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107
.github/contributors/kwhumphreys.md
vendored
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107
.github/contributors/kwhumphreys.md
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@ -0,0 +1,107 @@
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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
|
||||
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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||||
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||||
If you agree to be bound by these terms, fill in the information requested
|
||||
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
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
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
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [ ] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect my
|
||||
contributions.
|
||||
|
||||
* [x] I am signing on behalf of my employer or a legal entity and I have the
|
||||
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 | Kevin Humphreys |
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| Company name (if applicable) | Textio Inc. |
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| Title or role (if applicable) | |
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| Date | 01-03-2018 |
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| GitHub username | kwhumphreys |
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| Website (optional) | |
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@ -150,7 +150,7 @@ recipes, that does provide some argument for bringing it "in house".
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### Getting started
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To make changes to spaCy's code base, you need to clone the GitHub repository
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To make changes to spaCy's code base, you need to fork then clone the GitHub repository
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and build spaCy from source. You'll need to make sure that you have a
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development environment consisting of a Python distribution including header
|
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files, a compiler, [pip](https://pip.pypa.io/en/latest/installing/),
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|
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|
@ -45,20 +45,25 @@ This is a list of everyone who has made significant contributions to spaCy, in a
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* Maxim Samsonov, [@maxirmx](https://github.com/maxirmx)
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* Michael Wallin, [@wallinm1](https://github.com/wallinm1)
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* Miguel Almeida, [@mamoit](https://github.com/mamoit)
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* Motoki Wu, [@tokestermw](https://github.com/tokestermw)
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* Oleg Zd, [@olegzd](https://github.com/olegzd)
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* Orhan Bilgin, [@melanuria](https://github.com/melanuria)
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* Orion Montoya, [@mdcclv](https://github.com/mdcclv)
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* Paul O'Leary McCann, [@polm](https://github.com/polm)
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* Pokey Rule, [@pokey](https://github.com/pokey)
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* Ramanan Balakrishnan, [@ramananbalakrishnan](https://github.com/ramananbalakrishnan)
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* Raphaël Bournhonesque, [@raphael0202](https://github.com/raphael0202)
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* Rob van Nieuwpoort, [@RvanNieuwpoort](https://github.com/RvanNieuwpoort)
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* Roman Domrachev, [@ligser](https://github.com/ligser)
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* Roman Inflianskas, [@rominf](https://github.com/rominf)
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* Sam Bozek, [@sambozek](https://github.com/sambozek)
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* Sasho Savkov, [@savkov](https://github.com/savkov)
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* Shuvanon Razik, [@shuvanon](https://github.com/shuvanon)
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* Søren Lind Kristiansen, [@sorenlind](https://github.com/sorenlind)
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* Swier, [@swierh](https://github.com/swierh)
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* Thomas Tanon, [@Tpt](https://github.com/Tpt)
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* Tiago Rodrigues, [@TiagoMRodrigues](https://github.com/TiagoMRodrigues)
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* Vadim Mazaev, [@GreenRiverRUS](https://github.com/GreenRiverRUS)
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* Vimos Tan, [@Vimos](https://github.com/Vimos)
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* Vsevolod Solovyov, [@vsolovyov](https://github.com/vsolovyov)
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* Wah Loon Keng, [@kengz](https://github.com/kengz)
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|
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|
@ -25,4 +25,4 @@ def blank(name, **kwargs):
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def info(model=None, markdown=False):
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return cli_info(None, model, markdown)
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return cli_info(model, markdown)
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|
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@ -28,7 +28,7 @@ if __name__ == '__main__':
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command = sys.argv.pop(1)
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sys.argv[0] = 'spacy %s' % command
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if command in commands:
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plac.call(commands[command])
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plac.call(commands[command], sys.argv[1:])
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else:
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prints(
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"Available: %s" % ', '.join(commands),
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|
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@ -24,8 +24,7 @@ CONVERTERS = {
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n_sents=("Number of sentences per doc", "option", "n", int),
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converter=("Name of converter (auto, iob, conllu or ner)", "option", "c", str),
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morphology=("Enable appending morphology to tags", "flag", "m", bool))
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def convert(cmd, input_file, output_dir, n_sents=1, morphology=False,
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converter='auto'):
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def convert(input_file, output_dir, n_sents=1, morphology=False, converter='auto'):
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"""
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Convert files into JSON format for use with train command and other
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experiment management functions.
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|
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@ -16,7 +16,7 @@ from .. import about
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model=("model to download, shortcut or name)", "positional", None, str),
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direct=("force direct download. Needs model name with version and won't "
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"perform compatibility check", "flag", "d", bool))
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def download(cmd, model, direct=False):
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def download(model, direct=False):
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"""
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Download compatible model from default download path using pip. Model
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can be shortcut, model name or, if --direct flag is set, full model name
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|
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@ -25,8 +25,8 @@ numpy.random.seed(0)
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displacy_path=("directory to output rendered parses as HTML", "option",
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"dp", str),
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displacy_limit=("limit of parses to render as HTML", "option", "dl", int))
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def evaluate(cmd, model, data_path, gpu_id=-1, gold_preproc=False,
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displacy_path=None, displacy_limit=25):
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def evaluate(model, data_path, gpu_id=-1, gold_preproc=False, displacy_path=None,
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displacy_limit=25):
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"""
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Evaluate a model. To render a sample of parses in a HTML file, set an
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output directory as the displacy_path argument.
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|
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@ -13,7 +13,7 @@ from .. import util
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@plac.annotations(
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model=("optional: shortcut link of model", "positional", None, str),
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markdown=("generate Markdown for GitHub issues", "flag", "md", str))
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def info(cmd, model=None, markdown=False):
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def info(model=None, markdown=False):
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"""Print info about spaCy installation. If a model shortcut link is
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speficied as an argument, print model information. Flag --markdown
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prints details in Markdown for easy copy-pasting to GitHub issues.
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|
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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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"option", "V", int)
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)
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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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def init_model(lang, output_dir, freqs_loc, clusters_loc=None, vectors_loc=None, prune_vectors=-1):
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"""
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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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|
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@ -13,7 +13,7 @@ from .. import util
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origin=("package name or local path to model", "positional", None, str),
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link_name=("name of shortuct link to create", "positional", None, str),
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force=("force overwriting of existing link", "flag", "f", bool))
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def link(cmd, origin, link_name, force=False, model_path=None):
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def link(origin, link_name, force=False, model_path=None):
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"""
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Create a symlink for models within the spacy/data directory. Accepts
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either the name of a pip package, or the local path to the model data
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|
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|
@ -20,7 +20,7 @@ from .. import about
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"the command line prompt", "flag", "c", bool),
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force=("force overwriting of existing model directory in output directory",
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"flag", "f", bool))
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def package(cmd, input_dir, output_dir, meta_path=None, create_meta=False,
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def package(input_dir, output_dir, meta_path=None, create_meta=False,
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force=False):
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"""
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Generate Python package for model data, including meta and required
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|
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@ -29,7 +29,7 @@ def read_inputs(loc):
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@plac.annotations(
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lang=("model/language", "positional", None, str),
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inputs=("Location of input file", "positional", None, read_inputs))
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def profile(cmd, lang, inputs=None):
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def profile(lang, inputs=None):
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"""
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Profile a spaCy pipeline, to find out which functions take the most time.
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"""
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|
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@ -38,7 +38,7 @@ numpy.random.seed(0)
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version=("Model version", "option", "V", str),
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meta_path=("Optional path to meta.json. All relevant properties will be "
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"overwritten.", "option", "m", Path))
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def train(cmd, lang, output_dir, train_data, dev_data, n_iter=30, n_sents=0,
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def train(lang, output_dir, train_data, dev_data, n_iter=30, n_sents=0,
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use_gpu=-1, vectors=None, no_tagger=False,
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no_parser=False, no_entities=False, gold_preproc=False,
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version="0.0.0", meta_path=None):
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|
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@ -11,7 +11,7 @@ from ..util import prints, get_data_path, read_json
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from .. import about
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def validate(cmd):
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def validate():
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"""Validate that the currently installed version of spaCy is compatible
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with the installed models. Should be run after `pip install -U spacy`.
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"""
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|
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@ -21,8 +21,7 @@ from ..util import prints, ensure_path
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prune_vectors=("optional: number of vectors to prune to.",
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"option", "V", int)
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)
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def make_vocab(cmd, lang, output_dir, lexemes_loc,
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vectors_loc=None, prune_vectors=-1):
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def make_vocab(lang, output_dir, lexemes_loc, vectors_loc=None, prune_vectors=-1):
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"""Compile a vocabulary from a lexicon jsonl file and word vectors."""
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if not lexemes_loc.exists():
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prints(lexemes_loc, title="Can't find lexical data", exits=1)
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|
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@ -213,7 +213,8 @@ for verb_data in [
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{ORTH: "could", NORM: "could", TAG: "MD"},
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{ORTH: "might", NORM: "might", TAG: "MD"},
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{ORTH: "must", NORM: "must", TAG: "MD"},
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{ORTH: "should", NORM: "should", TAG: "MD"}]:
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{ORTH: "should", NORM: "should", TAG: "MD"},
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{ORTH: "would", NORM: "would", TAG: "MD"}]:
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verb_data_tc = dict(verb_data)
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verb_data_tc[ORTH] = verb_data_tc[ORTH].title()
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for data in [verb_data, verb_data_tc]:
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|
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@ -9,7 +9,6 @@ from ...cli.train import train
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@pytest.mark.xfail
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def test_cli_trained_model_can_be_saved(tmpdir):
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cmd = None
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lang = 'nl'
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output_dir = str(tmpdir)
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train_file = NamedTemporaryFile('wb', dir=output_dir, delete=False)
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@ -86,6 +85,6 @@ def test_cli_trained_model_can_be_saved(tmpdir):
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# spacy train -n 1 -g -1 nl output_nl training_corpus.json training \
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# corpus.json
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train(cmd, lang, output_dir, train_data, dev_data, n_iter=1)
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train(lang, output_dir, train_data, dev_data, n_iter=1)
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assert True
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|
|
13
spacy/tests/regression/test_issue1758.py
Normal file
13
spacy/tests/regression/test_issue1758.py
Normal file
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@ -0,0 +1,13 @@
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|||
# coding: utf-8
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from __future__ import unicode_literals
|
||||
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||||
import pytest
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||||
|
||||
|
||||
@pytest.mark.parametrize('text', ["would've"])
|
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def test_issue1758(en_tokenizer, text):
|
||||
"""Test that "would've" is handled by the English tokenizer exceptions."""
|
||||
tokens = en_tokenizer(text)
|
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assert len(tokens) == 2
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assert tokens[0].tag_ == "MD"
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||||
assert tokens[1].lemma_ == "have"
|
|
@ -51,7 +51,9 @@ p
|
|||
p
|
||||
| Import and load a #[code Language] class. Allows lazy-loading
|
||||
| #[+a("/usage/adding-languages") language data] and importing
|
||||
| languages using the two-letter language code.
|
||||
| languages using the two-letter language code. To add a language code
|
||||
| for a custom language class, you can use the
|
||||
| #[+api("top-level#util.set_lang_class") #[code set_lang_class]] helper.
|
||||
|
||||
+aside-code("Example").
|
||||
for lang_id in ['en', 'de']:
|
||||
|
@ -70,6 +72,33 @@ p
|
|||
+cell #[code Language]
|
||||
+cell Language class.
|
||||
|
||||
+h(3, "util.set_lang_class") util.set_lang_class
|
||||
+tag function
|
||||
|
||||
p
|
||||
| Set a custom #[code Language] class name that can be loaded via
|
||||
| #[+api("top-level#util.get_lang_class") #[code get_lang_class]]. If
|
||||
| your model uses a custom language, this is required so that spaCy can
|
||||
| load the correct class from the two-letter language code.
|
||||
|
||||
+aside-code("Example").
|
||||
from spacy.lang.xy import CustomLanguage
|
||||
|
||||
util.set_lang_class('xy', CustomLanguage)
|
||||
lang_class = util.get_lang_class('xy')
|
||||
nlp = lang_class()
|
||||
|
||||
+table(["Name", "Type", "Description"])
|
||||
+row
|
||||
+cell #[code name]
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||||
+cell unicode
|
||||
+cell Two-letter language code, e.g. #[code 'en'].
|
||||
|
||||
+row
|
||||
+cell #[code cls]
|
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+cell #[code Language]
|
||||
+cell The language class, e.g. #[code English].
|
||||
|
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+h(3, "util.load_model") util.load_model
|
||||
+tag function
|
||||
+tag-new(2)
|
||||
|
|
|
@ -136,7 +136,7 @@ p
|
|||
+aside-code("Example").
|
||||
from spacy.gold import biluo_tags_from_offsets
|
||||
|
||||
doc = nlp('I like London.')
|
||||
doc = nlp(u'I like London.')
|
||||
entities = [(7, 13, 'LOC')]
|
||||
tags = biluo_tags_from_offsets(doc, entities)
|
||||
assert tags == ['O', 'O', 'U-LOC', 'O']
|
||||
|
|
Loading…
Reference in New Issue
Block a user