czbenchmarks.runner

Attributes

logger

Classes

ContainerRunner

Handles Docker container execution logic for running models

Functions

run_inference(→ czbenchmarks.datasets.BaseDataset)

Convenience function to run inference on a single dataset.

Module Contents

czbenchmarks.runner.logger
class czbenchmarks.runner.ContainerRunner(model_name: str | czbenchmarks.models.types.ModelType, gpu: bool = False, interactive: bool = False, app_mount_dir: str | None = None, environment: Dict[str, str] | None = None, custom_config_path: str | None = None, **kwargs: Any)[source]

Handles Docker container execution logic for running models in isolated environments

client
image
model_type
app_mount_dir = None
gpu = False
interactive = False
cli_args
environment
run(datasets: czbenchmarks.datasets.BaseDataset | List[czbenchmarks.datasets.BaseDataset]) czbenchmarks.datasets.BaseDataset | List[czbenchmarks.datasets.BaseDataset][source]

Run the model on one or more datasets.

Parameters:

datasets – A single dataset or list of datasets to process

Returns:

The processed dataset(s) with model outputs attached

czbenchmarks.runner.run_inference(model_name: str, dataset: czbenchmarks.datasets.BaseDataset, gpu: bool = True, interactive: bool = False, app_mount_dir: str | None = None, environment: Dict[str, str] | None = None, custom_config_path: str | None = None, **kwargs) czbenchmarks.datasets.BaseDataset[source]

Convenience function to run inference on a single dataset.

Parameters:
  • model_name – Name of the model to run

  • dataset – Dataset to process

  • gpu – Whether to use GPU acceleration

  • interactive – Whether to run in interactive mode

  • app_mount_dir – Optional directory to mount to /app in the container (this will override the default /app mount from the docker build!)

  • environment – Dictionary of environment variables to pass to the container

  • custom_config_path – Path to a custom models.yaml file

  • **kwargs – Additional arguments to pass to the container as CLI params

Returns:

The processed dataset with model outputs attached