spaCy/spacy/cli/_messages.py

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# coding: utf8
from __future__ import unicode_literals
2018-04-10 22:42:46 +03:00
💫 New JSON helpers, training data internals & CLI rewrite (#2932) * 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 * Remove outdated test * Add write_json and write_jsonl helpers * WIP: Update spacy train * Tidy up spacy train * WIP: Use wasabi for formatting * Add GoldParse helpers for JSON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
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# fmt: off
class Messages(object):
M001 = ("Download successful but linking failed")
M002 = ("Creating a shortcut link for 'en' didn't work (maybe you "
"don't have admin permissions?), but you can still load the "
"model via its full package name: nlp = spacy.load('{name}')")
M003 = ("Server error ({code})")
M004 = ("Couldn't fetch {desc}. Please find a model for your spaCy "
"installation (v{version}), and download it manually. For more "
"details, see the documentation: https://spacy.io/usage/models")
M005 = ("Compatibility error")
M006 = ("No compatible models found for v{version} of spaCy.")
M007 = ("No compatible model found for '{name}' (spaCy v{version}).")
M008 = ("Can't locate model data")
M009 = ("The data should be located in {path}")
M010 = ("Can't find the spaCy data path to create model symlink")
M011 = ("Make sure a directory `/data` exists within your spaCy "
"installation and try again. The data directory should be "
"located here:")
M012 = ("Link '{name}' already exists")
M013 = ("To overwrite an existing link, use the --force flag.")
M014 = ("Can't overwrite symlink '{name}'")
M015 = ("This can happen if your data directory contains a directory or "
"file of the same name.")
M016 = ("Error: Couldn't link model to '{name}'")
M017 = ("Creating a symlink in spacy/data failed. Make sure you have the "
"required permissions and try re-running the command as admin, or "
"use a virtualenv. You can still import the model as a module and "
"call its load() method, or create the symlink manually.")
M018 = ("Linking successful")
M019 = ("You can now load the model via spacy.load('{name}')")
M020 = ("Can't find model meta.json")
M021 = ("Couldn't fetch compatibility table.")
M022 = ("Can't find spaCy v{version} in compatibility table")
M023 = ("Installed models (spaCy v{version})")
M024 = ("No models found in your current environment.")
M025 = ("Use the following commands to update the model packages:")
M026 = ("The following models are not available for spaCy "
"v{version}: {models}")
M027 = ("You may also want to overwrite the incompatible links using the "
"`python -m spacy link` command with `--force`, or remove them "
"from the data directory. Data path: {path}")
M028 = ("Input file not found")
M029 = ("Output directory not found")
M030 = ("Unknown format")
M031 = ("Can't find converter for {converter}")
M032 = ("Generated output file {name}")
M033 = ("Created {n_docs} documents")
M034 = ("Evaluation data not found")
M035 = ("Visualization output directory not found")
M036 = ("Generated {n} parses as HTML")
M037 = ("Can't find words frequencies file")
M038 = ("Sucessfully compiled vocab")
M039 = ("{entries} entries, {vectors} vectors")
M040 = ("Output directory not found")
M041 = ("Loaded meta.json from file")
M042 = ("Successfully created package '{name}'")
M043 = ("To build the package, run `python setup.py sdist` in this "
"directory.")
M044 = ("Package directory already exists")
M045 = ("Please delete the directory and try again, or use the `--force` "
"flag to overwrite existing directories.")
M046 = ("Generating meta.json")
M047 = ("Enter the package settings for your model. The following "
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"information will be read from your model data: pipeline, vectors.")
M048 = ("No '{key}' setting found in meta.json")
M049 = ("This setting is required to build your package.")
M050 = ("Training data not found")
M051 = ("Development data not found")
M052 = ("Not a valid meta.json format")
M053 = ("Expected dict but got: {meta_type}")
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M054 = ("No --lang specified, but tokenization required.")
💫 New JSON helpers, training data internals & CLI rewrite (#2932) * 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
2018-11-30 22:16:14 +03:00
M055 = ("Training pipeline: {pipeline}")
M056 = ("Starting with base model '{model}'")
M057 = ("Starting with blank model '{model}'")
M058 = ("Loading vector from model '{model}'")
M059 = ("Can't use multitask objective without '{pipe}' in the pipeline")
M060 = ("Counting training words (limit={limit})")
M061 = ("\nSaving model...")
M062 = ("Output directory is not empty.")
M063 = ("Incompatible arguments")
M064 = ("The -f and -c arguments are deprecated, and not compatible with "
"the -j argument, which should specify the same information. "
"Either merge the frequencies and clusters data into the "
"JSONL-formatted file (recommended), or use only the -f and -c "
"files, without the other lexical attributes.")
M065 = ("This can lead to unintended side effects when saving the model. "
"Please use an empty directory or a different path instead. If "
"the specified output path doesn't exist, the directory will be "
"created for you.")
M066 = ("Saved model to output directory")
M067 = ("Can't find lexical data")
M068 = ("Sucessfully compiled vocab and vectors, and saved model")
M069 = ("Unknown file type: '{name}'")
M070 = ("Supported file types: '{options}'")
M071 = ("Loaded pretrained tok2vec for: {components}")
M072 = ("Model language ('{model_lang}') doesn't match language specified "
"as `lang` argument ('{lang}') ")
# fmt: on