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 |
|---|---|---|---|---|---|
gym | gym/envs/mujoco/humanoid.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
def mass_center(model, sim):
mass = np.expand_dims(model.body_mass, 1)
xpos = sim.data.xipos
return (np.sum(mass * xpos, 0) / np.sum(mass))[0]
class HumanoidEnv(MuJocoPyEnv, utils.EzPickle):
... | 95 | 2,800 |
gym | gym/envs/mujoco/swimmer.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class SwimmerEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 25,
}
... | 60 | 1,676 |
gym | gym/envs/mujoco/pusher.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class PusherEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 20,
}
... | 85 | 2,504 |
gym | gym/envs/mujoco/humanoid_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": 1,
"distance": 4.0,
"lookat": np.array((0.0, 0.0, 2.0)),
"elevation": -20.0,
}
def mass_center(model, data):
mass = np.expand_dims(model.body_mass, a... | 375 | 27,951 |
gym | gym/envs/mujoco/hopper_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": 3.0,
"lookat": np.array((0.0, 0.0, 1.15)),
"elevation": -20.0,
}
class HopperEnv(MujocoEnv, utils.EzPickle):
"""
### Description
... | 299 | 16,025 |
gym | gym/envs/mujoco/walker2d.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class Walker2dEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 125,
}
... | 62 | 1,897 |
gym | gym/envs/mujoco/inverted_double_pendulum.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class InvertedDoublePendulumEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps"... | 70 | 2,125 |
gym | gym/envs/mujoco/ant_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 = {
"distance": 4.0,
}
class AntEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
... | 187 | 5,705 |
gym | gym/envs/mujoco/reacher.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class ReacherEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 50,
}
... | 76 | 2,190 |
gym | gym/envs/mujoco/humanoidstandup_v4.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MujocoEnv
from gym.spaces import Box
class HumanoidStandupEnv(MujocoEnv, utils.EzPickle):
"""
### Description
This environment is based on the environment introduced by Tassa, Erez and Todorov
in ["Synthesis and stabilization of co... | 260 | 21,674 |
gym | gym/envs/mujoco/inverted_pendulum.py | .py | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class InvertedPendulumEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 25,
... | 57 | 1,596 |
gym | gym/envs/mujoco/mujoco_rendering.py | .py | import collections
import os
import time
from threading import Lock
import glfw
import imageio
import mujoco
import numpy as np
def _import_egl(width, height):
from mujoco.egl import GLContext
return GLContext(width, height)
def _import_glfw(width, height):
from mujoco.glfw import GLContext
retur... | 553 | 19,629 |
gym | gym/envs/mujoco/ant_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 = {
"distance": 4.0,
}
class AntEnv(MujocoEnv, utils.EzPickle):
"""
### Description
This environment is based on the environment introduced by Schulman,
Moritz, Levine... | 357 | 19,981 |
gym | gym/envs/mujoco/swimmer_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 = {}
class SwimmerEnv(MujocoEnv, utils.EzPickle):
"""
### Description
This environment corresponds to the Swimmer environment described in Rémi... | 240 | 11,896 |
gym | tests/test_core.py | .py | from typing import Optional
import numpy as np
import pytest
from gym import core, spaces
from gym.wrappers import OrderEnforcing, TimeLimit
class ArgumentEnv(core.Env):
observation_space = spaces.Box(low=0, high=1, shape=(1,))
action_space = spaces.Box(low=0, high=1, shape=(1,))
calls = 0
def __in... | 140 | 4,240 |
gym | tests/testing_env.py | .py | """Provides a generic testing environment for use in tests with custom reset, step and render functions."""
import types
from typing import Any, Dict, Optional, Tuple, Union
import gym
from gym import spaces
from gym.core import ActType, ObsType
from gym.envs.registration import EnvSpec
def basic_reset_fn(
self,... | 83 | 3,161 |
gym | tests/wrappers/test_autoreset.py | .py | """Tests the gym.wrapper.AutoResetWrapper operates as expected."""
from typing import Generator, Optional
from unittest.mock import MagicMock
import numpy as np
import pytest
import gym
from gym.wrappers import AutoResetWrapper
from tests.envs.utils import all_testing_env_specs
class DummyResetEnv(gym.Env):
"""... | 137 | 4,731 |
gym | tests/wrappers/test_transform_reward.py | .py | import numpy as np
import pytest
import gym
from gym.wrappers import TransformReward
@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
def test_transform_reward(env_id):
# use case #1: scale
scales = [0.1, 200]
for scale in scales:
env = gym.make(env_id, disable_env_checker=True)... | 63 | 1,834 |
gym | tests/wrappers/utils.py | .py | import gym
def has_wrapper(wrapped_env: gym.Env, wrapper_type: type) -> bool:
while isinstance(wrapped_env, gym.Wrapper):
if isinstance(wrapped_env, wrapper_type):
return True
wrapped_env = wrapped_env.env
return False
| 10 | 257 |
gym | tests/wrappers/test_clip_action.py | .py | import numpy as np
import gym
from gym.wrappers import ClipAction
def test_clip_action():
# mountaincar: action-based rewards
env = gym.make("MountainCarContinuous-v0", disable_env_checker=True)
wrapped_env = ClipAction(
gym.make("MountainCarContinuous-v0", disable_env_checker=True)
)
se... | 29 | 790 |
gym | tests/wrappers/test_video_recorder.py | .py | import gc
import os
import re
import time
import pytest
import gym
from gym.wrappers.monitoring.video_recorder import VideoRecorder
class BrokenRecordableEnv(gym.Env):
metadata = {"render_modes": ["rgb_array_list"]}
def __init__(self, render_mode="rgb_array_list"):
self.render_mode = render_mode
... | 120 | 2,910 |
gym | tests/wrappers/test_gray_scale_observation.py | .py | import pytest
import gym
from gym import spaces
from gym.wrappers import GrayScaleObservation
@pytest.mark.parametrize("env_id", ["CarRacing-v2"])
@pytest.mark.parametrize("keep_dim", [True, False])
def test_gray_scale_observation(env_id, keep_dim):
rgb_env = gym.make(env_id, disable_env_checker=True)
asser... | 27 | 920 |
gym | tests/wrappers/test_record_episode_statistics.py | .py | import numpy as np
import pytest
import gym
from gym.wrappers import RecordEpisodeStatistics, VectorListInfo
from gym.wrappers.record_episode_statistics import add_vector_episode_statistics
@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
@pytest.mark.parametrize("deque_size", [2, 5])
def test_reco... | 103 | 3,578 |
gym | tests/wrappers/test_time_limit.py | .py | import pytest
import gym
from gym.envs.classic_control.pendulum import PendulumEnv
from gym.wrappers import TimeLimit
def test_time_limit_reset_info():
env = gym.make("CartPole-v1", disable_env_checker=True)
env = TimeLimit(env)
ob_space = env.observation_space
obs, info = env.reset()
assert ob_s... | 58 | 1,703 |
gym | tests/wrappers/test_order_enforcing.py | .py | import pytest
import gym
from gym.envs.classic_control import CartPoleEnv
from gym.error import ResetNeeded
from gym.wrappers import OrderEnforcing
from tests.envs.utils import all_testing_env_specs
from tests.wrappers.utils import has_wrapper
@pytest.mark.parametrize(
"spec", all_testing_env_specs, ids=[spec.id... | 46 | 1,786 |
gym | tests/wrappers/test_pixel_observation.py | .py | """Tests for the pixel observation wrapper."""
from typing import Optional
import numpy as np
import pytest
import gym
from gym import spaces
from gym.wrappers.pixel_observation import STATE_KEY, PixelObservationWrapper
class FakeEnvironment(gym.Env):
def __init__(self, render_mode="single_rgb_array"):
... | 126 | 4,188 |
gym | tests/wrappers/test_flatten.py | .py | """Tests for the flatten observation wrapper."""
from collections import OrderedDict
from typing import Optional
import numpy as np
import pytest
import gym
from gym.spaces import Box, Dict, flatten, unflatten
from gym.wrappers import FlattenObservation
class FakeEnvironment(gym.Env):
def __init__(self, observ... | 99 | 3,314 |
gym | tests/wrappers/test_time_aware_observation.py | .py | import pytest
import gym
from gym import spaces
from gym.wrappers import TimeAwareObservation
@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
def test_time_aware_observation(env_id):
env = gym.make(env_id, disable_env_checker=True)
wrapped_env = TimeAwareObservation(env)
assert isinst... | 37 | 1,277 |
gym | tests/wrappers/test_record_video.py | .py | import os
import shutil
import gym
from gym.wrappers import capped_cubic_video_schedule
def test_record_video_using_default_trigger():
env = gym.make(
"CartPole-v1", render_mode="rgb_array_list", disable_env_checker=True
)
env = gym.wrappers.RecordVideo(env, "videos")
env.reset()
for _ in... | 87 | 2,831 |
gym | tests/wrappers/test_atari_preprocessing.py | .py | import numpy as np
import pytest
from gym.spaces import Box, Discrete
from gym.wrappers import AtariPreprocessing, StepAPICompatibility
from tests.testing_env import GenericTestEnv, old_step_fn
class AleTesting:
"""A testing implementation for the ALE object in atari games."""
grayscale_obs_space = Box(low=... | 127 | 4,102 |
gym | tests/wrappers/test_flatten_observation.py | .py | import numpy as np
import pytest
import gym
from gym import spaces
from gym.wrappers import FlattenObservation
@pytest.mark.parametrize("env_id", ["Blackjack-v1"])
def test_flatten_observation(env_id):
env = gym.make(env_id, disable_env_checker=True)
wrapped_env = FlattenObservation(env)
obs, info = env... | 24 | 702 |
gym | tests/wrappers/test_frame_stack.py | .py | import numpy as np
import pytest
import gym
from gym.wrappers import FrameStack
try:
import lz4
except ImportError:
lz4 = None
@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1", "CarRacing-v2"])
@pytest.mark.parametrize("num_stack", [2, 3, 4])
@pytest.mark.parametrize(
"lz4_compress",
... | 53 | 1,457 |
gym | tests/wrappers/test_human_rendering.py | .py | import re
import pytest
import gym
from gym.wrappers import HumanRendering
def test_human_rendering():
for mode in ["rgb_array", "rgb_array_list"]:
env = HumanRendering(
gym.make("CartPole-v1", render_mode=mode, disable_env_checker=True)
)
assert env.render_mode == "human"
... | 33 | 828 |
gym | tests/wrappers/test_rescale_action.py | .py | import numpy as np
import pytest
import gym
from gym.wrappers import RescaleAction
def test_rescale_action():
env = gym.make("CartPole-v1", disable_env_checker=True)
with pytest.raises(AssertionError):
env = RescaleAction(env, -1, 1)
del env
env = gym.make("Pendulum-v1", disable_env_checker=... | 32 | 861 |
gym | tests/wrappers/test_vector_list_info.py | .py | import pytest
import gym
from gym.wrappers import RecordEpisodeStatistics, VectorListInfo
ENV_ID = "CartPole-v1"
NUM_ENVS = 3
ENV_STEPS = 50
SEED = 42
def test_usage_in_vector_env():
env = gym.make(ENV_ID, disable_env_checker=True)
vector_env = gym.vector.make(ENV_ID, num_envs=NUM_ENVS, disable_env_checker=... | 59 | 2,090 |
gym | tests/wrappers/test_filter_observation.py | .py | from typing import Optional, Tuple
import numpy as np
import pytest
import gym
from gym import spaces
from gym.wrappers.filter_observation import FilterObservation
class FakeEnvironment(gym.Env):
def __init__(
self, render_mode=None, observation_keys: Tuple[str, ...] = ("state",)
):
self.obs... | 88 | 2,972 |
gym | tests/wrappers/test_transform_observation.py | .py | import numpy as np
import pytest
import gym
from gym.wrappers import TransformObservation
@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
def test_transform_observation(env_id):
def affine_transform(x):
return 3 * x + 2
env = gym.make(env_id, disable_env_checker=True)
wrapped_... | 36 | 1,085 |
gym | tests/wrappers/test_resize_observation.py | .py | import pytest
import gym
from gym import spaces
from gym.wrappers import ResizeObservation
@pytest.mark.parametrize("env_id", ["CarRacing-v2"])
@pytest.mark.parametrize("shape", [16, 32, (8, 5), [10, 7]])
def test_resize_observation(env_id, shape):
env = gym.make(env_id, disable_env_checker=True)
env = Resiz... | 23 | 739 |
gym | tests/wrappers/test_passive_env_checker.py | .py | import re
import warnings
import numpy as np
import pytest
import gym
from gym.wrappers.env_checker import PassiveEnvChecker
from tests.envs.test_envs import PASSIVE_CHECK_IGNORE_WARNING
from tests.envs.utils import all_testing_initialised_envs
from tests.testing_env import GenericTestEnv
@pytest.mark.parametrize(
... | 104 | 3,060 |
gym | tests/wrappers/test_normalize.py | .py | from typing import Optional
import numpy as np
from numpy.testing import assert_almost_equal
import gym
from gym.wrappers.normalize import NormalizeObservation, NormalizeReward
class DummyRewardEnv(gym.Env):
metadata = {}
def __init__(self, return_reward_idx=0):
self.action_space = gym.spaces.Discr... | 126 | 3,760 |
gym | tests/wrappers/test_step_compatibility.py | .py | import pytest
import gym
from gym.spaces import Discrete
from gym.wrappers import StepAPICompatibility
class OldStepEnv(gym.Env):
def __init__(self):
self.action_space = Discrete(2)
self.observation_space = Discrete(2)
def step(self, action):
obs = self.observation_space.sample()
... | 83 | 2,458 |
gym | tests/wrappers/test_nested_dict.py | .py | """Tests for the filter observation wrapper."""
from typing import Optional
import numpy as np
import pytest
import gym
from gym.spaces import Box, Dict, Tuple
from gym.wrappers import FilterObservation, FlattenObservation
class FakeEnvironment(gym.Env):
def __init__(self, observation_space, render_mode=None):
... | 121 | 4,067 |
gym | tests/vector/test_numpy_utils.py | .py | from collections import OrderedDict
import numpy as np
import pytest
from gym.spaces import Dict, Tuple
from gym.vector.utils.numpy_utils import concatenate, create_empty_array
from gym.vector.utils.spaces import BaseGymSpaces
from tests.vector.utils import spaces
@pytest.mark.parametrize(
"space", spaces, ids=... | 143 | 5,025 |
gym | tests/vector/utils.py | .py | import time
from typing import Optional
import numpy as np
import gym
from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Tuple
from gym.utils.seeding import RandomNumberGenerator
spaces = [
Box(low=np.array(-1.0), high=np.array(1.0), dtype=np.float64),
Box(low=np.array([0.0]), high=np.ar... | 140 | 3,834 |
gym | tests/vector/test_vector_env_info.py | .py | import numpy as np
import pytest
import gym
from gym.vector.sync_vector_env import SyncVectorEnv
from tests.vector.utils import make_env
ENV_ID = "CartPole-v1"
NUM_ENVS = 3
ENV_STEPS = 50
SEED = 42
@pytest.mark.parametrize("asynchronous", [True, False])
def test_vector_env_info(asynchronous):
env = gym.vector.m... | 57 | 2,180 |
gym | tests/vector/test_async_vector_env.py | .py | import re
from multiprocessing import TimeoutError
import numpy as np
import pytest
from gym.error import AlreadyPendingCallError, ClosedEnvironmentError, NoAsyncCallError
from gym.spaces import Box, Discrete, MultiDiscrete, Tuple
from gym.vector.async_vector_env import AsyncVectorEnv
from tests.vector.utils import (... | 309 | 10,139 |
gym | tests/vector/test_shared_memory.py | .py | import multiprocessing as mp
from collections import OrderedDict
from multiprocessing import Array, Process
from multiprocessing.sharedctypes import SynchronizedArray
import numpy as np
import pytest
from gym.error import CustomSpaceError
from gym.spaces import Dict, Tuple
from gym.vector.utils.shared_memory import (... | 178 | 5,713 |
gym | tests/vector/test_vector_env.py | .py | from functools import partial
import numpy as np
import pytest
from gym.spaces import Discrete, Tuple
from gym.vector.async_vector_env import AsyncVectorEnv
from gym.vector.sync_vector_env import SyncVectorEnv
from gym.vector.vector_env import VectorEnv
from tests.testing_env import GenericTestEnv
from tests.vector.u... | 126 | 4,274 |
gym | tests/vector/test_spaces.py | .py | import copy
import numpy as np
import pytest
from numpy.testing import assert_array_equal
from gym.spaces import Box, Dict, MultiDiscrete, Space, Tuple
from gym.vector.utils.spaces import batch_space, iterate
from tests.vector.utils import CustomSpace, assert_rng_equal, custom_spaces, spaces
expected_batch_spaces_4 ... | 200 | 6,908 |
gym | tests/vector/test_sync_vector_env.py | .py | import numpy as np
import pytest
from gym.envs.registration import EnvSpec
from gym.spaces import Box, Discrete, MultiDiscrete, Tuple
from gym.vector.sync_vector_env import SyncVectorEnv
from tests.envs.utils import all_testing_env_specs
from tests.vector.utils import (
CustomSpace,
assert_rng_equal,
make_... | 178 | 5,756 |
gym | tests/vector/test_vector_env_wrapper.py | .py | import numpy as np
from gym.vector import VectorEnvWrapper, make
class DummyWrapper(VectorEnvWrapper):
def __init__(self, env):
self.env = env
self.counter = 0
def reset_async(self, **kwargs):
super().reset_async()
self.counter += 1
def test_vector_env_wrapper_inheritance()... | 32 | 972 |
gym | tests/vector/test_vector_make.py | .py | import pytest
import gym
from gym.vector import AsyncVectorEnv, SyncVectorEnv
from gym.wrappers import OrderEnforcing, TimeLimit, TransformObservation
from gym.wrappers.env_checker import PassiveEnvChecker
from tests.wrappers.utils import has_wrapper
def test_vector_make_id():
env = gym.vector.make("CartPole-v1"... | 85 | 2,726 |
gym | tests/spaces/utils.py | .py | from typing import List
import numpy as np
from gym.spaces import (
Box,
Dict,
Discrete,
Graph,
MultiBinary,
MultiDiscrete,
Sequence,
Space,
Text,
Tuple,
)
TESTING_FUNDAMENTAL_SPACES = [
Discrete(3),
Discrete(3, start=-1),
Box(low=0.0, high=1.0),
Box(low=0.0, h... | 104 | 3,047 |
gym | tests/spaces/test_space.py | .py | from functools import partial
import pytest
from gym import Space
from gym.spaces import utils
TESTING_SPACE = Space()
@pytest.mark.parametrize(
"func",
[
TESTING_SPACE.sample,
partial(TESTING_SPACE.contains, None),
partial(utils.flatdim, TESTING_SPACE),
partial(utils.flatte... | 25 | 561 |
gym | tests/spaces/test_graph.py | .py | import re
import numpy as np
import pytest
from gym.spaces import Discrete, Graph, GraphInstance
def test_node_space_sample():
space = Graph(node_space=Discrete(3), edge_space=None)
space.seed(0)
sample = space.sample(
mask=(tuple(np.array([0, 1, 0], dtype=np.int8) for _ in range(5)), None),
... | 138 | 4,111 |
gym | tests/spaces/test_sequence.py | .py | import re
import numpy as np
import pytest
import gym.spaces
def test_sample():
"""Tests the sequence sampling works as expects and the errors are correctly raised."""
space = gym.spaces.Sequence(gym.spaces.Box(0, 1))
# Test integer mask length
for length in range(4):
sample = space.sample(... | 60 | 1,673 |
gym | tests/spaces/test_multibinary.py | .py | import numpy as np
from gym.spaces import MultiBinary
def test_sample():
space = MultiBinary(4)
sample = space.sample(mask=np.array([0, 0, 1, 1], dtype=np.int8))
assert np.all(sample == [0, 0, 1, 1])
sample = space.sample(mask=np.array([0, 1, 2, 2], dtype=np.int8))
assert sample[0] == 0 and sam... | 20 | 603 |
gym | tests/spaces/test_dict.py | .py | from collections import OrderedDict
import numpy as np
import pytest
from gym.spaces import Box, Dict, Discrete
def test_dict_init():
with pytest.raises(
AssertionError,
match=r"^Unexpected Dict space input, expecting dict, OrderedDict or Sequence, actual type: ",
):
Dict(Discrete(2)... | 141 | 4,135 |
gym | tests/spaces/test_box.py | .py | import re
import warnings
import numpy as np
import pytest
import gym.error
from gym.spaces import Box
from gym.spaces.box import get_inf
@pytest.mark.parametrize(
"box,expected_shape",
[
( # Test with same 1-dim low and high shape
Box(low=np.zeros(2), high=np.ones(2), dtype=np.int32),
... | 317 | 10,945 |
gym | tests/spaces/test_spaces.py | .py | import copy
import itertools
import json # note: ujson fails this test due to float equality
import pickle
import tempfile
from typing import List, Union
import numpy as np
import pytest
from gym.spaces import Box, Discrete, MultiBinary, MultiDiscrete, Space, Text
from gym.utils import seeding
from gym.utils.env_che... | 481 | 18,219 |
gym | tests/spaces/test_discrete.py | .py | import numpy as np
from gym.spaces import Discrete
def test_space_legacy_pickling():
"""Test the legacy pickle of Discrete that is missing the `start` parameter."""
legacy_state = {
"shape": (
1,
2,
3,
),
"dtype": np.int64,
"np_random": np.r... | 41 | 1,167 |
gym | tests/spaces/test_utils.py | .py | from itertools import zip_longest
from typing import Optional
import numpy as np
import pytest
import gym
from gym.spaces import Box, Graph, utils
from gym.utils.env_checker import data_equivalence
from tests.spaces.utils import TESTING_SPACES, TESTING_SPACES_IDS
TESTING_SPACES_EXPECTED_FLATDIMS = [
# Discrete
... | 136 | 3,718 |
gym | tests/spaces/test_multidiscrete.py | .py | import pytest
from gym.spaces import Discrete, MultiDiscrete
from gym.utils.env_checker import data_equivalence
def test_multidiscrete_as_tuple():
# 1D multi-discrete
space = MultiDiscrete([3, 4, 5])
assert space.shape == (3,)
assert space[0] == Discrete(3)
assert space[0:1] == MultiDiscrete([3]... | 67 | 2,507 |
gym | tests/spaces/test_tuple.py | .py | import numpy as np
import pytest
import gym.spaces
from gym.spaces import Box, Dict, Discrete, MultiBinary, Tuple
from gym.utils.env_checker import data_equivalence
def test_sequence_inheritance():
"""The gym Tuple space inherits from abc.Sequences, this test checks all functions work"""
spaces = [Discrete(5... | 110 | 3,035 |
gym | tests/spaces/test_text.py | .py | import re
import numpy as np
import pytest
from gym.spaces import Text
def test_sample_mask():
space = Text(min_length=1, max_length=5)
# Test the sample length
sample = space.sample(mask=(3, None))
assert sample in space
assert len(sample) == 3
sample = space.sample(mask=None)
assert ... | 42 | 1,091 |
gym | tests/utils/test_env_checker.py | .py | """Tests that the `env_checker` runs as expects and all errors are possible."""
import re
import warnings
from typing import Tuple, Union
import numpy as np
import pytest
import gym
from gym import spaces
from gym.core import ObsType
from gym.utils.env_checker import (
check_env,
check_reset_options,
chec... | 263 | 9,325 |
gym | tests/utils/test_play.py | .py | from functools import partial
from itertools import product
from typing import Callable
import numpy as np
import pygame
import pytest
from pygame import KEYDOWN, KEYUP, QUIT, event
from pygame.event import Event
import gym
from gym.utils.play import MissingKeysToAction, PlayableGame, play
from tests.testing_env impo... | 210 | 6,763 |
gym | tests/utils/test_save_video.py | .py | import os
import shutil
import numpy as np
import gym
from gym.utils.save_video import capped_cubic_video_schedule, save_video
def test_record_video_using_default_trigger():
env = gym.make(
"CartPole-v1", render_mode="rgb_array_list", disable_env_checker=True
)
env.reset()
step_starting_ind... | 118 | 3,573 |
gym | tests/utils/test_seeding.py | .py | import pickle
from gym import error
from gym.utils import seeding
def test_invalid_seeds():
for seed in [-1, "test"]:
try:
seeding.np_random(seed)
except error.Error:
pass
else:
assert False, f"Invalid seed {seed} passed validation"
def test_valid_see... | 31 | 721 |
gym | tests/utils/test_step_api_compatibility.py | .py | import numpy as np
import pytest
from gym.utils.env_checker import data_equivalence
from gym.utils.step_api_compatibility import (
convert_to_done_step_api,
convert_to_terminated_truncated_step_api,
)
@pytest.mark.parametrize(
"is_vector_env, done_returns, expected_terminated, expected_truncated",
(
... | 170 | 6,019 |
gym | tests/utils/test_passive_env_checker.py | .py | import re
import warnings
from typing import Dict, Union
import numpy as np
import pytest
import gym
from gym import spaces
from gym.utils.passive_env_checker import (
check_action_space,
check_obs,
check_observation_space,
env_render_passive_checker,
env_reset_passive_checker,
env_step_passiv... | 459 | 17,819 |
gym | tests/envs/test_envs.py | .py | import pickle
import warnings
import numpy as np
import pytest
import gym
from gym.envs.registration import EnvSpec
from gym.logger import warn
from gym.utils.env_checker import check_env, data_equivalence
from tests.envs.utils import (
all_testing_env_specs,
all_testing_initialised_envs,
assert_equals,
)... | 201 | 7,474 |
gym | tests/envs/utils.py | .py | """Finds all the specs that we can test with"""
from typing import List, Optional
import numpy as np
import gym
from gym import error, logger
from gym.envs.registration import EnvSpec
def try_make_env(env_spec: EnvSpec) -> Optional[gym.Env]:
"""Tries to make the environment showing if it is possible.
Warni... | 89 | 2,770 |
gym | tests/envs/test_env_implementation.py | .py | from typing import Optional
import numpy as np
import pytest
import gym
from gym.envs.box2d import BipedalWalker
from gym.envs.box2d.lunar_lander import demo_heuristic_lander
from gym.envs.toy_text import TaxiEnv
from gym.envs.toy_text.frozen_lake import generate_random_map
def test_lunar_lander_heuristics():
"... | 216 | 7,592 |
gym | tests/envs/test_compatibility.py | .py | import sys
from typing import Any, Dict, Optional, Tuple
import numpy as np
import gym
from gym.spaces import Discrete
from gym.wrappers.compatibility import EnvCompatibility, LegacyEnv
class LegacyEnvExplicit(LegacyEnv, gym.Env):
"""Legacy env that explicitly implements the old API."""
observation_space =... | 131 | 3,885 |
gym | tests/envs/utils_envs.py | .py | import gym
class RegisterDuringMakeEnv(gym.Env):
"""Used in `test_registration.py` to check if `env.make` can import and register an env"""
def __init__(self):
self.action_space = gym.spaces.Discrete(1)
self.observation_space = gym.spaces.Discrete(1)
class ArgumentEnv(gym.Env):
observat... | 50 | 1,382 |
gym | tests/envs/test_action_dim_check.py | .py | import numpy as np
import pytest
import gym
from gym import spaces
from gym.envs.registration import EnvSpec
from tests.envs.utils import all_testing_initialised_envs, mujoco_testing_env_specs
@pytest.mark.parametrize(
"env_spec",
mujoco_testing_env_specs,
ids=[env_spec.id for env_spec in mujoco_testing_... | 137 | 4,045 |
gym | tests/envs/test_register.py | .py | """Tests that `gym.register` works as expected."""
import re
from typing import Optional
import pytest
import gym
@pytest.fixture(scope="function")
def register_testing_envs():
"""Registers testing environments."""
namespace = "MyAwesomeNamespace"
versioned_name = "MyAwesomeVersionedEnv"
unversioned... | 199 | 6,631 |
gym | tests/envs/test_make.py | .py | """Tests that gym.make works as expected."""
import re
import warnings
from copy import deepcopy
import numpy as np
import pytest
import gym
from gym.envs.classic_control import cartpole
from gym.wrappers import AutoResetWrapper, HumanRendering, OrderEnforcing, TimeLimit
from gym.wrappers.env_checker import PassiveE... | 311 | 10,418 |
gym | tests/envs/test_spec.py | .py | """Tests that gym.spec works as expected."""
import re
import pytest
import gym
def test_spec():
spec = gym.spec("CartPole-v1")
assert spec.id == "CartPole-v1"
assert spec is gym.envs.registry["CartPole-v1"]
def test_spec_kwargs():
map_name_value = "8x8"
env = gym.make("FrozenLake-v1", map_na... | 93 | 2,694 |
gym | tests/envs/test_mujoco.py | .py | import numpy as np
import pytest
import gym
from gym import envs
from gym.envs.registration import EnvSpec
from tests.envs.utils import mujoco_testing_env_specs
EPS = 1e-6
def verify_environments_match(
old_env_id: str, new_env_id: str, seed: int = 1, num_actions: int = 1000
):
"""Verifies with two environm... | 123 | 4,833 |
OpenVoice | setup.py | .py | from setuptools import setup, find_packages
setup(name='MyShell-OpenVoice',
version='0.0.0',
description='Instant voice cloning by MyShell.',
long_description=open('README.md').read().strip(),
long_description_content_type='text/markdown',
keywords=[
'text-to-speech',
... | 46 | 1,481 |
OpenVoice | openvoice/se_extractor.py | .py | import os
import glob
import torch
import hashlib
import librosa
import base64
from glob import glob
import numpy as np
from pydub import AudioSegment
from faster_whisper import WhisperModel
import hashlib
import base64
import librosa
from whisper_timestamped.transcribe import get_audio_tensor, get_vad_segments
model_... | 154 | 5,145 |
OpenVoice | openvoice/commons.py | .py | import math
import torch
from torch.nn import functional as F
def init_weights(m, mean=0.0, std=0.01):
classname = m.__class__.__name__
if classname.find("Conv") != -1:
m.weight.data.normal_(mean, std)
def get_padding(kernel_size, dilation=1):
return int((kernel_size * dilation - dilation) / 2)
... | 161 | 4,956 |
OpenVoice | openvoice/utils.py | .py | import re
import json
import numpy as np
def get_hparams_from_file(config_path):
with open(config_path, "r", encoding="utf-8") as f:
data = f.read()
config = json.loads(data)
hparams = HParams(**config)
return hparams
class HParams:
def __init__(self, **kwargs):
for k, v in kwarg... | 194 | 5,776 |
OpenVoice | openvoice/models.py | .py | import math
import torch
from torch import nn
from torch.nn import functional as F
from openvoice import commons
from openvoice import modules
from openvoice import attentions
from torch.nn import Conv1d, ConvTranspose1d, Conv2d
from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
from openvoice... | 500 | 16,801 |
OpenVoice | openvoice/attentions.py | .py | import math
import torch
from torch import nn
from torch.nn import functional as F
from openvoice import commons
import logging
logger = logging.getLogger(__name__)
class LayerNorm(nn.Module):
def __init__(self, channels, eps=1e-5):
super().__init__()
self.channels = channels
self.eps = ... | 466 | 16,360 |
OpenVoice | openvoice/mel_processing.py | .py | import torch
import torch.utils.data
from librosa.filters import mel as librosa_mel_fn
MAX_WAV_VALUE = 32768.0
def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
"""
PARAMS
------
C: compression factor
"""
return torch.log(torch.clamp(x, min=clip_val) * C)
def dynamic_range_decompr... | 183 | 6,098 |
OpenVoice | openvoice/modules.py | .py | import math
import torch
from torch import nn
from torch.nn import functional as F
from torch.nn import Conv1d
from torch.nn.utils import weight_norm, remove_weight_norm
from openvoice import commons
from openvoice.commons import init_weights, get_padding
from openvoice.transforms import piecewise_rational_quadratic_... | 599 | 19,010 |
OpenVoice | openvoice/transforms.py | .py | import torch
from torch.nn import functional as F
import numpy as np
DEFAULT_MIN_BIN_WIDTH = 1e-3
DEFAULT_MIN_BIN_HEIGHT = 1e-3
DEFAULT_MIN_DERIVATIVE = 1e-3
def piecewise_rational_quadratic_transform(
inputs,
unnormalized_widths,
unnormalized_heights,
unnormalized_derivatives,
inverse=False,
... | 210 | 7,253 |
OpenVoice | openvoice/openvoice_app.py | .py | import os
import torch
import argparse
import gradio as gr
from zipfile import ZipFile
import langid
from openvoice import se_extractor
from openvoice.api import BaseSpeakerTTS, ToneColorConverter
parser = argparse.ArgumentParser()
parser.add_argument("--share", action='store_true', default=False, help="make link publ... | 276 | 11,625 |
OpenVoice | openvoice/api.py | .py | import torch
import numpy as np
import re
import soundfile
from openvoice import utils
from openvoice import commons
import os
import librosa
from openvoice.text import text_to_sequence
from openvoice.mel_processing import spectrogram_torch
from openvoice.models import SynthesizerTrn
class OpenVoiceBaseClass(object):... | 203 | 7,823 |
OpenVoice | openvoice/text/mandarin.py | .py | import os
import sys
import re
from pypinyin import lazy_pinyin, BOPOMOFO
import jieba
import cn2an
import logging
# List of (Latin alphabet, bopomofo) pairs:
_latin_to_bopomofo = [(re.compile('%s' % x[0], re.IGNORECASE), x[1]) for x in [
('a', 'ㄟˉ'),
('b', 'ㄅㄧˋ'),
('c', 'ㄙㄧˉ'),
('d', 'ㄉㄧˋ'),
('e'... | 327 | 7,717 |
OpenVoice | openvoice/text/cleaners.py | .py | import re
from openvoice.text.english import english_to_lazy_ipa, english_to_ipa2, english_to_lazy_ipa2
from openvoice.text.mandarin import number_to_chinese, chinese_to_bopomofo, latin_to_bopomofo, chinese_to_romaji, chinese_to_lazy_ipa, chinese_to_ipa, chinese_to_ipa2
def cjke_cleaners2(text):
text = re.sub(r'\[... | 16 | 846 |
OpenVoice | openvoice/text/symbols.py | .py | '''
Defines the set of symbols used in text input to the model.
'''
# japanese_cleaners
# _pad = '_'
# _punctuation = ',.!?-'
# _letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
'''# japanese_cleaners2
_pad = '_'
_punctuation = ',.!?-~…'
_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
'''
'''# korean_... | 88 | 2,588 |
OpenVoice | openvoice/text/__init__.py | .py | """ from https://github.com/keithito/tacotron """
from openvoice.text import cleaners
from openvoice.text.symbols import symbols
# Mappings from symbol to numeric ID and vice versa:
_symbol_to_id = {s: i for i, s in enumerate(symbols)}
_id_to_symbol = {i: s for i, s in enumerate(symbols)}
def text_to_sequence(text,... | 80 | 2,757 |
OpenVoice | openvoice/text/english.py | .py | """ from https://github.com/keithito/tacotron """
'''
Cleaners are transformations that run over the input text at both training and eval time.
Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners"
hyperparameter. Some cleaners are English-specific. You'll typically want to use... | 189 | 5,559 |
pytorch-image-models | inference.py | .py | #!/usr/bin/env python3
"""PyTorch Inference Script
An example inference script that outputs top-k class ids for images in a folder into a csv.
Hacked together by / Copyright 2020 Ross Wightman (https://github.com/rwightman)
"""
import argparse
import json
import logging
import os
import time
from contextlib import su... | 390 | 17,861 |
pytorch-image-models | train.py | .py | #!/usr/bin/env python3
""" ImageNet Training Script
This is intended to be a lean and easily modifiable ImageNet training script that reproduces ImageNet
training results with some of the latest networks and training techniques. It favours canonical PyTorch
and standard Python style over trying to be able to 'do it al... | 1,534 | 73,502 |
pytorch-image-models | benchmark.py | .py | #!/usr/bin/env python3
""" Model Benchmark Script
An inference and train step benchmark script for timm models.
Hacked together by Ross Wightman (https://github.com/rwightman)
"""
import argparse
import csv
import json
import logging
import time
from collections import OrderedDict
from contextlib import suppress
from... | 693 | 28,381 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.