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83e06cd30a
* WIP. * WIP. * WIP. * WIP. * WIP. * Fix * WIP. * Add TD3 quick Pendulum regresison. * Cleanup. * Fix. * LINT. * Fix. * Sort quick_learning test cases, add TD3. * Sort quick_learning test cases, add TD3. * Revert test_checkpoint_restore.py (debugging) changes. * Fix old soft_q settings in documentation and test configs. * More doc fixes. * Fix test case. * Fix test case. * Lower test load. * WIP.
32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
from gym.spaces import Discrete
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from ray.rllib.utils.exploration.stochastic_sampling import StochasticSampling
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class SoftQ(StochasticSampling):
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"""Special case of StochasticSampling w/ Categorical and temperature param.
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Returns a stochastic sample from a Categorical parameterized by the model
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output divided by the temperature. Returns the argmax iff explore=False.
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"""
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def __init__(self,
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action_space,
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*,
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temperature=1.0,
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framework="tf",
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**kwargs):
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"""Initializes a SoftQ Exploration object.
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Args:
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action_space (Space): The gym action space used by the environment.
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temperature (Schedule): The temperature to divide model outputs by
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before creating the Categorical distribution to sample from.
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framework (Optional[str]): One of None, "tf", "torch".
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"""
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assert isinstance(action_space, Discrete)
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super().__init__(
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action_space,
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static_params=dict(temperature=temperature),
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framework=framework,
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**kwargs)
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