{"id":15704453,"url":"https://github.com/ksdkamesh99/tensorgram","last_synced_at":"2025-04-13T23:54:13.800Z","repository":{"id":54432554,"uuid":"306812687","full_name":"ksdkamesh99/TensorGram","owner":"ksdkamesh99","description":"A real-time remote service to get the tensorflow callbacks to the telegram including the details of metrics--\u003epip install tensorgram","archived":false,"fork":false,"pushed_at":"2021-10-06T05:46:24.000Z","size":1548,"stargazers_count":79,"open_issues_count":9,"forks_count":9,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-03-27T14:03:36.039Z","etag":null,"topics":["keras","telegram-bot","tensorflow","tensorgram"],"latest_commit_sha":null,"homepage":"https://pypi.org/project/tensorgram/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ksdkamesh99.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-10-24T05:27:51.000Z","updated_at":"2023-10-22T14:34:46.000Z","dependencies_parsed_at":"2022-08-13T15:31:01.593Z","dependency_job_id":null,"html_url":"https://github.com/ksdkamesh99/TensorGram","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksdkamesh99%2FTensorGram","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksdkamesh99%2FTensorGram/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksdkamesh99%2FTensorGram/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksdkamesh99%2FTensorGram/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ksdkamesh99","download_url":"https://codeload.github.com/ksdkamesh99/TensorGram/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248799911,"owners_count":21163403,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["keras","telegram-bot","tensorflow","tensorgram"],"created_at":"2024-10-03T20:11:58.505Z","updated_at":"2025-04-13T23:54:13.781Z","avatar_url":"https://github.com/ksdkamesh99.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"A realtime remote service to get the keras callbacks to the telegram including the details of metrics .  \n\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://pypi.org/project/tensorgram/\"\u003e\n    \u003cimg src=\"https://raw.githubusercontent.com/ksdkamesh99/TensorGram/main/Images/tensorgram.gif\" alt=\"Logo\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\n\u003cp align=\"center\"\u003e\n\n[![Downloads](https://pepy.tech/badge/tensorgram)](https://pepy.tech/project/tensorgram)\n[![License](https://img.shields.io/github/license/ksdkamesh99/TensorGram)](https://github.com/ksdkamesh99/TensorGram/blob/main/LICENSE)\n[![Stargazers](https://img.shields.io/github/stars/ksdkamesh99/TensorGram)](https://github.com//ksdkamesh99/TensorGram/stargazers)\n[![Issues](https://img.shields.io/github/issues/ksdkamesh99/TensorGram)](https://github.com/thinktocode/COVID-19-Tracker/issues)\n[![Contributors](https://img.shields.io/github/contributors/ksdkamesh99/TensorGram)](https://img.shields.io/github/contributors/ksdkamesh99/TensorGram)\n[![Top Language](https://img.shields.io/github/languages/top/ksdkamesh99/TensorGram)](https://github.com/thinktocode/COVID-19-Tracker)\n[![Pull Request](https://img.shields.io/github/issues-pr/ksdkamesh99/TensorGram)](https://github.com/thinktocode/COVID-19-Tracker/pulls)\n[![Forks](https://img.shields.io/github/forks/ksdkamesh99/TensorGram)](https://github.com//ksdkamesh99/TensorGram/network/members)\n\n\u003c/p\u003e\n\n\n## Features:-\n\n1. It helps by getting the updates of your model including metrics and loss function graphs which help user the view and get to a statistical conclusion about the model remotely.\n2. It is a biggest advantage for the users who need not spend hours and hours infront of system for watching the updates of the model.\n3. Updates you get are from a telegram bot.\n\n## Installation:-\n\nYou can easily install this telegram using following command.\n```\npip install tensorgram\n```\n## Dependencies/Requirements:-\n\n1. Keras\n2. Tensorflow\n3. Requests\n4. Matplotlib\n\n#### Works on python\u003e=3.7\n\n## How to use:-\n\n* Create a neural network in keras.The sample code is as follows.\n```\nimport tensorflow\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Dense, Dropout, Activation\nimport numpy as np \nfrom tensorflow.keras.optimizers import SGD\n\nX = np.array([[0,0],[0,1],[1,0],[1,1]])\ny = np.array([[0],[1],[1],[0]])\n\nmodel = Sequential()\nmodel.add(Dense(8, input_dim=2))\nmodel.add(Activation('tanh'))\nmodel.add(Dense(1))\nmodel.add(Activation('sigmoid'))\n\nsgd = SGD(learning_rate=0.1)\nmodel.compile(loss='binary_crossentropy', optimizer=sgd,metrics=['accuracy'])\n\n\n\n```\n\n* Now go to Telegram app and search for @tensorgram_bot and join the channel by clicking on the chat.  \n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://pypi.org/project/tensorgram/\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/ksdkamesh99/TensorGram/main/Images/start.jpeg\" width=200px\u003e\n\u003c/a\u003e\n\u003c/p\u003e\n* This application send you the data based on the unique chat id for every user in telegram. So to get your chat id you need to go to search and type @chatid_echo_bot and click on start to get your unique chat id.  \n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://pypi.org/project/tensorgram/\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/ksdkamesh99/TensorGram/main/Images/chatid.jpeg\" width=200px\u003e\n\u003c/a\u003e\n\u003c/p\u003e\n\n\n* Store it safely as it will be required later.  \n\n* Now we need to import the TensorGram from tensorgram library using following code.  \n\n\n```\nfrom tensorgram import TensorGram\n```\n\n* Now we need to create a object of TensorGram by specifying the following attributes like model name and chat id which you obtained before.  \n\n\n```\ntf=TensorGram(\"model-name\",\"123456789\")\n```\n\n* Now you can start training the model and specify the object in the callbacks.  \n\n\n```\nmodel.fit(X, y, batch_size=1, epochs=10,callbacks=[tf],verbose=1)\n```\n\n* Now if you open the telegram app you will find the updates as follows.  \n\n\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://pypi.org/project/tensorgram/\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/ksdkamesh99/TensorGram/main/Images/merged.png\" width=500px float=\"left\"\u003e\n\u003c/a\u003e\n\u003c/p\u003e\n\n\n## Bug / Feature Request:-\n\nIf you find a bug (gave undesired results), kindly open an issue [here](https://github.com/ksdkamesh99/TensorGram/issues/new/choose) by including your search query and the expected result.\n\nIf you'd like to request a new function, feel free to do so by opening an issue [here](https://github.com/ksdkamesh99/TensorGram/issues/new/). Please include sample queries and their corresponding results.\n\n## 💥 How to Contribute ?\n- If you wish to contribute kindly check the [CONTRIBUTING.md](https://github.com/ksdkamesh99/TensorGram/blob/main/CONTRIBUTING.md)🤝\n\n## ❤️ Thanks to our awesome contributors ✨✨\n\n\u003ctable\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\n      \u003ca href=\"https://github.com/ksdkamesh99/TensorGram/graphs/contributors\"\u003e\n        \u003cimg src=\"https://contrib.rocks/image?repo=ksdkamesh99/TensorGram\" /\u003e\n      \u003c/a\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\n[CONTRIBUTORS.md](/CONTRIBUTORS.md)\n\n\n\n## Code of Conduct\n\nYou can find our Code of Conduct [here](/CODE_OF_CONDUCT.md).\n\n\n## Open-source Programs\n\n\nWinter of Code is an open-source program envisioned by DevScript that helps understand the paradigm of Open Source contribution. It aims to bring students into the world of open source development and see the power of unified problem solving in real time.\n\n\u003cimg src=\"https://devscript.tech/woc/img/WOC-logo.png\" width=\"40%\"\u003e\n## License\n\nThis project follows the [MIT License](/LICENSE).\n\n## Contact:-\nFor any kind of suggesstions/ help in code Please mail me at ksdkamesh99@gmail.com.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksdkamesh99%2Ftensorgram","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fksdkamesh99%2Ftensorgram","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksdkamesh99%2Ftensorgram/lists"}