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Fix references to config file in the docs & UX (#9961)
* doc fixes around config file * fix typo * clarify default
This commit is contained in:
Sofie Van Landeghem
GitHub
parent
029a48e340
commit
56dcb39fb7
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@ -25,7 +25,7 @@ def debug_config_cli(
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show_vars: bool = Opt(False, "--show-variables", "-V", help="Show an overview of all variables referenced in the config and their values. This will also reflect variables overwritten on the CLI.")
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# fmt: on
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):
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"""Debug a config.cfg file and show validation errors. The command will
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"""Debug a config file and show validation errors. The command will
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create all objects in the tree and validate them. Note that some config
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validation errors are blocking and will prevent the rest of the config from
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being resolved. This means that you may not see all validation errors at
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@ -27,7 +27,7 @@ class Optimizations(str, Enum):
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@init_cli.command("config")
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def init_config_cli(
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# fmt: off
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output_file: Path = Arg(..., help="File to save config.cfg to or - for stdout (will only output config and no additional logging info)", allow_dash=True),
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output_file: Path = Arg(..., help="File to save the config to or - for stdout (will only output config and no additional logging info)", allow_dash=True),
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lang: str = Opt("en", "--lang", "-l", help="Two-letter code of the language to use"),
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pipeline: str = Opt("tagger,parser,ner", "--pipeline", "-p", help="Comma-separated names of trainable pipeline components to include (without 'tok2vec' or 'transformer')"),
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optimize: Optimizations = Opt(Optimizations.efficiency.value, "--optimize", "-o", help="Whether to optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger and slower model). This will impact the choice of architecture, pretrained weights and related hyperparameters."),
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@ -37,7 +37,7 @@ def init_config_cli(
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# fmt: on
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):
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"""
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Generate a starter config.cfg for training. Based on your requirements
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Generate a starter config file for training. Based on your requirements
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specified via the CLI arguments, this command generates a config with the
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optimal settings for your use case. This includes the choice of architecture,
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pretrained weights and related hyperparameters.
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@ -66,15 +66,15 @@ def init_config_cli(
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@init_cli.command("fill-config")
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def init_fill_config_cli(
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# fmt: off
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base_path: Path = Arg(..., help="Base config to fill", exists=True, dir_okay=False),
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output_file: Path = Arg("-", help="File to save config.cfg to (or - for stdout)", allow_dash=True),
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base_path: Path = Arg(..., help="Path to base config to fill", exists=True, dir_okay=False),
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output_file: Path = Arg("-", help="Path to output .cfg file (or - for stdout)", allow_dash=True),
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pretraining: bool = Opt(False, "--pretraining", "-pt", help="Include config for pretraining (with 'spacy pretrain')"),
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diff: bool = Opt(False, "--diff", "-D", help="Print a visual diff highlighting the changes"),
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code_path: Optional[Path] = Opt(None, "--code-path", "--code", "-c", help="Path to Python file with additional code (registered functions) to be imported"),
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# fmt: on
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):
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"""
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Fill partial config.cfg with default values. Will add all missing settings
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Fill partial config file with default values. Will add all missing settings
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from the default config and will create all objects, check the registered
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functions for their default values and update the base config. This command
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can be used with a config generated via the training quickstart widget:
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@ -642,7 +642,7 @@ class Errors(metaclass=ErrorsWithCodes):
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E912 = ("Failed to initialize lemmatizer. Missing lemmatizer table(s) found "
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"for mode '{mode}'. Required tables: {tables}. Found: {found}.")
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E913 = ("Corpus path can't be None. Maybe you forgot to define it in your "
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"config.cfg or override it on the CLI?")
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".cfg file or override it on the CLI?")
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E914 = ("Executing {name} callback failed. Expected the function to "
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"return the nlp object but got: {value}. Maybe you forgot to return "
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"the modified object in your function?")
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@ -63,7 +63,7 @@ OOV_RANK = numpy.iinfo(numpy.uint64).max
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DEFAULT_OOV_PROB = -20
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LEXEME_NORM_LANGS = ["cs", "da", "de", "el", "en", "id", "lb", "mk", "pt", "ru", "sr", "ta", "th"]
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# Default order of sections in the config.cfg. Not all sections needs to exist,
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# Default order of sections in the config file. Not all sections needs to exist,
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# and additional sections are added at the end, in alphabetical order.
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CONFIG_SECTION_ORDER = ["paths", "variables", "system", "nlp", "components", "corpora", "training", "pretraining", "initialize"]
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# fmt: on
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@ -465,7 +465,7 @@ def load_model_from_path(
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"""Load a model from a data directory path. Creates Language class with
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pipeline from config.cfg and then calls from_disk() with path.
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model_path (Path): Mmodel path.
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model_path (Path): Model path.
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meta (Dict[str, Any]): Optional model meta.
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vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
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a new Vocab object will be created.
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@ -642,8 +642,8 @@ def load_config(
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sys.stdin.read(), overrides=overrides, interpolate=interpolate
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)
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else:
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if not config_path or not config_path.exists() or not config_path.is_file():
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raise IOError(Errors.E053.format(path=config_path, name="config.cfg"))
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if not config_path or not config_path.is_file():
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raise IOError(Errors.E053.format(path=config_path, name="config file"))
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return config.from_disk(
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config_path, overrides=overrides, interpolate=interpolate
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)
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@ -148,8 +148,8 @@ $ python -m spacy init config [output_file] [--lang] [--pipeline] [--optimize] [
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### init fill-config {#init-fill-config new="3"}
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Auto-fill a partial [`config.cfg` file](/usage/training#config) file with **all
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default values**, e.g. a config generated with the
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Auto-fill a partial [.cfg file](/usage/training#config) with **all default
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values**, e.g. a config generated with the
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[quickstart widget](/usage/training#quickstart). Config files used for training
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should always be complete and not contain any hidden defaults or missing values,
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so this command helps you create your final training config. In order to find
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@ -175,7 +175,7 @@ $ python -m spacy init fill-config [base_path] [output_file] [--diff]
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| Name | Description |
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| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `base_path` | Path to base config to fill, e.g. generated by the [quickstart widget](/usage/training#quickstart). ~~Path (positional)~~ |
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| `output_file` | Path to output `.cfg` file. If not set, the config is written to stdout so you can pipe it forward to a file. ~~Path (positional)~~ |
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| `output_file` | Path to output `.cfg` file or "-" to write to stdout so you can pipe it to a file. Defaults to "-" (stdout). ~~Path (positional)~~ |
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| `--code`, `-c` | Path to Python file with additional code to be imported. Allows [registering custom functions](/usage/training#custom-functions) for new architectures. ~~Optional[Path] \(option)~~ |
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| `--pretraining`, `-pt` | Include config for pretraining (with [`spacy pretrain`](/api/cli#pretrain)). Defaults to `False`. ~~bool (flag)~~ |
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| `--diff`, `-D` | Print a visual diff highlighting the changes. ~~bool (flag)~~ |
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@ -535,7 +535,7 @@ As of spaCy v3.0, the `meta.json` **isn't** used to construct the language class
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and pipeline anymore and only contains meta information for reference and for
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creating a Python package with [`spacy package`](/api/cli#package). How to set
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up the `nlp` object is now defined in the
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[`config.cfg`](/api/data-formats#config), which includes detailed information
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[config file](/api/data-formats#config), which includes detailed information
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about the pipeline components and their model architectures, and all other
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settings and hyperparameters used to train the pipeline. It's the **single
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source of truth** used for loading a pipeline.
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