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37c7c85a86
* Support nowrap setting in util.prints * Tidy up and fix whitespace * Simplify script and use read_jsonl helper * Add JSON schemas (see #2928) * Deprecate Doc.print_tree Will be replaced with Doc.to_json, which will produce a unified format * Add Doc.to_json() method (see #2928) Converts Doc objects to JSON using the same unified format as the training data. Method also supports serializing selected custom attributes in the doc._. space. * Remove outdated test * Add write_json and write_jsonl helpers * WIP: Update spacy train * Tidy up spacy train * WIP: Use wasabi for formatting * Add GoldParse helpers for JSON format * WIP: add debug-data command * Fix typo * Add missing import * Update wasabi pin * Add missing import * 💫 Refactor CLI (#2943) To be merged into #2932. ## Description - [x] refactor CLI To use [`wasabi`](https://github.com/ines/wasabi) - [x] use [`black`](https://github.com/ambv/black) for auto-formatting - [x] add `flake8` config - [x] move all messy UD-related scripts to `cli.ud` - [x] make converters function that take the opened file and return the converted data (instead of having them handle the IO) ### Types of change enhancement ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * Update wasabi pin * Delete old test * Update errors * Fix typo * Tidy up and format remaining code * Fix formatting * Improve formatting of messages * Auto-format remaining code * Add tok2vec stuff to spacy.train * Fix typo * Update wasabi pin * Fix path checks for when train() is called as function * Reformat and tidy up pretrain script * Update argument annotations * Raise error if model language doesn't match lang * Document new train command
78 lines
2.5 KiB
Python
78 lines
2.5 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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import plac
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import platform
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from pathlib import Path
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from wasabi import Printer
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from ._messages import Messages
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from ..compat import path2str
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from .. import util
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from .. import about
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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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silent=("Don't print anything (just return)", "flag", "s"),
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)
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def info(model=None, markdown=False, silent=False):
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"""
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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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msg = Printer()
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if model:
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if util.is_package(model):
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model_path = util.get_package_path(model)
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else:
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model_path = util.get_data_path() / model
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meta_path = model_path / "meta.json"
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if not meta_path.is_file():
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msg.fail(Messages.M020, meta_path, exits=1)
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meta = util.read_json(meta_path)
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if model_path.resolve() != model_path:
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meta["link"] = path2str(model_path)
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meta["source"] = path2str(model_path.resolve())
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else:
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meta["source"] = path2str(model_path)
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if not silent:
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title = "Info about model '{}'".format(model)
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model_meta = {
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k: v for k, v in meta.items() if k not in ("accuracy", "speed")
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}
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if markdown:
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util.print_markdown(model_meta, title=title)
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else:
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msg.table(model_meta, title=title)
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return meta
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data = {
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"spaCy version": about.__version__,
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"Location": path2str(Path(__file__).parent.parent),
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"Platform": platform.platform(),
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"Python version": platform.python_version(),
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"Models": list_models(),
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}
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if not silent:
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title = "Info about spaCy"
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if markdown:
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util.print_markdown(data, title=title)
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else:
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msg.table(data, title=title)
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return data
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def list_models():
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def exclude_dir(dir_name):
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# exclude common cache directories and hidden directories
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exclude = ("cache", "pycache", "__pycache__")
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return dir_name in exclude or dir_name.startswith(".")
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data_path = util.get_data_path()
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if data_path:
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models = [f.parts[-1] for f in data_path.iterdir() if f.is_dir()]
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return ", ".join([m for m in models if not exclude_dir(m)])
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return "-"
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