mirror of https://github.com/explosion/spaCy.git
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# spaCy contributor agreement
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This spaCy Contributor Agreement (**"SCA"**) is based on the
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[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
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The SCA applies to any contribution that you make to any product or project
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managed by us (the **"project"**), and sets out the intellectual property rights
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you grant to us in the contributed materials. The term **"us"** shall mean
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[ExplosionAI UG (haftungsbeschränkt)](https://explosion.ai/legal). The term
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**"you"** shall mean the person or entity identified below.
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If you agree to be bound by these terms, fill in the information requested
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below and include the filled-in version with your first pull request, under the
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folder [`.github/contributors/`](/.github/contributors/). The name of the file
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should be your GitHub username, with the extension `.md`. For example, the user
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example_user would create the file `.github/contributors/example_user.md`.
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Read this agreement carefully before signing. These terms and conditions
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constitute a binding legal agreement.
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## Contributor Agreement
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1. The term "contribution" or "contributed materials" means any source code,
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object code, patch, tool, sample, graphic, specification, manual,
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documentation, or any other material posted or submitted by you to the project.
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2. With respect to any worldwide copyrights, or copyright applications and
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registrations, in your contribution:
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* you hereby assign to us joint ownership, and to the extent that such
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assignment is or becomes invalid, ineffective or unenforceable, you hereby
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grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
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royalty-free, unrestricted license to exercise all rights under those
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copyrights. This includes, at our option, the right to sublicense these same
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rights to third parties through multiple levels of sublicensees or other
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licensing arrangements;
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* you agree that each of us can do all things in relation to your
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contribution as if each of us were the sole owners, and if one of us makes
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a derivative work of your contribution, the one who makes the derivative
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work (or has it made will be the sole owner of that derivative work;
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* you agree that you will not assert any moral rights in your contribution
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against us, our licensees or transferees;
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* you agree that we may register a copyright in your contribution and
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exercise all ownership rights associated with it; and
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* you agree that neither of us has any duty to consult with, obtain the
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consent of, pay or render an accounting to the other for any use or
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distribution of your contribution.
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3. With respect to any patents you own, or that you can license without payment
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to any third party, you hereby grant to us a perpetual, irrevocable,
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non-exclusive, worldwide, no-charge, royalty-free license to:
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* make, have made, use, sell, offer to sell, import, and otherwise transfer
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your contribution in whole or in part, alone or in combination with or
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included in any product, work or materials arising out of the project to
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which your contribution was submitted, and
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* at our option, to sublicense these same rights to third parties through
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multiple levels of sublicensees or other licensing arrangements.
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4. Except as set out above, you keep all right, title, and interest in your
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contribution. The rights that you grant to us under these terms are effective
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on the date you first submitted a contribution to us, even if your submission
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took place before the date you sign these terms.
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5. You covenant, represent, warrant and agree that:
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* Each contribution that you submit is and shall be an original work of
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authorship and you can legally grant the rights set out in this SCA;
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* to the best of your knowledge, each contribution will not violate any
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third party's copyrights, trademarks, patents, or other intellectual
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property rights; and
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* each contribution shall be in compliance with U.S. export control laws and
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other applicable export and import laws. You agree to notify us if you
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become aware of any circumstance which would make any of the foregoing
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representations inaccurate in any respect. We may publicly disclose your
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participation in the project, including the fact that you have signed the SCA.
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6. This SCA is governed by the laws of the State of California and applicable
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U.S. Federal law. Any choice of law rules will not apply.
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7. Please place an “x” on one of the applicable statement below. Please do NOT
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mark both statements:
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* [x] I am signing on behalf of myself as an individual and no other person
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or entity, including my employer, has or will have rights with respect to my
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contributions.
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* [ ] I am signing on behalf of my employer or a legal entity and I have the
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actual authority to contractually bind that entity.
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## Contributor Details
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| Field | Entry |
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|------------------------------- | -------------------- |
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| Name | QingHeng Zhang |
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| Company name (if applicable) | |
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| Title or role (if applicable) | |
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| Date | 2017-12-28 |
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| GitHub username | zqhZY |
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| Website (optional) | https://someth.duapp.com/ |
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@ -99,5 +99,5 @@ you how run-time usage will eventually look.
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## Getting updates
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## Getting updates
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We should have the blog post explaining the model ready before the end of the week. To get
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We should have the blog post explaining the model ready before the end of the week. To get
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notified when it's published, you can either the follow me on [Twitter](https://twitter.com/honnibal),
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notified when it's published, you can either follow me on [Twitter](https://twitter.com/honnibal)
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or subscribe to our [mailing list](http://eepurl.com/ckUpQ5).
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or subscribe to our [mailing list](http://eepurl.com/ckUpQ5).
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@ -25,7 +25,7 @@ from ..util import prints, ensure_path, get_lang_class
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prune_vectors=("optional: number of vectors to prune to",
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prune_vectors=("optional: number of vectors to prune to",
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"option", "V", int)
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"option", "V", int)
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)
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)
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def init_model(lang, output_dir, freqs_loc, clusters_loc=None, vectors_loc=None, prune_vectors=-1):
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def init_model(_cmd, lang, output_dir, freqs_loc, clusters_loc=None, vectors_loc=None, prune_vectors=-1):
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"""
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"""
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Create a new model from raw data, like word frequencies, Brown clusters
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Create a new model from raw data, like word frequencies, Brown clusters
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and word vectors.
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and word vectors.
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@ -36,7 +36,7 @@ def init_model(lang, output_dir, freqs_loc, clusters_loc=None, vectors_loc=None,
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vectors_loc = ensure_path(vectors_loc)
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vectors_loc = ensure_path(vectors_loc)
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probs, oov_prob = read_freqs(freqs_loc)
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probs, oov_prob = read_freqs(freqs_loc)
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vectors_data, vector_keys = read_vectors(vectors_loc) if vectors_loc else None
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vectors_data, vector_keys = read_vectors(vectors_loc) if vectors_loc else None, None
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clusters = read_clusters(clusters_loc) if clusters_loc else {}
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clusters = read_clusters(clusters_loc) if clusters_loc else {}
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nlp = create_model(lang, probs, oov_prob, clusters, vectors_data, vector_keys, prune_vectors)
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nlp = create_model(lang, probs, oov_prob, clusters, vectors_data, vector_keys, prune_vectors)
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@ -69,7 +69,7 @@ def create_model(lang, probs, oov_prob, clusters, vectors_data, vector_keys, pru
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lex_added += 1
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lex_added += 1
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nlp.vocab.cfg.update({'oov_prob': oov_prob})
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nlp.vocab.cfg.update({'oov_prob': oov_prob})
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if len(vectors_data):
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if vectors_data:
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nlp.vocab.vectors = Vectors(data=vectors_data, keys=vector_keys)
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nlp.vocab.vectors = Vectors(data=vectors_data, keys=vector_keys)
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if prune_vectors >= 1:
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if prune_vectors >= 1:
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nlp.vocab.prune_vectors(prune_vectors)
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nlp.vocab.prune_vectors(prune_vectors)
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@ -1,12 +1,19 @@
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# coding: utf8
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# coding: utf8
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from __future__ import unicode_literals
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from __future__ import unicode_literals
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from ...attrs import LANG
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from ...language import Language
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from ...language import Language
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from ...tokens import Doc
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from ...tokens import Doc
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class ChineseDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters[LANG] = lambda text: 'zh' # for pickling
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class Chinese(Language):
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class Chinese(Language):
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lang = 'zh'
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lang = 'zh'
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Defaults = ChineseDefaults # override defaults
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def make_doc(self, text):
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def make_doc(self, text):
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try:
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try:
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