Keras Notify Callback
A Tensorflow/Keras callback which sends information about your model training, on various messaging platforms.
Installation
Using pip:
pip install keras-notify
Usage
Import the required module and add it to the list callbacks while training your model.
Example:
>>> from keras-notify import TelegramCallback
>>> telegram_callback = TelegramCallback('<BotToken>',
'<ChatID>',
'CNN Model',
['loss', 'val_loss'],
['accuracy', 'val_accuracy'],
True)
>>> model.fit(x_train, y_train,
batch_size=32,
epochs=10,
validation_data=(x_test, y_test),
callbacks=[telegram_callback])
Telegram
- Create a telegram bot using BotFather
- Search for @BotFather on telegram.
- Send
/helpto get list of all commands. - Send
/newbotto create a new bot and complete the setup. - Copy the bot token after creating the bot.
- Get the chat ID
- Search for the bot you created and send it any random message.
- Go to this URL
https://api.telegram.org/bot<BOT_TOKEN>/getUpdates(replace <BOT_TOKEN> with your bot token) - Copy the
chat idof the user you want to send messages to. - You receive the
chat idonly if you send the message first and then go to the above url.
- Use the
TelegramCallback()class.
TelegramCallback(bot_token=None, chat_id=None, modelName='model', loss_metrics=['loss'], acc_metrics=[], getSummary=False):
Arguments:
bot_token: unique token of Telegram bot{str}chat_id: Telegram chat id you want to send message to{str}modelName: name of your model{str}loss_metrics: loss metrics you want in the loss graph{list of strings}acc_metrics: accuracy metrics you want in the accuracy graphs{list of strings}getSummary: Do you want message for each epoch (False) or a single message containing information about all epochs (True).{bool}
Slack
- Create a Slack workspace
- Create a new channel
- Search for the Incoming Webhooks in the Apps and install it.
- Copy the Webhook URL
- Use the
SlackCallback()class.
SlackCallback(bot_token=None, chat_id=None, modelName='model', loss_metrics=['loss'], acc_metrics=[], getSummary=False):
Arguments:
webhookURL: unique webhook URL of the app{str}channel: channel name or username you want to send message to{str}modelName: name of your model{str}loss_metrics: loss metrics you want in the loss graph{list of strings}acc_metrics: accuracy metrics you want in the accuracy graph{list of strings}getSummary: Do you want message for each epoch (False) or a single message containing information about all epochs (True).{bool}
Sending images in Slack is not supported currently.
ToDo
- Zulip
- Messages
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
keras-notify-0.0.1.tar.gz
(5.2 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file keras-notify-0.0.1.tar.gz.
File metadata
- Download URL: keras-notify-0.0.1.tar.gz
- Upload date:
- Size: 5.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.6.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1534e00288f09615ccc1519aec23bd860092b81d8a1c563afca5378ce81429e6
|
|
| MD5 |
5daa6ec3755946fae84a609ae8474519
|
|
| BLAKE2b-256 |
531fbd6e04a1cba65b4ff40708588976fb4cfe1c2f860bca0654a02097d633a5
|
File details
Details for the file keras_notify-0.0.1-py3-none-any.whl.
File metadata
- Download URL: keras_notify-0.0.1-py3-none-any.whl
- Upload date:
- Size: 4.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.2.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.6.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
88c79a8fd4cf5be95424d6deac4117377f9edef74fb3047fc31527c8b783f618
|
|
| MD5 |
e6e71b45cef10d5e44fafb4db08f4fd6
|
|
| BLAKE2b-256 |
a28c5d935b2fdb58f3d44c050b4a12b3ced4f6d2ff51fae249954601d3ae4d65
|