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docs/source/trainer.rst

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@@ -612,10 +612,10 @@ stored. If you don't then use this argument for convenience. Paths can be local
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paths or remote paths such as `s3://bucket/path` or 'hdfs://path/'. Credentials
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will need to be set up to use remote filepaths.
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Example::
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.. testcode::
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# default used by the Trainer
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trainer = Trainer(default_root_path=os.getcwd())
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trainer = Trainer(default_root_dir=os.getcwd())
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distributed_backend
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^^^^^^^^^^^^^^^^^^^

notebooks/05-trainer-flags-overview.ipynb

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"outputs": [],
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"source": [
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"# default used by the Trainer\n",
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"trainer = pl.Trainer(default_root_path=os.getcwd())\n",
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"trainer = pl.Trainer(default_root_dir=os.getcwd())\n",
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"\n",
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"trainer.fit(model, train_loader, val_loader)"
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]

pytorch_lightning/trainer/properties.py

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@@ -48,7 +48,6 @@ class TrainerProperties(ABC):
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limit_val_batches: int
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_default_root_dir: str
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_weights_save_path: str
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default_root_path: str
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accelerator_backend: Accelerator
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logger: LightningLoggerBase
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model_connector: ModelConnector

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