{
    "info": {
        "author": "Taku Kudo",
        "author_email": "taku@google.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: Text Processing :: Linguistic"
        ],
        "description": "# SentencePiece Python Wrapper\n\nPython wrapper for SentencePiece with SWIG. This module wraps sentencepiece::SentencePieceProcessor class with the following modifications:\n* Encode and Decode methods are re-defined as EncodeAsIds, EncodeAsPieces, DecodeIds and DecodePieces respectively.\n* Support model training with SentencePieceTrainer.Train method.\n* SentencePieceText proto is not supported.\n* Added __len__ and __getitem__ methods. len(obj) and obj[key] returns vocab size and vocab id respectively.\n\n## Build and Install SentencePiece\nFor Linux (x64/i686), macOS, and Windows(win32/x64) environment, you can simply use pip command to install SentencePiece python module.\n\n```\n% pip install sentencepiece\n```\n\nTo build and install the Python wrapper from source, please install [SentencePiece C++](https://github.com/google/sentencepiece#c-from-source) and try the following commands:\n```\n% python setup.py build\n% sudo python setup.py install\n```\n\nIf you don\u2019t have write permission to the global site-packages directory or don\u2019t want to install into it, please try:\n```\n% python setup.py install --user\n```\n\n## Usage\n\nSee [this google colab page](https://github.com/google/sentencepiece/blob/master/python/sentencepiece_python_module_example.ipynb) to run sentencepiece interactively.\n\n### Segmentation\n```\n% python\n>>> import sentencepiece as spm\n>>> sp = spm.SentencePieceProcessor()\n>>> sp.Load(\"test/test_model.model\")\nTrue\n>>> sp.EncodeAsPieces(\"This is a test\")\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'est']\n>>> sp.EncodeAsIds(\"This is a test\")\n[284, 47, 11, 4, 15, 400]\n>>> sp.DecodePieces(['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'est'])\n'This is a test'\n>>> sp.NBestEncodeAsPieces(\"This is a test\", 5)\n[['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'est'], ['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 'te', 'st'], ['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 'te', 's', 't'], ['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'e', 'st'], ['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'es', 't']]\n>>> for x in range(10):\n...     sp.SampleEncodeAsPieces(\"This is a test\", -1, 0.1)\n...\n['\\xe2\\x96\\x81', 'T', 'h', 'i', 's', '\\xe2\\x96\\x81', 'is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'e', 's', 't']\n['\\xe2\\x96\\x81T', 'h', 'is', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81', 'a', '\\xe2\\x96\\x81', 't', 'est']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81', 'a', '\\xe2\\x96\\x81', 't', 'e', 'st']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'e', 'st']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'e', 's', 't']\n['\\xe2\\x96\\x81T', 'h', 'is', '\\xe2\\x96\\x81', 'i', 's', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 'te', 's', 't']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81', 'is', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 'te', 's', 't']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81', 'i', 's', '\\xe2\\x96\\x81a', '\\xe2\\x96\\x81', 't', 'e', 'st']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81', 'is', '\\xe2\\x96\\x81', 'a', '\\xe2\\x96\\x81', 't', 'e', 'st']\n['\\xe2\\x96\\x81This', '\\xe2\\x96\\x81', 'i', 's', '\\xe2\\x96\\x81', 'a', '\\xe2\\x96\\x81', 'te', 's', 't']\n>>> sp.DecodeIds([284, 47, 11, 4, 15, 400])\n'This is a test'\n>>> sp.GetPieceSize()\n1000\n>>> sp.IdToPiece(2)\n'</s>'\n>>> sp.PieceToId('</s>')\n2\n>>> len(sp)\n1000\n>>> sp['</s>']\n2\n```\n\n### Model Training\nTraining is performed by passing parameters of [spm_train](https://github.com/google/sentencepiece#train-sentencepiece-model) to  SentencePieceTrainer.Train() function.\n\n```\n>>> import sentencepiece as spm\n>>> spm.SentencePieceTrainer.Train('--input=test/botchan.txt --model_prefix=m --vocab_size=1000')\nunigram_model_trainer.cc(494) LOG(INFO) Starts training with : \ninput: \"test/botchan.txt\"\nmodel_prefix: \"m\"\nmodel_type: UNIGRAM\n..snip..\nunigram_model_trainer.cc(529) LOG(INFO) EM sub_iter=0 size=1239 obj=10.4055 num_tokens=36256 num_tokens/piece=29.2623\nunigram_model_trainer.cc(529) LOG(INFO) EM sub_iter=1 size=1239 obj=10.3187 num_tokens=36256 num_tokens/piece=29.2623\nunigram_model_trainer.cc(529) LOG(INFO) EM sub_iter=0 size=1100 obj=10.5285 num_tokens=37633 num_tokens/piece=34.2118\nunigram_model_trainer.cc(529) LOG(INFO) EM sub_iter=1 size=1100 obj=10.4973 num_tokens=37630 num_tokens/piece=34.2091\ntrainer_interface.cc(284) LOG(INFO) Saving model: m.model\ntrainer_interface.cc(293) LOG(INFO) Saving vocabs: m.vocab\n>>>\n```\n\n## Python2/3 String/Unicode compatibility\nSentencepiece python wrapper accepts both Unicode string and legacy byte string.\nThe output string type is determined by the input string type.\nThe output type of IdToPiece/DecodeIds methods is *str*, but note that it is a legacy byte string in Python2 and Unicode string in Python3 respectively.\n\n* Python2:\n```\n>>> sp.EncodeAsPieces('\u543e\u8f29\u306f\u732b\u3067\u3042\u308b')\n['\\xe2\\x96\\x81', '\\xe5\\x90\\xbe', '\\xe8\\xbc\\xa9', '\\xe3\\x81\\xaf', '\\xe7\\x8c\\xab', '\\xe3\\x81\\xa7\\xe3\\x81\\x82\\xe3\\x82\\x8b']\n>>> sp.EncodeAsPieces(u'\u543e\u8f29\u306f\u732b\u3067\u3042\u308b')\n[u'\\u2581', u'\\u543e', u'\\u8f29', u'\\u306f', u'\\u732b', u'\\u3067\\u3042\\u308b']\n>>> sp.EncodeAsPieces(u'\u543e\u8f29\u306f\u732b\u3067\u3042\u308b'.encode('utf-8'))\n['\\xe2\\x96\\x81', '\\xe5\\x90\\xbe', '\\xe8\\xbc\\xa9', '\\xe3\\x81\\xaf', '\\xe7\\x8c\\xab', '\\xe3\\x81\\xa7\\xe3\\x81\\x82\\xe3\\x82\\x8b']\n>>> sp.IdToPiece(10)\n'\\xe3\\x81\\xab'\n>>> type(sp.IdToPiece(10))\n<type 'str'>\n```\n\n* Python3:\n```\n>>> sp.EncodeAsPieces('\u543e\u8f29\u306f\u732b\u3067\u3042\u308b')\n['\u2581', '\u543e', '\u8f29', '\u306f', '\u732b', '\u3067\u3042\u308b']\n>>> sp.EncodeAsPieces('\u543e\u8f29\u306f\u732b\u3067\u3042\u308b'.encode('utf-8'))\n[b'\\xe2\\x96\\x81', b'\\xe5\\x90\\xbe', b'\\xe8\\xbc\\xa9', b'\\xe3\\x81\\xaf', b'\\xe7\\x8c\\xab', b'\\xe3\\x81\\xa7\\xe3\\x81\\x82\\xe3\\x82\\x8b']\n>>>\n>>> sp.IdToPiece(10)\n'\u306b'\n>>> type(sp.IdToPiece(10))\n<class 'str'>\n```\n\n\n",
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