{"data":{"slug":"mindspore-ai-mindspore","name":"mindspore","tagline":"MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.","github_url":"https://github.com/mindspore-ai/mindspore","owner":"mindspore-ai","repo":"mindspore","owner_avatar_url":"https://avatars.githubusercontent.com/u/54143604?v=4","primary_language":"C++","stars":4694,"forks":752,"topics":[],"archived":false,"github_pushed_at":"2024-07-29T01:48:05+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/mindspore-ai-mindspore","markdown_url":"https://www.graphcanon.com/tools/mindspore-ai-mindspore.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/mindspore-ai-mindspore","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=mindspore-ai-mindspore","description":"MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.","homepage_url":"https://gitee.com/mindspore/mindspore","license":"Apache-2.0","open_issues":225,"watchers":148,"ai_summary":null,"readme_excerpt":"### Pip mode method installation\n\nMindSpore offers build options across multiple backends:\n\n| Hardware Platform | Operating System | Status |\n| :---------------- | :--------------- | :----- |\n| Ascend910 | Ubuntu-x86 | ✔️ |\n|  | Ubuntu-aarch64 | ✔️ |\n|  | EulerOS-aarch64 | ✔️ |\n|  | CentOS-x86 | ✔️ |\n|  | CentOS-aarch64 | ✔️ |\n| GPU CUDA 10.1 | Ubuntu-x86 | ✔️ |\n| CPU | Ubuntu-x86 | ✔️ |\n|  | Ubuntu-aarch64 | ✔️ |\n|  | Windows-x86 | ✔️ |\n\nFor installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an example:\n\n1. Download whl from [MindSpore download page](https://www.mindspore.cn/versions/en), and install the package.\n\n    ```bash\n    pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.2.0-rc1/MindSpore/cpu/ubuntu_x86/mindspore-1.2.0rc1-cp37-cp37m-linux_x86_64.whl\n    ```\n\n2. Run the following command to verify the install.\n\n    ```python\n    import numpy as np\n    import mindspore.context as context\n    import mindspore.nn as nn\n    from mindspore import Tensor\n    from mindspore.ops import operations as P\n\n    context.set_context(mode=context.GRAPH_MODE, device_target=\"CPU\")\n\n    class Mul(nn.Cell):\n        def __init__(self):\n            super(Mul, self).__init__()\n            self.mul = P.Mul()\n\n        def construct(self, x, y):\n            return self.mul(x, y)\n\n    x = Tensor(np.array([1.0, 2.0, 3.0]).astype(np.float32))\n    y = Tensor(np.array([4.0, 5.0, 6.0]).astype(np.float32))\n\n    mul = Mul()\n    print(mul(x, y))\n    ```\n\n    ```text\n    [ 4. 10. 18.]\n    ```\n\nUse pip mode method to install MindSpore in different environments. Refer to the following documents.\n\n- [Using pip mode method to install MindSpore in Ascend environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_pip_en.md)\n- [Using pip mode method to install MindSpore in GPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_pip_en.md)\n- [Using pip mode method to install MindSpore in CPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_pip_en.md)\n\n---\n\n### Source code compilation installation\n\nUse the source code compilation method to install MindSpore in different environments. Refer to the following documents.\n\n- [Using the source code compilation method to install MindSpore in Ascend environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_source_en.md)\n- [Using the source code compilation method to install MindSpore in GPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_source_en.md)\n- [Using the source code compilation method to install MindSpore in CPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_source_en.md)\n\n---\n\n### Docker Image\n\nMindSpore docker image is hosted on [Docker Hub](https://hub.docker.com/r/mindspore),\ncurrently the containerized build options are supported as follows:\n\n| Hardware Platform | Docker Image Repository | Tag | Description |\n| :---------------- | :---------------------- | :-- | :---------- |\n| CPU | `mindspore/mindspore-cpu` | `x.y.z` | Production environment with pre-installed MindSpore `x.y.z` CPU release. |\n|  |  | `devel` | Development environment provided to build MindSpore (with `CPU` backend) from the source, refer to <https://www.mindspore.cn/install/en> for installation details. |\n|  |  | `runtime` | Runtime environment provided to install MindSpore binary package with `CPU` backend. |\n| GPU | `mindspore/mindspore-gpu` | `x.y.z` | Production environment with pre-installed MindSpore `x.y.z` GPU release. |\n|  |  | `devel` | Development environment provided to build MindSpore (with `GPU CUDA10.1` backend) from the source, refer to <https://www.mindspore.cn/install/en> for installation details. |\n|  |  | `runtime` | Runtime environment provided to install MindSpore binary package with `GPU CUDA10.1` backend. |\n\n> **NOTICE:** For GPU `devel` docker image, it's NOT s","github_created_at":"2020-02-11T08:43:48+00:00","created_at":"2026-07-11T23:24:02.383266+00:00","updated_at":"2026-07-11T23:24:23.514349+00:00","categories":[{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"},{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"c","name":"c++"}],"trust":{"provenance":{"is_fork":false,"github_id":239714835,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:24:11.463Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":712,"last_release_at":null},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":103,"high_count":0,"last_scan_at":"2026-07-11T23:24:11.946Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:24:11.201Z"},"languages":{"value":["c++"],"source":"github.language","observed_at":"2026-07-11T23:24:11.201Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T23:24:11.201Z"}}}}