trw.train.options

Module Contents

Classes

TrainingParameters	Define here specific training parameters
WorkflowOptions	Define here workflow options
Runtime	Define here the runtime configuration
Options	Create default options for the training and evaluation process.

Functions

get_logging_root(logging_root: Optional[str] = None) → str

Return the data root directory

Attributes

logger

trw.train.options.logger

trw.train.options.get_logging_root(logging_root: Optional[str] = None) → str

Return the data root directory

class trw.train.options.TrainingParameters(num_epochs: int, mixed_precision_enabled: bool = False, gradient_update_frequency: int = 1)

Define here specific training parameters

__repr__(self) → str

Return repr(self).

class trw.train.options.WorkflowOptions(logging_directory: str, device: torch.device)

Define here workflow options

__repr__(self) → str

Return repr(self).

class trw.train.options.Runtime

Define here the runtime configuration

__repr__(self) → str

Return repr(self).

class trw.train.options.Options(logging_directory: Optional[str] = None, num_epochs: int = 50, device: Optional[torch.device] = None, mixed_precision_enabled: bool = False, gradient_update_frequency: int = 1)

Create default options for the training and evaluation process.

__repr__(self) → str

Return repr(self).