ade85ab32b
# Changes ## Dependencies - New extra "eval" ## Api Extension - `Experiment` and `ExperimentConfig` now have a `name`, that can however be overridden when `Experiment.run()` is called - When building an `Experiment` from an `ExperimentConfig`, the user has the option to add info about seeds to the name. - New method in `ExperimentConfig` called `build_default_seeded_experiments` - `SamplingConfig` has an explicit training seed, `test_seed` is inferred. - New `evaluation` package for repeating the same experiment with multiple seeds and aggregating the results (important extension!). Currently in alpha state. - Loggers can now restore the logged data into python by using the new `restore_logged_data` ## Breaking Changes - `AtariEnvFactory` (in examples) now receives explicit train and test seeds - `EnvFactoryRegistered` now requires an explicit `test_seed` - `BaseLogger.prepare_dict_for_logging` is now abstract --------- Co-authored-by: Maximilian Huettenrauch <m.huettenrauch@appliedai.de> Co-authored-by: Michael Panchenko <m.panchenko@appliedai.de> Co-authored-by: Michael Panchenko <35432522+MischaPanch@users.noreply.github.com>
109 lines
3.2 KiB
Python
109 lines
3.2 KiB
Python
from test.highlevel.env_factory import ContinuousTestEnvFactory, DiscreteTestEnvFactory
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import pytest
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from tianshou.highlevel.config import SamplingConfig
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from tianshou.highlevel.experiment import (
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A2CExperimentBuilder,
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DDPGExperimentBuilder,
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DiscreteSACExperimentBuilder,
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DQNExperimentBuilder,
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ExperimentBuilder,
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ExperimentConfig,
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IQNExperimentBuilder,
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PGExperimentBuilder,
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PPOExperimentBuilder,
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REDQExperimentBuilder,
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SACExperimentBuilder,
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TD3ExperimentBuilder,
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TRPOExperimentBuilder,
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)
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@pytest.mark.parametrize(
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"builder_cls",
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[
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PPOExperimentBuilder,
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A2CExperimentBuilder,
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SACExperimentBuilder,
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DDPGExperimentBuilder,
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TD3ExperimentBuilder,
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# NPGExperimentBuilder, # TODO test fails non-deterministically
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REDQExperimentBuilder,
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TRPOExperimentBuilder,
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PGExperimentBuilder,
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],
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)
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def test_experiment_builder_continuous_default_params(builder_cls: type[ExperimentBuilder]) -> None:
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env_factory = ContinuousTestEnvFactory()
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sampling_config = SamplingConfig(
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num_epochs=1,
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step_per_epoch=100,
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num_train_envs=2,
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num_test_envs=2,
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)
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experiment_config = ExperimentConfig(persistence_enabled=False)
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builder = builder_cls(
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experiment_config=experiment_config,
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env_factory=env_factory,
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sampling_config=sampling_config,
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)
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experiment = builder.build()
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experiment.run(override_experiment_name="test")
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print(experiment)
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@pytest.mark.parametrize(
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"builder_cls",
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[
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PPOExperimentBuilder,
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A2CExperimentBuilder,
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DQNExperimentBuilder,
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DiscreteSACExperimentBuilder,
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IQNExperimentBuilder,
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],
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)
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def test_experiment_builder_discrete_default_params(builder_cls: type[ExperimentBuilder]) -> None:
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env_factory = DiscreteTestEnvFactory()
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sampling_config = SamplingConfig(
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num_epochs=1,
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step_per_epoch=100,
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num_train_envs=2,
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num_test_envs=2,
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)
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builder = builder_cls(
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experiment_config=ExperimentConfig(persistence_enabled=False),
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env_factory=env_factory,
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sampling_config=sampling_config,
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)
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experiment = builder.build()
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experiment.run(override_experiment_name="test")
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print(experiment)
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def test_temp_builder_modification() -> None:
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env_factory = DiscreteTestEnvFactory()
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sampling_config = SamplingConfig(
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num_epochs=1,
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step_per_epoch=100,
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num_train_envs=2,
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num_test_envs=2,
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)
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builder = PPOExperimentBuilder(
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experiment_config=ExperimentConfig(persistence_enabled=False),
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env_factory=env_factory,
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sampling_config=sampling_config,
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)
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original_seed = builder.experiment_config.seed
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original_train_seed = builder.sampling_config.train_seed
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with builder.temp_config_mutation():
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builder.experiment_config.seed += 12345
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builder.sampling_config.train_seed += 456
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exp = builder.build()
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assert builder.experiment_config.seed == original_seed
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assert builder.sampling_config.train_seed == original_train_seed
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assert exp.config.seed == original_seed + 12345
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assert exp.sampling_config.train_seed == original_train_seed + 456
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