Running An Experiment From A Different Repository

🚧
Apologies, the code for this tutorial is out of date due to the major change in how we configure Monty. We'll update it soon™️.

If you have your own repository and want to run your own experiment or a benchmark, you do not need to replicate the tbp.monty benchmarks setup.

📘
We have a tbp.monty_project_template template repository, so that you can quickly use tbp.monty for your project, prototype, or paper.

You have the option of running everything from a single script file. The general setup is:

from tbp.monty.frameworks.run_env import setup_env

# call setup_env() to initialize environment used by
# tbp.monty configuration and runtime.
setup_env()

# imports from tbp.monty for use in your configuration

# import run or run_parallel to run the experiment
from tbp.monty.frameworks.run import run  # noqa: E402
from tbp.monty.frameworks.run_parallel import run_parallel  # noqa: E402

experiment_config = # your configuration

run(experiment_config)
# or
run_parallel(experiment_config)

A more filled out example:

import os

from tbp.monty.frameworks.run_env import setup_env

setup_env()

from tbp.monty.frameworks.config_utils.config_args import (  # noqa: E402
    LoggingConfig,
    PatchAndViewMontyConfig,
)
from tbp.monty.frameworks.config_utils.make_env_interface_configs import (  # noqa: E402
    SupervisedPretrainingExperimentArgs,
    get_env_interface_per_object_by_idx,
)
from tbp.monty.frameworks.environments import embodied_data as ED  # noqa: E402
from tbp.monty.frameworks.experiments.pretraining_experiments import (  # noqa: E402
    MontySupervisedObjectPretrainingExperiment,
)
from tbp.monty.frameworks.run import run  # noqa: E402
from tbp.monty.simulators.habitat.configs import (  # noqa: E402
    PatchViewFinderMountHabitatEnvInterfaceConfig,
)

first_experiment = dict(
    experiment_class=MontySupervisedObjectPretrainingExperiment,
    logging=LoggingConfig(
        log_parallel_wandb=False,
        run_name="test",
        output_dir=os.path.expanduser(
            os.path.join(os.getenv("MONTY_LOGS"), "projects/monty_runs/test")
        ),
    ),
    experiment_args=SupervisedPretrainingExperimentArgs(
        do_eval=False,
        max_train_steps=1,
        n_train_epochs=1,
    ),
    monty_config=PatchAndViewMontyConfig(),
    env_interface_config=PatchViewFinderMountHabitatEnvInterfaceConfig(),
    train_env_interface_class=ED.EnvironmentInterfacePerObject,
    train_env_interface_args=get_env_interface_per_object_by_idx(start=0, stop=1),
)

run(first_experiment)

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