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https://github.com/explosion/spaCy.git
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* Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
109 lines
3.6 KiB
Python
109 lines
3.6 KiB
Python
from typing import Optional, Dict, Any, Union
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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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import srsly
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from ._util import app, Arg, Opt
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from .. import util
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from .. import about
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@app.command("info")
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def info_cli(
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# fmt: off
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model: Optional[str] = Arg(None, help="Optional model name"),
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markdown: bool = Opt(False, "--markdown", "-md", help="Generate Markdown for GitHub issues"),
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silent: bool = Opt(False, "--silent", "-s", "-S", help="Don't print anything (just return)"),
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# fmt: on
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):
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"""
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Print info about spaCy installation. If a model is speficied as an argument,
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print model information. Flag --markdown prints details in Markdown for easy
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copy-pasting to GitHub issues.
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"""
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info(model, markdown=markdown, silent=silent)
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def info(
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model: Optional[str] = None, *, markdown: bool = False, silent: bool = True
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) -> Union[str, dict]:
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msg = Printer(no_print=silent, pretty=not silent)
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if model:
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title = f"Info about model '{model}'"
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data = info_model(model, silent=silent)
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else:
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title = "Info about spaCy"
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data = info_spacy()
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raw_data = {k.lower().replace(" ", "_"): v for k, v in data.items()}
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if "Models" in data and isinstance(data["Models"], dict):
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data["Models"] = ", ".join(f"{n} ({v})" for n, v in data["Models"].items())
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markdown_data = get_markdown(data, title=title)
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if markdown:
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if not silent:
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print(markdown_data)
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return markdown_data
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if not silent:
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table_data = dict(data)
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msg.table(table_data, title=title)
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return raw_data
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def info_spacy() -> Dict[str, any]:
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"""Generate info about the current spaCy intallation.
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RETURNS (dict): The spaCy info.
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"""
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all_models = {}
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for pkg_name in util.get_installed_models():
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package = pkg_name.replace("-", "_")
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all_models[package] = util.get_package_version(pkg_name)
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return {
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"spaCy version": about.__version__,
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"Location": str(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": all_models,
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}
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def info_model(model: str, *, silent: bool = True) -> Dict[str, Any]:
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"""Generate info about a specific model.
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model (str): Model name of path.
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silent (bool): Don't print anything, just return.
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RETURNS (dict): The model meta.
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"""
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msg = Printer(no_print=silent, pretty=not silent)
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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 = 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("Can't find model meta.json", meta_path, exits=1)
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meta = srsly.read_json(meta_path)
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if model_path.resolve() != model_path:
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meta["source"] = str(model_path.resolve())
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else:
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meta["source"] = str(model_path)
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return {k: v for k, v in meta.items() if k not in ("accuracy", "speed")}
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def get_markdown(data: Dict[str, Any], title: Optional[str] = None) -> str:
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"""Get data in GitHub-flavoured Markdown format for issues etc.
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data (dict or list of tuples): Label/value pairs.
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title (str / None): Title, will be rendered as headline 2.
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RETURNS (str): The Markdown string.
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"""
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markdown = []
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for key, value in data.items():
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if isinstance(value, str) and Path(value).exists():
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continue
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markdown.append(f"* **{key}:** {value}")
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result = "\n{}\n".format("\n".join(markdown))
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if title:
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result = f"\n## {title}\n{result}"
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return result
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