Good work builds on good work.
TensorReps brings together original exercises and recovered community collections. Each problem links to its source where available. The source notices below are preserved as collected; license terms and recovery coverage differ by collection.
TorchLeet
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MIT License Copyright (c) 2024-2026 Chandrahas Aroori and TorchLeet contributors Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
HappyTorch
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MIT License Copyright (c) 2026 Jin Li Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
TorchCode
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No LICENSE file was present in this snapshot. The README MIT badge and pyproject.toml license="MIT" declare MIT licensing. Attribution: duoan/TorchCode. Preserve that declaration and consult the repository for any later clarification.
DML-OpenProblem
Open-Deep-ML/DML-OpenProblem ↗
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Educational Use Only License Version 1.0, July 2024 TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 8 of this document. "Licensor" shall mean the individual or entity offering the License. "Licensee" shall mean the individual or entity exercising permissions granted by this License. "Work" shall mean the questions, problems, software, or material licensed under these terms. 2. Grant of License. Subject to the terms and conditions of this License, the Licensor hereby grants the Licensee a worldwide, royalty-free, non-exclusive, non-transferable license to use, reproduce, and distribute the Work for educational purposes only. 3. Commercial Use. a. The Licensee shall not use the Work for any commercial purposes. Commercial purposes include, but are not limited to, selling, leasing, or using the Work in a commercial product or service. b. The Licensor retains the exclusive right to use the Work for commercial purposes. 4. Restrictions. a. The Licensee may not sublicense, transfer, or distribute the Work except as expressly permitted under this License. b. The Licensee may not use the Work as part of any commercial service or product, including but not limited to online platforms like LeetCode, without the explicit permission of the Licensor. 5. Prohibition of Use in Machine Learning Models. The Licensee shall not use the Work as training data for large language models (LLMs) or any other machine learning models. This includes but is not limited to using the Work to improve, enhance, or develop machine learning algorithms. 6. Disclaimer of Warranty. The Work is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, and noninfringement. In no event shall the Licensor be liable for any claim, damages, or other liability, whether in an action of contract, tort, or otherwise, arising from, out of, or in connection with the Work or the use or other dealings in the Work. 7. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Licensor be liable to Licensee for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Licensor has been advised of the possibility of such damages. 8. Acceptance. By using, reproducing, or distributing the Work, the Licensee accepts the terms and conditions of this License. Any violation of the terms of this License will automatically terminate the Licensee's rights under this License.
Tensor Puzzles
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MIT License Copyright (c) 2022 Sasha Rush Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
What verification means
A verified badge means the reference implementation passed the available tests in the local CPU audit. It does not guarantee exhaustive test coverage or GPU compatibility. Unverified source checks and self-review exercises are labeled separately.
Recovered collections
The TensorGym collection contains 30 archived descriptions, including 20 exercises with recovered code and tests. The LeetGPU collection retains its source links and GPU-specific requirements. An available description or source test is not a claim that an exercise has been independently verified.
The tools behind the workspace
Built with Next.js, React, CodeMirror, PyTorch, NumPy, Neon, Vercel, and E2B. These projects and their contributors make this kind of learning possible.
TensorReps is an independent product and is not affiliated with OpenAI, LeetCode, Google, PyTorch, or the maintainers of the source exercise collections.