deeppavlov.core.commands¶
Basic training and inference functions.
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deeppavlov.core.commands.infer.
build_model
(config: Union[str, pathlib.Path, dict], mode: str = 'infer', load_trained: bool = False, install: bool = False, download: bool = False) → deeppavlov.core.common.chainer.Chainer[source]¶ Build and return the model described in corresponding configuration file.
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deeppavlov.core.commands.infer.
interact_model
(config: Union[str, pathlib.Path, dict]) → None[source]¶ Start interaction with the model described in corresponding configuration file.
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deeppavlov.core.commands.infer.
predict_on_stream
(config: Union[str, pathlib.Path, dict], batch_size: Optional[int] = None, file_path: Optional[str] = None) → None[source]¶ Make a prediction with the component described in corresponding configuration file.
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deeppavlov.core.commands.train.
get_iterator_from_config
(config: dict, data: dict)[source]¶ Create iterator (from config) for specified data.
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deeppavlov.core.commands.train.
read_data_by_config
(config: dict)[source]¶ Read data by dataset_reader from specified config.
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deeppavlov.core.commands.train.
train_evaluate_model_from_config
(config: Union[str, pathlib.Path, dict], iterator: Optional[Union[deeppavlov.core.data.data_learning_iterator.DataLearningIterator, deeppavlov.core.data.data_fitting_iterator.DataFittingIterator]] = None, *, to_train: bool = True, evaluation_targets: Optional[Iterable[str]] = None, install: bool = False, download: bool = False, start_epoch_num: Optional[int] = None, recursive: bool = False) → Dict[str, Dict[str, float]][source]¶ Make training and evaluation of the model described in corresponding configuration file.