repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
dspy | dspy/adapters/types/history.py | .py | from typing import Any
import pydantic
class History(pydantic.BaseModel):
"""Class representing the conversation history.
The conversation history is a list of messages, each message entity should have keys from the associated signature.
For example, if you have the following signature:
```
cla... | 69 | 2,113 |
dspy | dspy/adapters/types/code.py | .py | import re
from typing import Any, ClassVar
import pydantic
from pydantic import create_model
from dspy.adapters.types.base_type import Type
class Code(Type):
"""Code type in DSPy.
This type is useful for code generation and code analysis.
Example 1: dspy.Code as output type in code generation:
``... | 132 | 3,837 |
dspy | dspy/adapters/types/audio.py | .py | import base64
import io
import mimetypes
import os
import warnings
from typing import Any, Union
from urllib.parse import urlparse
import pydantic
import requests
from dspy.adapters.types.base_type import Type
try:
import soundfile as sf
SF_AVAILABLE = True
except ImportError:
SF_AVAILABLE = False
def... | 213 | 8,656 |
dspy | dspy/adapters/types/tool.py | .py | import asyncio
import inspect
from typing import TYPE_CHECKING, Any, Callable, get_origin, get_type_hints
import json_repair
import pydantic
from jsonschema import ValidationError, validate
from pydantic import BaseModel, TypeAdapter, create_model
from dspy.adapters.types.base_type import Type
from dspy.dsp.utils.set... | 560 | 21,554 |
dspy | dspy/adapters/types/reasoning.py | .py | from typing import TYPE_CHECKING, Any, Optional
import pydantic
from dspy.adapters.types.base_type import Type
from dspy.clients.base_lm import BaseLM
if TYPE_CHECKING:
from dspy.signatures.signature import Signature
class Reasoning(Type):
"""Reasoning type in DSPy.
This type is useful when you want t... | 171 | 6,231 |
dspy | dspy/adapters/types/document.py | .py | from typing import Any, Literal
import pydantic
from dspy.adapters.types.base_type import Type
from dspy.utils.annotation import experimental
@experimental(version="3.0.4")
class Document(Type):
"""A document type for providing content that can be cited by language models.
This type represents documents th... | 115 | 3,843 |
dspy | dspy/adapters/types/base_type.py | .py | import json
import re
from typing import TYPE_CHECKING, Any, Optional, get_args, get_origin
import json_repair
import pydantic
from dspy.clients.base_lm import BaseLM
if TYPE_CHECKING:
from litellm import ModelResponseStream
from dspy.signatures.signature import Signature
CUSTOM_TYPE_START_IDENTIFIER = "<<... | 218 | 7,718 |
gym | setup.py | .py | """Setups the project."""
import itertools
import re
from setuptools import find_packages, setup
with open("gym/version.py") as file:
full_version = file.read()
assert (
re.match(r'VERSION = "\d\.\d+\.\d+"\n', full_version).group(0) == full_version
), f"Unexpected version: {full_version}"
VERS... | 91 | 3,048 |
gym | gym/error.py | .py | """Set of Error classes for gym."""
import warnings
class Error(Exception):
"""Error superclass."""
# Local errors
class Unregistered(Error):
"""Raised when the user requests an item from the registry that does not actually exist."""
class UnregisteredEnv(Unregistered):
"""Raised when the user reque... | 195 | 5,545 |
gym | gym/logger.py | .py | """Set of functions for logging messages."""
import sys
import warnings
from typing import Optional, Type
from gym.utils import colorize
DEBUG = 10
INFO = 20
WARN = 30
ERROR = 40
DISABLED = 50
min_level = 30
# Ensure DeprecationWarning to be displayed (#2685, #3059)
warnings.filterwarnings("once", "", DeprecationW... | 74 | 1,774 |
gym | gym/__init__.py | .py | """Root __init__ of the gym module setting the __all__ of gym modules."""
# isort: skip_file
from gym import error
from gym.version import VERSION as __version__
from gym.core import (
Env,
Wrapper,
ObservationWrapper,
ActionWrapper,
RewardWrapper,
)
from gym.spaces import Space
from gym.envs impo... | 44 | 1,177 |
gym | gym/core.py | .py | """Core API for Environment, Wrapper, ActionWrapper, RewardWrapper and ObservationWrapper."""
import sys
from typing import (
TYPE_CHECKING,
Any,
Dict,
Generic,
List,
Optional,
SupportsFloat,
Tuple,
TypeVar,
Union,
)
import numpy as np
from gym import spaces
from gym.logger imp... | 469 | 20,620 |
gym | gym/wrappers/clip_action.py | .py | """Wrapper for clipping actions within a valid bound."""
import numpy as np
import gym
from gym import ActionWrapper
from gym.spaces import Box
class ClipAction(ActionWrapper):
"""Clip the continuous action within the valid :class:`Box` observation space bound.
Example:
>>> import gym
>>> en... | 41 | 1,155 |
gym | gym/wrappers/normalize.py | .py | """Set of wrappers for normalizing actions and observations."""
import numpy as np
import gym
# taken from https://github.com/openai/baselines/blob/master/baselines/common/vec_env/vec_normalize.py
class RunningMeanStd:
"""Tracks the mean, variance and count of values."""
# https://en.wikipedia.org/wiki/Algo... | 145 | 5,712 |
gym | gym/wrappers/time_limit.py | .py | """Wrapper for limiting the time steps of an environment."""
from typing import Optional
import gym
class TimeLimit(gym.Wrapper):
"""This wrapper will issue a `truncated` signal if a maximum number of timesteps is exceeded.
If a truncation is not defined inside the environment itself, this is the only place... | 69 | 2,527 |
gym | gym/wrappers/transform_reward.py | .py | """Wrapper for transforming the reward."""
from typing import Callable
import gym
from gym import RewardWrapper
class TransformReward(RewardWrapper):
"""Transform the reward via an arbitrary function.
Warning:
If the base environment specifies a reward range which is not invariant under :attr:`f`, t... | 45 | 1,332 |
gym | gym/wrappers/atari_preprocessing.py | .py | """Implementation of Atari 2600 Preprocessing following the guidelines of Machado et al., 2018."""
import numpy as np
import gym
from gym.spaces import Box
try:
import cv2
except ImportError:
cv2 = None
class AtariPreprocessing(gym.Wrapper):
"""Atari 2600 preprocessing wrapper.
This class follows t... | 191 | 7,860 |
gym | gym/wrappers/gray_scale_observation.py | .py | """Wrapper that converts a color observation to grayscale."""
import numpy as np
import gym
from gym.spaces import Box
class GrayScaleObservation(gym.ObservationWrapper):
"""Convert the image observation from RGB to gray scale.
Example:
>>> env = gym.make('CarRacing-v1')
>>> env.observation_... | 65 | 2,079 |
gym | gym/wrappers/env_checker.py | .py | """A passive environment checker wrapper for an environment's observation and action space along with the reset, step and render functions."""
import gym
from gym.core import ActType
from gym.utils.passive_env_checker import (
check_action_space,
check_observation_space,
env_render_passive_checker,
env_... | 56 | 2,306 |
gym | gym/wrappers/order_enforcing.py | .py | """Wrapper to enforce the proper ordering of environment operations."""
import gym
from gym.error import ResetNeeded
class OrderEnforcing(gym.Wrapper):
"""A wrapper that will produce an error if :meth:`step` is called before an initial :meth:`reset`.
Example:
>>> from gym.envs.classic_control import ... | 57 | 2,158 |
gym | gym/wrappers/pixel_observation.py | .py | """Wrapper for augmenting observations by pixel values."""
import collections
import copy
from collections.abc import MutableMapping
from typing import Any, Dict, List, Optional, Tuple
import numpy as np
import gym
from gym import spaces
STATE_KEY = "state"
class PixelObservationWrapper(gym.ObservationWrapper):
... | 208 | 8,049 |
gym | gym/wrappers/vector_list_info.py | .py | """Wrapper that converts the info format for vec envs into the list format."""
from typing import List
import gym
class VectorListInfo(gym.Wrapper):
"""Converts infos of vectorized environments from dict to List[dict].
This wrapper converts the info format of a
vector environment from a dictionary to a... | 112 | 3,821 |
gym | gym/wrappers/record_video.py | .py | """Wrapper for recording videos."""
import os
from typing import Callable, Optional
import gym
from gym import logger
from gym.wrappers.monitoring import video_recorder
def capped_cubic_video_schedule(episode_id: int) -> bool:
"""The default episode trigger.
This function will trigger recordings at the epis... | 212 | 8,310 |
gym | gym/wrappers/flatten_observation.py | .py | """Wrapper for flattening observations of an environment."""
import gym
import gym.spaces as spaces
class FlattenObservation(gym.ObservationWrapper):
"""Observation wrapper that flattens the observation.
Example:
>>> import gym
>>> env = gym.make('CarRacing-v1')
>>> env.observation_sp... | 41 | 1,092 |
gym | gym/wrappers/record_episode_statistics.py | .py | """Wrapper that tracks the cumulative rewards and episode lengths."""
import time
from collections import deque
from typing import Optional
import numpy as np
import gym
def add_vector_episode_statistics(
info: dict, episode_info: dict, num_envs: int, env_num: int
):
"""Add episode statistics.
Add stat... | 152 | 5,650 |
gym | gym/wrappers/time_aware_observation.py | .py | """Wrapper for adding time aware observations to environment observation."""
import numpy as np
import gym
from gym.spaces import Box
class TimeAwareObservation(gym.ObservationWrapper):
"""Augment the observation with the current time step in the episode.
The observation space of the wrapped environment is ... | 72 | 2,402 |
gym | gym/wrappers/frame_stack.py | .py | """Wrapper that stacks frames."""
from collections import deque
from typing import Union
import numpy as np
import gym
from gym.error import DependencyNotInstalled
from gym.spaces import Box
class LazyFrames:
"""Ensures common frames are only stored once to optimize memory use.
To further reduce the memory... | 191 | 6,322 |
gym | gym/wrappers/compatibility.py | .py | """A compatibility wrapper converting an old-style environment into a valid environment."""
import sys
from typing import Any, Dict, Optional, Tuple
import gym
from gym.core import ObsType
from gym.utils.step_api_compatibility import convert_to_terminated_truncated_step_api
if sys.version_info >= (3, 8):
from typ... | 131 | 4,288 |
gym | gym/wrappers/filter_observation.py | .py | """A wrapper for filtering dictionary observations by their keys."""
import copy
from typing import Sequence
import gym
from gym import spaces
class FilterObservation(gym.ObservationWrapper):
"""Filter Dict observation space by the keys.
Example:
>>> import gym
>>> env = gym.wrappers.Transfo... | 92 | 3,435 |
gym | gym/wrappers/resize_observation.py | .py | """Wrapper for resizing observations."""
from typing import Union
import numpy as np
import gym
from gym.error import DependencyNotInstalled
from gym.spaces import Box
class ResizeObservation(gym.ObservationWrapper):
"""Resize the image observation.
This wrapper works on environments with image observation... | 73 | 2,399 |
gym | gym/wrappers/autoreset.py | .py | """Wrapper that autoreset environments when `terminated=True` or `truncated=True`."""
import gym
class AutoResetWrapper(gym.Wrapper):
"""A class for providing an automatic reset functionality for gym environments when calling :meth:`self.step`.
When calling step causes :meth:`Env.step` to return `terminated=... | 62 | 3,131 |
gym | gym/wrappers/render_collection.py | .py | """A wrapper that adds render collection mode to an environment."""
import gym
class RenderCollection(gym.Wrapper):
"""Save collection of render frames."""
def __init__(self, env: gym.Env, pop_frames: bool = True, reset_clean: bool = True):
"""Initialize a :class:`RenderCollection` instance.
... | 53 | 1,804 |
gym | gym/wrappers/transform_observation.py | .py | """Wrapper for transforming observations."""
from typing import Any, Callable
import gym
class TransformObservation(gym.ObservationWrapper):
"""Transform the observation via an arbitrary function :attr:`f`.
The function :attr:`f` should be defined on the observation space of the base environment, ``env``, a... | 44 | 1,672 |
gym | gym/wrappers/rescale_action.py | .py | """Wrapper for rescaling actions to within a max and min action."""
from typing import Union
import numpy as np
import gym
from gym import spaces
class RescaleAction(gym.ActionWrapper):
"""Affinely rescales the continuous action space of the environment to the range [min_action, max_action].
The base envir... | 83 | 3,100 |
gym | gym/wrappers/human_rendering.py | .py | """A wrapper that adds human-renering functionality to an environment."""
import numpy as np
import gym
from gym.error import DependencyNotInstalled
class HumanRendering(gym.Wrapper):
"""Performs human rendering for an environment that only supports "rgb_array"rendering.
This wrapper is particularly useful ... | 133 | 5,051 |
gym | gym/wrappers/step_api_compatibility.py | .py | """Implementation of StepAPICompatibility wrapper class for transforming envs between new and old step API."""
import gym
from gym.logger import deprecation
from gym.utils.step_api_compatibility import (
convert_to_done_step_api,
convert_to_terminated_truncated_step_api,
)
class StepAPICompatibility(gym.Wrapp... | 59 | 2,649 |
gym | gym/wrappers/monitoring/video_recorder.py | .py | """A wrapper for video recording environments by rolling it out, frame by frame."""
import json
import os
import os.path
import tempfile
from typing import List, Optional
from gym import error, logger
class VideoRecorder:
"""VideoRecorder renders a nice movie of a rollout, frame by frame.
It comes with an `... | 179 | 6,362 |
gym | gym/vector/__init__.py | .py | """Module for vector environments."""
from typing import Iterable, List, Optional, Union
import gym
from gym.vector.async_vector_env import AsyncVectorEnv
from gym.vector.sync_vector_env import SyncVectorEnv
from gym.vector.vector_env import VectorEnv, VectorEnvWrapper
__all__ = ["AsyncVectorEnv", "SyncVectorEnv", "V... | 74 | 3,023 |
gym | gym/vector/async_vector_env.py | .py | """An async vector environment."""
import multiprocessing as mp
import sys
import time
from copy import deepcopy
from enum import Enum
from typing import List, Optional, Sequence, Tuple, Union
import numpy as np
import gym
from gym import logger
from gym.core import ObsType
from gym.error import (
AlreadyPendingC... | 685 | 27,608 |
gym | gym/vector/sync_vector_env.py | .py | """A synchronous vector environment."""
from copy import deepcopy
from typing import Any, Callable, Iterator, List, Optional, Sequence, Union
import numpy as np
from gym import Env
from gym.spaces import Space
from gym.vector.utils import concatenate, create_empty_array, iterate
from gym.vector.vector_env import Vect... | 237 | 8,760 |
gym | gym/vector/vector_env.py | .py | """Base class for vectorized environments."""
from typing import Any, List, Optional, Tuple, Union
import numpy as np
import gym
from gym.vector.utils.spaces import batch_space
__all__ = ["VectorEnv"]
class VectorEnv(gym.Env):
"""Base class for vectorized environments. Runs multiple independent copies of the s... | 333 | 11,487 |
gym | gym/vector/utils/misc.py | .py | """Miscellaneous utilities."""
import contextlib
import os
__all__ = ["CloudpickleWrapper", "clear_mpi_env_vars"]
class CloudpickleWrapper:
"""Wrapper that uses cloudpickle to pickle and unpickle the result."""
def __init__(self, fn: callable):
"""Cloudpickle wrapper for a function."""
self.... | 56 | 1,587 |
gym | gym/vector/utils/shared_memory.py | .py | """Utility functions for vector environments to share memory between processes."""
import multiprocessing as mp
from collections import OrderedDict
from ctypes import c_bool
from functools import singledispatch
from typing import Union
import numpy as np
from gym.error import CustomSpaceError
from gym.spaces import B... | 183 | 6,522 |
gym | gym/vector/utils/__init__.py | .py | """Module for gym vector utils."""
from gym.vector.utils.misc import CloudpickleWrapper, clear_mpi_env_vars
from gym.vector.utils.numpy_utils import concatenate, create_empty_array
from gym.vector.utils.shared_memory import (
create_shared_memory,
read_from_shared_memory,
write_to_shared_memory,
)
from gym.... | 24 | 727 |
gym | gym/vector/utils/spaces.py | .py | """Utility functions for gym spaces: batch space and iterator."""
from collections import OrderedDict
from copy import deepcopy
from functools import singledispatch
from typing import Iterator
import numpy as np
from gym.error import CustomSpaceError
from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscr... | 212 | 6,434 |
gym | gym/vector/utils/numpy_utils.py | .py | """Numpy utility functions: concatenate space samples and create empty array."""
from collections import OrderedDict
from functools import singledispatch
from typing import Iterable, Union
import numpy as np
from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Space, Tuple
__all__ = ["concatenate"... | 137 | 4,477 |
gym | gym/spaces/multi_binary.py | .py | """Implementation of a space that consists of binary np.ndarrays of a fixed shape."""
from typing import Optional, Sequence, Tuple, Union
import numpy as np
from gym.spaces.space import Space
class MultiBinary(Space[np.ndarray]):
"""An n-shape binary space.
Elements of this space are binary arrays of a sha... | 119 | 4,569 |
gym | gym/spaces/utils.py | .py | """Implementation of utility functions that can be applied to spaces.
These functions mostly take care of flattening and unflattening elements of spaces
to facilitate their usage in learning code.
"""
import operator as op
from collections import OrderedDict
from functools import reduce, singledispatch
from typing im... | 451 | 14,940 |
gym | gym/spaces/sequence.py | .py | """Implementation of a space that represents finite-length sequences."""
from collections.abc import Sequence as CollectionSequence
from typing import Any, List, Optional, Tuple, Union
import numpy as np
import gym
from gym.spaces.space import Space
class Sequence(Space[Tuple]):
r"""This space represent sets of... | 127 | 5,487 |
gym | gym/spaces/box.py | .py | """Implementation of a space that represents closed boxes in euclidean space."""
from typing import Dict, List, Optional, Sequence, SupportsFloat, Tuple, Type, Union
import numpy as np
import gym.error
from gym import logger
from gym.spaces.space import Space
def _short_repr(arr: np.ndarray) -> str:
"""Create a... | 339 | 12,732 |
gym | gym/spaces/__init__.py | .py | """This module implements various spaces.
Spaces describe mathematical sets and are used in Gym to specify valid actions and observations.
Every Gym environment must have the attributes ``action_space`` and ``observation_space``.
If, for instance, three possible actions (0,1,2) can be performed in your environment and... | 40 | 1,266 |
gym | gym/spaces/multi_discrete.py | .py | """Implementation of a space that represents the cartesian product of `Discrete` spaces."""
from typing import Iterable, List, Optional, Sequence, Tuple, Union
import numpy as np
from gym import logger
from gym.spaces.discrete import Discrete
from gym.spaces.space import Space
class MultiDiscrete(Space[np.ndarray])... | 176 | 7,519 |
gym | gym/spaces/tuple.py | .py | """Implementation of a space that represents the cartesian product of other spaces."""
from collections.abc import Sequence as CollectionSequence
from typing import Iterable, Optional
from typing import Sequence as TypingSequence
from typing import Tuple as TypingTuple
from typing import Union
import numpy as np
from... | 163 | 6,382 |
gym | gym/spaces/text.py | .py | """Implementation of a space that represents textual strings."""
from typing import Any, Dict, FrozenSet, Optional, Set, Tuple, Union
import numpy as np
from gym.spaces.space import Space
alphanumeric: FrozenSet[str] = frozenset(
"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
)
class Text(Spa... | 186 | 7,660 |
gym | gym/spaces/discrete.py | .py | """Implementation of a space consisting of finitely many elements."""
from typing import Optional, Union
import numpy as np
from gym.spaces.space import Space
class Discrete(Space[int]):
r"""A space consisting of finitely many elements.
This class represents a finite subset of integers, more specifically a... | 127 | 4,476 |
gym | gym/spaces/dict.py | .py | """Implementation of a space that represents the cartesian product of other spaces as a dictionary."""
from collections import OrderedDict
from collections.abc import Mapping, Sequence
from typing import Any
from typing import Dict as TypingDict
from typing import List, Optional
from typing import Sequence as TypingSeq... | 246 | 10,427 |
gym | gym/spaces/space.py | .py | """Implementation of the `Space` metaclass."""
from typing import (
Any,
Generic,
Iterable,
List,
Mapping,
Optional,
Sequence,
Tuple,
Type,
TypeVar,
Union,
)
import numpy as np
from gym.utils import seeding
T_cov = TypeVar("T_cov", covariant=True)
class Space(Generic[T_... | 151 | 5,653 |
gym | gym/spaces/graph.py | .py | """Implementation of a space that represents graph information where nodes and edges can be represented with euclidean space."""
from typing import NamedTuple, Optional, Sequence, Tuple, Union
import numpy as np
from gym.logger import warn
from gym.spaces.box import Box
from gym.spaces.discrete import Discrete
from g... | 239 | 9,771 |
gym | gym/utils/colorize.py | .py | """A set of common utilities used within the environments.
These are not intended as API functions, and will not remain stable over time.
"""
color2num = dict(
gray=30,
red=31,
green=32,
yellow=33,
blue=34,
magenta=35,
cyan=36,
white=37,
crimson=38,
)
def colorize(
string: st... | 42 | 974 |
gym | gym/utils/ezpickle.py | .py | """Class for pickling and unpickling objects via their constructor arguments."""
class EzPickle:
"""Objects that are pickled and unpickled via their constructor arguments.
Example::
>>> class Dog(Animal, EzPickle):
... def __init__(self, furcolor, tailkind="bushy"):
... Ani... | 36 | 1,354 |
gym | gym/utils/env_checker.py | .py | """A set of functions for checking an environment details.
This file is originally from the Stable Baselines3 repository hosted on GitHub
(https://github.com/DLR-RM/stable-baselines3/)
Original Author: Antonin Raffin
It also uses some warnings/assertions from the PettingZoo repository hosted on GitHub
(https://github... | 311 | 12,606 |
gym | gym/utils/__init__.py | .py | """A set of common utilities used within the environments.
These are not intended as API functions, and will not remain stable over time.
"""
# These submodules should not have any import-time dependencies.
# We want this since we use `utils` during our import-time sanity checks
# that verify that our dependencies ar... | 11 | 420 |
gym | gym/utils/play.py | .py | """Utilities of visualising an environment."""
from collections import deque
from typing import Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import gym.error
from gym import Env, logger
from gym.core import ActType, ObsType
from gym.error import DependencyNotInstalled
from gym.logger import depreca... | 387 | 15,289 |
gym | gym/utils/seeding.py | .py | """Set of random number generator functions: seeding, generator, hashing seeds."""
from typing import Any, Optional, Tuple
import numpy as np
from gym import error
def np_random(seed: Optional[int] = None) -> Tuple[np.random.Generator, Any]:
"""Generates a random number generator from the seed and returns the G... | 31 | 911 |
gym | gym/utils/save_video.py | .py | """Utility functions to save rendering videos."""
import os
from typing import Callable, Optional
import gym
from gym import logger
try:
from moviepy.video.io.ImageSequenceClip import ImageSequenceClip
except ImportError:
raise gym.error.DependencyNotInstalled(
"MoviePy is not installed, run `pip inst... | 108 | 4,191 |
gym | gym/utils/passive_env_checker.py | .py | """A set of functions for passively checking environment implementations."""
import inspect
from functools import partial
from typing import Callable
import numpy as np
from gym import Space, error, logger, spaces
def _check_box_observation_space(observation_space: spaces.Box):
"""Checks that a :class:`Box` obs... | 321 | 15,046 |
gym | gym/utils/step_api_compatibility.py | .py | """Contains methods for step compatibility, from old-to-new and new-to-old API."""
from typing import Tuple, Union
import numpy as np
from gym.core import ObsType
DoneStepType = Tuple[
Union[ObsType, np.ndarray],
Union[float, np.ndarray],
Union[bool, np.ndarray],
Union[dict, list],
]
TerminatedTrunc... | 162 | 6,522 |
gym | gym/envs/__init__.py | .py | from gym.envs.registration import load_env_plugins as _load_env_plugins
from gym.envs.registration import make, register, registry, spec
# Hook to load plugins from entry points
_load_env_plugins()
# Classic
# ----------------------------------------
register(
id="CartPole-v0",
entry_point="gym.envs.classic... | 321 | 6,961 |
gym | gym/envs/registration.py | .py | import contextlib
import copy
import difflib
import importlib
import importlib.util
import re
import sys
import warnings
from dataclasses import dataclass, field
from typing import (
Callable,
Dict,
List,
Optional,
Sequence,
SupportsFloat,
Tuple,
Union,
overload,
)
import numpy as n... | 704 | 26,208 |
gym | gym/envs/classic_control/continuous_mountain_car.py | .py | """
@author: Olivier Sigaud
A merge between two sources:
* Adaptation of the MountainCar Environment from the "FAReinforcement" library
of Jose Antonio Martin H. (version 1.0), adapted by 'Tom Schaul, tom@idsia.ch'
and then modified by Arnaud de Broissia
* the gym MountainCar environment
itself from
http://incomple... | 301 | 10,546 |
gym | gym/envs/classic_control/cartpole.py | .py | """
Classic cart-pole system implemented by Rich Sutton et al.
Copied from http://incompleteideas.net/sutton/book/code/pole.c
permalink: https://perma.cc/C9ZM-652R
"""
import math
from typing import Optional, Union
import numpy as np
import gym
from gym import logger, spaces
from gym.envs.classic_control import utils... | 313 | 11,579 |
gym | gym/envs/classic_control/acrobot.py | .py | """classic Acrobot task"""
from typing import Optional
import numpy as np
from numpy import cos, pi, sin
from gym import core, logger, spaces
from gym.error import DependencyNotInstalled
__copyright__ = "Copyright 2013, RLPy http://acl.mit.edu/RLPy"
__credits__ = [
"Alborz Geramifard",
"Robert H. Klein",
... | 466 | 16,814 |
gym | gym/envs/classic_control/utils.py | .py | """
Utility functions used for classic control environments.
"""
from typing import Optional, SupportsFloat, Tuple
def verify_number_and_cast(x: SupportsFloat) -> float:
"""Verify parameter is a single number and cast to a float."""
try:
x = float(x)
except (ValueError, TypeError):
raise ... | 47 | 1,415 |
gym | gym/envs/classic_control/mountain_car.py | .py | """
http://incompleteideas.net/MountainCar/MountainCar1.cp
permalink: https://perma.cc/6Z2N-PFWC
"""
import math
from typing import Optional
import numpy as np
import gym
from gym import spaces
from gym.envs.classic_control import utils
from gym.error import DependencyNotInstalled
class MountainCarEnv(gym.Env):
... | 283 | 9,826 |
gym | gym/envs/classic_control/pendulum.py | .py | __credits__ = ["Carlos Luis"]
from os import path
from typing import Optional
import numpy as np
import gym
from gym import spaces
from gym.envs.classic_control import utils
from gym.error import DependencyNotInstalled
DEFAULT_X = np.pi
DEFAULT_Y = 1.0
class PendulumEnv(gym.Env):
"""
### Description
... | 272 | 9,519 |
gym | gym/envs/toy_text/blackjack.py | .py | import os
from typing import Optional
import numpy as np
import gym
from gym import spaces
from gym.error import DependencyNotInstalled
def cmp(a, b):
return float(a > b) - float(a < b)
# 1 = Ace, 2-10 = Number cards, Jack/Queen/King = 10
deck = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 10]
def draw_card(np_r... | 319 | 10,806 |
gym | gym/envs/toy_text/utils.py | .py | import numpy as np
def categorical_sample(prob_n, np_random: np.random.Generator):
"""Sample from categorical distribution where each row specifies class probabilities."""
prob_n = np.asarray(prob_n)
csprob_n = np.cumsum(prob_n)
return np.argmax(csprob_n > np_random.random())
| 9 | 295 |
gym | gym/envs/toy_text/frozen_lake.py | .py | from contextlib import closing
from io import StringIO
from os import path
from typing import List, Optional
import numpy as np
from gym import Env, logger, spaces, utils
from gym.envs.toy_text.utils import categorical_sample
from gym.error import DependencyNotInstalled
LEFT = 0
DOWN = 1
RIGHT = 2
UP = 3
MAPS = {
... | 414 | 13,715 |
gym | gym/envs/toy_text/cliffwalking.py | .py | from contextlib import closing
from io import StringIO
from os import path
from typing import Optional
import numpy as np
from gym import Env, logger, spaces
from gym.envs.toy_text.utils import categorical_sample
from gym.error import DependencyNotInstalled
UP = 0
RIGHT = 1
DOWN = 2
LEFT = 3
class CliffWalkingEnv(... | 294 | 10,940 |
gym | gym/envs/toy_text/taxi.py | .py | from contextlib import closing
from io import StringIO
from os import path
from typing import Optional
import numpy as np
from gym import Env, logger, spaces, utils
from gym.envs.toy_text.utils import categorical_sample
from gym.error import DependencyNotInstalled
MAP = [
"+---------+",
"|R: | : :G|",
"|... | 473 | 18,318 |
gym | gym/envs/box2d/car_dynamics.py | .py | """
Top-down car dynamics simulation.
Some ideas are taken from this great tutorial http://www.iforce2d.net/b2dtut/top-down-car by Chris Campbell.
This simulation is a bit more detailed, with wheels rotation.
Created by Oleg Klimov
"""
import math
import Box2D
import numpy as np
from gym.error import DependencyNot... | 352 | 12,147 |
gym | gym/envs/box2d/bipedal_walker.py | .py | __credits__ = ["Andrea PIERRÉ"]
import math
from typing import TYPE_CHECKING, List, Optional
import numpy as np
import gym
from gym import error, spaces
from gym.error import DependencyNotInstalled
from gym.utils import EzPickle
try:
import Box2D
from Box2D.b2 import (
circleShape,
contactLi... | 858 | 31,175 |
gym | gym/envs/box2d/lunar_lander.py | .py | __credits__ = ["Andrea PIERRÉ"]
import math
import warnings
from typing import TYPE_CHECKING, Optional
import numpy as np
import gym
from gym import error, spaces
from gym.error import DependencyNotInstalled
from gym.utils import EzPickle, colorize
from gym.utils.step_api_compatibility import step_api_compatibility
... | 818 | 29,802 |
gym | gym/envs/box2d/car_racing.py | .py | __credits__ = ["Andrea PIERRÉ"]
import math
from typing import Optional, Union
import numpy as np
import gym
from gym import spaces
from gym.envs.box2d.car_dynamics import Car
from gym.error import DependencyNotInstalled, InvalidAction
from gym.utils import EzPickle
try:
import Box2D
from Box2D.b2 import co... | 829 | 28,932 |
gym | gym/envs/mujoco/mujoco_env.py | .py | from os import path
from typing import Optional, Union
import numpy as np
import gym
from gym import error, logger, spaces
from gym.spaces import Space
try:
import mujoco_py
except ImportError as e:
MUJOCO_PY_IMPORT_ERROR = e
else:
MUJOCO_PY_IMPORT_ERROR = None
try:
import mujoco
except ImportError ... | 438 | 14,450 |
gym | gym/envs/mujoco/ant.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class AntEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 20,
}
de... | 81 | 2,400 |
gym | gym/envs/mujoco/pusher_v4.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
class PusherEnv(MujocoEnv, utils.EzPickle):
"""
### Description
"Pusher" is a multi-jointed robot arm which is very similar to that of a human.
The goal is to move a target cylinder (called *obj... | 207 | 12,160 |
gym | gym/envs/mujoco/walker2d_v4.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
"distance": 4.0,
"lookat": np.array((0.0, 0.0, 1.15)),
"elevation": -20.0,
}
class Walker2dEnv(MujocoEnv, utils.EzPickle):
"""
### Description... | 297 | 16,500 |
gym | gym/envs/mujoco/inverted_pendulum_v4.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
class InvertedPendulumEnv(MujocoEnv, utils.EzPickle):
"""
### Description
This environment is the cartpole environment based on the work done by
Barto, Sutton, and Anderson in ["Neuronlike adapt... | 133 | 5,736 |
gym | gym/envs/mujoco/swimmer_v3.py | .py | __credits__ = ["Rushiv Arora"]
import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {}
class SwimmerEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"... | 129 | 3,877 |
gym | gym/envs/mujoco/half_cheetah_v4.py | .py | __credits__ = ["Rushiv Arora"]
import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"distance": 4.0,
}
class HalfCheetahEnv(MujocoEnv, utils.EzPickle):
"""
### Description
This environment is based on the work by P. Waw... | 246 | 13,252 |
gym | gym/envs/mujoco/hopper_v3.py | .py | __credits__ = ["Rushiv Arora"]
import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
"distance": 3.0,
"lookat": np.array((0.0, 0.0, 1.15)),
"elevation": -20.0,
}
class HopperEnv(MuJocoPyEnv, utils.EzPi... | 178 | 5,316 |
gym | gym/envs/mujoco/inverted_double_pendulum_v4.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
class InvertedDoublePendulumEnv(MujocoEnv, utils.EzPickle):
"""
### Description
This environment originates from control theory and builds on the cartpole
environment based on the work done by B... | 174 | 9,332 |
gym | gym/envs/mujoco/half_cheetah.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class HalfCheetahEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 20,
}... | 65 | 1,840 |
gym | gym/envs/mujoco/reacher_v4.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
class ReacherEnv(MujocoEnv, utils.EzPickle):
"""
### Description
"Reacher" is a two-jointed robot arm. The goal is to move the robot's end effector (called *fingertip*) close to a
target that is ... | 188 | 10,039 |
gym | gym/envs/mujoco/humanoid_v3.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 1,
"distance": 4.0,
"lookat": np.array((0.0, 0.0, 2.0)),
"elevation": -20.0,
}
def mass_center(model, sim):
mass = np.expand_dims(model.body_mass, ... | 200 | 6,299 |
gym | gym/envs/mujoco/humanoidstandup.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class HumanoidStandupEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 67,
... | 88 | 2,449 |
gym | gym/envs/mujoco/half_cheetah_v3.py | .py | __credits__ = ["Rushiv Arora"]
import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"distance": 4.0,
}
class HalfCheetahEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
... | 128 | 3,669 |
gym | gym/envs/mujoco/hopper.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class HopperEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 125,
}
... | 68 | 2,026 |
gym | gym/envs/mujoco/walker2d_v3.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
"distance": 4.0,
"lookat": np.array((0.0, 0.0, 1.15)),
"elevation": -20.0,
}
class Walker2dEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
... | 168 | 4,942 |
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