `telegram_id`. Follow instructions below.
 8 | 
 9 | #### Step 1. Register your telegram bot.  
10 |  - Find `BotFather` in Telegram.
11 |  - Follow `BotFather` instructions to register your bot in a few steps and get `token`.
12 | 
13 | #### Step 2. Get your ID.
14 |  - Find `@my_id_bot` bot in Telegram and get your `telegram_id`. If bot is not working get `telegram_id` manually (step 2a).  
15 | 
16 | #### Step 2a. Get your ID (optional).
17 |  - Find your bot in telegram and send message 'hello!'
18 |  - Paste in your browser `api.telegram.org/bot<token>/getUpdates` (use token you get in previous step), if you did everything correctly you will recive a JSON where you can find your `telegram_id`.
19 | 
20 | ### Example
21 | 
22 | ```python
23 | from .callbacks import TelegramCallback
24 | 
25 | # load data, define and compile model
26 | ...
27 | 
28 | # create callback
29 | config = {
30 |     'token': '556983321:AAHO-bSWaIqcvHL91Xw12X18OWczFIpY1s0',   # paste your bot token
31 |     'telegram_id': 123456789,                                   # paste your telegram_id
32 | }
33 | 
34 | tg_callback = TelegramCallback(config)
35 | 
36 | # start training
37 | model.fit(x, y, batch_size=32, callbacks=[tg_callback])
38 | ```
39 | 
40 | Congratulations! Now you will recive logs (losses, metrics, lr, etc.) in Telegram!
41 | 


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/callbacks/__init__.py:
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1 | from .telegram_callback import TelegramCallback


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/callbacks/telegram_callback.py:
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 1 | import telegram
 2 | from keras.callbacks import Callback
 3 | 
 4 | 
 5 | class TelegramCallback(Callback):
 6 | 
 7 |     def __init__(self, config, name=None):
 8 |         super(TelegramCallback, self).__init__()
 9 |         self.user_id = config['telegram_id']
10 |         self.bot = telegram.Bot(config['token'])
11 |         if name != None:
12 |             self.name = name
13 |         else:
14 |             self.name = self.model.name
15 | 
16 |     def send_message(self, text):
17 |         try:
18 |             self.bot.send_message(chat_id=self.user_id, text=text)
19 |         except Exception as e:
20 |             print('Message did not send. Error: {}.'.format(e))
21 | 
22 |     def on_train_begin(self, logs={}):
23 |         text = 'Start training model {}.'.format(self.name)
24 |         self.send_message(text)
25 | 
26 |     def on_train_end(self, logs={}):
27 |         text = 'Training model {} ended.'.format(self.name)
28 |         self.send_message(text)
29 | 
30 |     def on_epoch_end(self, epoch, logs={}):
31 |         text = '{}: Epoch {}.\n'.format(self.name, epoch)
32 |         for k, v in logs.items():
33 |             if k != "lr":
34 |                 text += '{}: {:.4f}; '.format(k, v)
35 |             else:
36 |                 text += '{}: {:.6f}; '.format(k, v) #4 decimal places too short for learning rate
37 |         self.send_message(text)
38 | 


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/requerments.txt:
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1 | python-telegram-bot==10.0.2
2 | keras==2.1.4
3 | 


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