dacapo.experiments.run_config
Module Contents
Classes
A class to represent a configuration of a run that helps to structure all the tasks, |
- class dacapo.experiments.run_config.RunConfig
A class to represent a configuration of a run that helps to structure all the tasks, architecture, training, and datasplit configurations.
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Attributes:
- task_config: TaskConfig
A config defining the Task to run that includes deciding the output of the model and different methods to achieve the goal.
- architecture_config: ArchitectureConfig
A config that defines the backbone architecture of the model. It impacts the model’s performance significantly.
- trainer_config: TrainerConfig
Defines how batches are generated and passed for training the model along with defining configurations like batch size, learning rate, number of cpu workers and snapshot logging.
- datasplit_config: DataSplitConfig
Configures the data available for the model during training or validation phases.
- name: str
A unique name for this run to distinguish it.
- repetition: int
The repetition number of this run.
- num_iterations: int
The total number of iterations to train for during this run.
- validation_interval: int
Specifies how often to perform validation during the run. It defaults to 1000.
- start_configOptional[StartConfig]
A starting point for continued training. It is optional and can be left out.
- task_config: dacapo.experiments.tasks.TaskConfig
- architecture_config: dacapo.experiments.architectures.ArchitectureConfig
- trainer_config: dacapo.experiments.trainers.TrainerConfig
- datasplit_config: dacapo.experiments.datasplits.DataSplitConfig
- name: str
- repetition: int
- num_iterations: int
- validation_interval: int
- start_config: dacapo.experiments.starts.StartConfig | None