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align=\"center\"\u003e\n\n# TorchRua\n\n![GitHub Workflow Status (with event)](https://img.shields.io/github/actions/workflow/status/speedcell4/torchrua/unit-tests.yml?cacheSeconds=0)\n![PyPI - Version](https://img.shields.io/pypi/v/torchrua?label=pypi%20version\u0026cacheSeconds=0)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/torchrua?cacheSeconds=0)\n\n\u003c/div\u003e\n\n**Rua** derives from the [Szechwanese](https://en.wikipedia.org/wiki/Sichuanese_dialects) character \u003cruby\u003e挼\u003crt\u003e\nruá\u003c/rt\u003e\u003c/ruby\u003e which means \"pack, rumple, screw up, manipulate\". TorchRua provides tons of easy-to-use functions to\nhelp you rua tensors with `PackedSequence`, `CattedSequence`, and `PaddedSequence`!\n\n## Installation\n\n`python -m pip torchrua`","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspeedcell4%2Ftorchrua","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fspeedcell4%2Ftorchrua","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fspeedcell4%2Ftorchrua/lists"}