API Reference

class vanjari.apps.VanjariFast(**kwargs)

cache_dir() → Path

Returns a path to a directory where data files for this app can be cached.

checkpoint(checkpoint: Path = None) → str

Returns a path to a checkpoint to use for prediction.

data = Method(func=<function Corgi.data>, methods_to_call=[], main=False, tool=False, signature_ready=False)

extra_hyperparameters = Method(func=<function Corgi.extra_hyperparameters>, methods_to_call=[], main=False, tool=False, signature_ready=False)

gui = Method(func=<function CLIApp.gui>, methods_to_call=[], main=False, tool=True, signature_ready=False)

model = Method(func=<function Corgi.model>, methods_to_call=('module_class',), main=False, tool=False, signature_ready=False)

node_to_str(node: SoftmaxNode) → str

Converts the node to a string

predict = Method(func=<function TorchApp.predict>, methods_to_call=('load_checkpoint', 'prediction_trainer', 'prediction_dataloader', 'output_results'), main=True, tool=True, signature_ready=False)

train = Method(func=<function TorchApp.train>, methods_to_call=('setup', 'data', 'lightning_module', 'trainer'), main=False, tool=True, signature_ready=False)

tune = Method(func=<function TorchApp.tune>, methods_to_call=('train', 'project_name'), main=False, tool=True, signature_ready=False)

validate = Method(func=<function TorchApp.validate>, methods_to_call=('setup', 'data', 'load_checkpoint', 'trainer'), main=False, tool=True, signature_ready=False)

version(verbose: bool = False)

Prints the version of the package that defines this app.

Used in the command-line interface.

Parameters:

verbose (bool, optional) – Whether or not to print to stdout. Defaults to False.

Raises:

Exception – If it cannot find the package.