152 lines
5.1 KiB
Python
Executable File
152 lines
5.1 KiB
Python
Executable File
# Copyright 2017 The dm_control Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""A collection of MuJoCo-based Reinforcement Learning environments."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import collections
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import inspect
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import itertools
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from dm_control.rl import control
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from local_dm_control_suite import acrobot
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from local_dm_control_suite import ball_in_cup
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from local_dm_control_suite import cartpole
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from local_dm_control_suite import cheetah
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from local_dm_control_suite import finger
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from local_dm_control_suite import fish
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from local_dm_control_suite import hopper
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from local_dm_control_suite import humanoid
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from local_dm_control_suite import humanoid_CMU
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from local_dm_control_suite import lqr
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from local_dm_control_suite import manipulator
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from local_dm_control_suite import pendulum
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from local_dm_control_suite import point_mass
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from local_dm_control_suite import quadruped
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from local_dm_control_suite import reacher
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from local_dm_control_suite import stacker
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from local_dm_control_suite import swimmer
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from local_dm_control_suite import walker
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# Find all domains imported.
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_DOMAINS = {name: module for name, module in locals().items()
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if inspect.ismodule(module) and hasattr(module, 'SUITE')}
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def _get_tasks(tag):
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"""Returns a sequence of (domain name, task name) pairs for the given tag."""
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result = []
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for domain_name in sorted(_DOMAINS.keys()):
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domain = _DOMAINS[domain_name]
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if tag is None:
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tasks_in_domain = domain.SUITE
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else:
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tasks_in_domain = domain.SUITE.tagged(tag)
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for task_name in tasks_in_domain.keys():
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result.append((domain_name, task_name))
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return tuple(result)
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def _get_tasks_by_domain(tasks):
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"""Returns a dict mapping from task name to a tuple of domain names."""
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result = collections.defaultdict(list)
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for domain_name, task_name in tasks:
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result[domain_name].append(task_name)
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return {k: tuple(v) for k, v in result.items()}
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# A sequence containing all (domain name, task name) pairs.
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ALL_TASKS = _get_tasks(tag=None)
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# Subsets of ALL_TASKS, generated via the tag mechanism.
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BENCHMARKING = _get_tasks('benchmarking')
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EASY = _get_tasks('easy')
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HARD = _get_tasks('hard')
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EXTRA = tuple(sorted(set(ALL_TASKS) - set(BENCHMARKING)))
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# A mapping from each domain name to a sequence of its task names.
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TASKS_BY_DOMAIN = _get_tasks_by_domain(ALL_TASKS)
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def load(domain_name, task_name, task_kwargs=None, environment_kwargs=None,
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visualize_reward=False):
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"""Returns an environment from a domain name, task name and optional settings.
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```python
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env = suite.load('cartpole', 'balance')
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```
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Args:
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domain_name: A string containing the name of a domain.
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task_name: A string containing the name of a task.
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task_kwargs: Optional `dict` of keyword arguments for the task.
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environment_kwargs: Optional `dict` specifying keyword arguments for the
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environment.
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visualize_reward: Optional `bool`. If `True`, object colours in rendered
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frames are set to indicate the reward at each step. Default `False`.
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Returns:
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The requested environment.
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"""
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return build_environment(domain_name, task_name, task_kwargs,
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environment_kwargs, visualize_reward)
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def build_environment(domain_name, task_name, task_kwargs=None,
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environment_kwargs=None, visualize_reward=False):
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"""Returns an environment from the suite given a domain name and a task name.
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Args:
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domain_name: A string containing the name of a domain.
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task_name: A string containing the name of a task.
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task_kwargs: Optional `dict` specifying keyword arguments for the task.
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environment_kwargs: Optional `dict` specifying keyword arguments for the
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environment.
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visualize_reward: Optional `bool`. If `True`, object colours in rendered
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frames are set to indicate the reward at each step. Default `False`.
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Raises:
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ValueError: If the domain or task doesn't exist.
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Returns:
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An instance of the requested environment.
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"""
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if domain_name not in _DOMAINS:
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raise ValueError('Domain {!r} does not exist.'.format(domain_name))
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domain = _DOMAINS[domain_name]
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if task_name not in domain.SUITE:
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raise ValueError('Level {!r} does not exist in domain {!r}.'.format(
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task_name, domain_name))
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task_kwargs = task_kwargs or {}
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if environment_kwargs is not None:
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task_kwargs = task_kwargs.copy()
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task_kwargs['environment_kwargs'] = environment_kwargs
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env = domain.SUITE[task_name](**task_kwargs)
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env.task.visualize_reward = visualize_reward
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return env
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