mirror of https://github.com/explosion/spaCy.git
Remove init form path
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@ -49,35 +49,11 @@ def train_cli(
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config = util.load_config(config_path, overrides=overrides, interpolate=False)
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config = util.load_config(config_path, overrides=overrides, interpolate=False)
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msg.divider("Initializing pipeline")
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msg.divider("Initializing pipeline")
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with show_validation_error(config_path, hint_fill=False):
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with show_validation_error(config_path, hint_fill=False):
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nlp = init_pipeline(config, output_path, use_gpu=use_gpu)
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nlp = init_nlp(config, use_gpu=use_gpu)
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msg.divider("Training pipeline")
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msg.divider("Training pipeline")
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train(nlp, output_path, use_gpu=use_gpu, silent=False)
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train(nlp, output_path, use_gpu=use_gpu, silent=False)
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def init_pipeline(
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config: Config, output_path: Optional[Path], *, use_gpu: int = -1
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) -> Language:
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init_kwargs = {"use_gpu": use_gpu}
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if output_path is not None:
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init_path = output_path / "model-initial"
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if not init_path.exists():
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msg.info(f"Initializing the pipeline in {init_path}")
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nlp = init_nlp(config, **init_kwargs)
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nlp.to_disk(init_path)
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msg.good(f"Saved initialized pipeline to {init_path}")
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else:
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nlp = util.load_model(init_path)
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if must_reinitialize(config, nlp.config):
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msg.warn("Config has changed: need to re-initialize pipeline")
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nlp = init_nlp(config, **init_kwargs)
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nlp.to_disk(init_path)
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msg.good(f"Re-initialized pipeline in {init_path}")
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else:
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msg.good(f"Loaded initialized pipeline from {init_path}")
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return nlp
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return init_nlp(config, **init_kwargs)
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def verify_cli_args(config_path: Path, output_path: Optional[Path] = None) -> None:
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def verify_cli_args(config_path: Path, output_path: Optional[Path] = None) -> None:
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# Make sure all files and paths exists if they are needed
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# Make sure all files and paths exists if they are needed
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if not config_path or not config_path.exists():
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if not config_path or not config_path.exists():
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