{"id":13689229,"url":"https://github.com/SymJAX/SymJAX","last_synced_at":"2025-05-01T23:33:07.187Z","repository":{"id":57472860,"uuid":"206337751","full_name":"SymJAX/SymJAX","owner":"SymJAX","description":"Documentation:","archived":false,"fork":false,"pushed_at":"2023-05-22T22:41:16.000Z","size":28581,"stargazers_count":120,"open_issues_count":3,"forks_count":5,"subscribers_count":9,"default_branch":"master","last_synced_at":"2024-10-30T21:36:49.499Z","etag":null,"topics":["dataset","deep-learning","deep-neural-networks","jax","lasagne","numpy","tensorflow","theano"],"latest_commit_sha":null,"homepage":"https://symjax.readthedocs.io/en/master/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/SymJAX.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2019-09-04T14:23:45.000Z","updated_at":"2024-10-16T09:51:15.000Z","dependencies_parsed_at":"2024-01-07T10:51:08.707Z","dependency_job_id":"0c550714-cc40-4b05-8e1b-0a17a537aaac","html_url":"https://github.com/SymJAX/SymJAX","commit_stats":{"total_commits":471,"total_committers":8,"mean_commits":58.875,"dds":0.08917197452229297,"last_synced_commit":"d8778c2eb3254b478cef4f45d934bf921e695619"},"previous_names":[],"tags_count":6,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SymJAX%2FSymJAX","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SymJAX%2FSymJAX/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SymJAX%2FSymJAX/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SymJAX%2FSymJAX/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SymJAX","download_url":"https://codeload.github.com/SymJAX/SymJAX/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224282190,"owners_count":17285786,"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":["dataset","deep-learning","deep-neural-networks","jax","lasagne","numpy","tensorflow","theano"],"created_at":"2024-08-02T15:01:39.069Z","updated_at":"2024-11-12T13:31:07.962Z","avatar_url":"https://github.com/SymJAX.png","language":"Python","funding_links":[],"categories":["Python","Libraries"],"sub_categories":["New Libraries","Inactive Libraries"],"readme":"\n![SymJAX logo](./docs/img/symjax_logo.png)\n\n\n# SymJAX: symbolic CPU/GPU/TPU programming ![Continuous integration](https://github.com/SymJAX/SymJAX/workflows/Continuous%20integration/badge.svg) ![doctest](https://github.com/SymJAX/SymJAX/workflows/doc/badge.svg) ![license](https://img.shields.io/badge/license-Apache%202-blue) \u003ca href=\"https://github.com/psf/black\"\u003e\u003cimg alt=\"Code style: black\" src=\"https://img.shields.io/badge/code%20style-black-000000.svg\"\u003e\u003c/a\u003e\nThis is an under-development research project, not an official product, expect bugs and sharp edges; please help by trying it out, reporting bugs.\n[**Reference docs**](https://symjax.readthedocs.io/en/latest/)\n\n\n## What is SymJAX ?\n\nSymJAX is a symbolic programming version of JAX simplifying graph input/output/updates and providing additional functionalities for general machine learning and deep learning applications. From an user perspective SymJAX apparents to Theano with fast graph optimization/compilation and broad hardware support, along with Lasagne-like deep learning functionalities\n\n## Why SymJAX ?\n\nThe number of libraries topping Jax/Tensorflow/Torch is large and growing by the\nday. What SymJAX offers as opposed to most is an all-in-one library with diverse\nfunctionalities such as\n\n- dozens of various datasets with clear descriptions and one line import\n- versatile set of functions from ffts, linear algebraic tools, random variables, ...\n- advanced signal processing tools such as multiple wavelet families (in time and frequency domain), multiple time-frequency representations, apodization windows, ...\n- IO utilities to monitor/save/track specific statistics during graph execution through h5 files and numpy, simple and explicit graph saving allowing to save and load models without burden\n- side utilities such as automatic batching of dataset, data splitting, cross-validation, ...\n\nand most importantly, a SYMBOLIC/DECLARATIVE programming environment allowing CONCISE/EXPLICIT/OPTIMIZED computations.\n\nFor a deep network oriented imperative library built on JAX and with a JAX syntax check out [FLAX](https://github.com/google/flax).\n\n## Examples\n\n```python\nimport sys\nimport symjax as sj\nimport symjax.tensor as T\n\n# create our variable to be optimized\nmu = T.Variable(T.random.normal((), seed=1))\n\n# create our cost\ncost = T.exp(-(mu-1)**2)\n\n# get the gradient, notice that it is itself a tensor that can then\n# be manipulated as well\ng = sj.gradients(cost, mu)\nprint(g)\n\n# (Tensor: shape=(), dtype=float32)\n\n# create the compiled function that will compute the cost and apply\n# the update onto the variable\nf = sj.function(outputs=cost, updates={mu:mu-0.2*g})\n\nfor i in range(10):\n    print(f())\n\n# 0.008471076\n# 0.008201109\n# 0.007946267\n# ...\n```\n\n## Installation\n\nMake sure to install all the needed GPU drivers (for GPU support, not mandatory) and install JAX as described in this [**guide**](https://symjax.readthedocs.io/en/latest/user/installation.html).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSymJAX%2FSymJAX","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FSymJAX%2FSymJAX","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSymJAX%2FSymJAX/lists"}