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Revert "Depend on sensAI instead of copying its utils (logging, string)"

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This reverts commit fdb0eba93d81fa5e698770b4f7088c87fc1238da.
This commit is contained in:
Dominik Jain 2023-11-07 10:54:22 +01:00
parent ac672f65d1
commit dae4000cd2
37 changed files with 746 additions and 760 deletions
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3
.gitignore vendored
View File

@ -153,5 +153,6 @@ videos/
# might be needed for IDE plugins that can't read ruff config
.flake8
# folder for temporary files
# temporary scripts (for ad-hoc testing), temp folder
/temp
/temp*.py

5
examples/atari/atari_dqn_hl.py
View File

@ -2,9 +2,6 @@
import os
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.atari.atari_callbacks import (
TestEpochCallbackDQNSetEps,
TrainEpochCallbackNatureDQNEpsLinearDecay,
@ -23,6 +20,8 @@ from tianshou.highlevel.params.policy_params import DQNParams
from tianshou.highlevel.params.policy_wrapper import (
PolicyWrapperFactoryIntrinsicCuriosity,
)
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

5
examples/atari/atari_iqn_hl.py
View File

@ -3,9 +3,6 @@
import os
from collections.abc import Sequence
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.atari.atari_callbacks import (
TestEpochCallbackDQNSetEps,
TrainEpochCallbackNatureDQNEpsLinearDecay,
@ -20,6 +17,8 @@ from tianshou.highlevel.experiment import (
IQNExperimentBuilder,
)
from tianshou.highlevel.params.policy_params import IQNParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

5
examples/atari/atari_ppo_hl.py
View File

@ -3,9 +3,6 @@
import os
from collections.abc import Sequence
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.atari.atari_network import (
ActorFactoryAtariDQN,
IntermediateModuleFactoryAtariDQNFeatures,
@ -21,6 +18,8 @@ from tianshou.highlevel.params.policy_params import PPOParams
from tianshou.highlevel.params.policy_wrapper import (
PolicyWrapperFactoryIntrinsicCuriosity,
)
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

5
examples/atari/atari_sac_hl.py
View File

@ -2,9 +2,6 @@
import os
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.atari.atari_network import (
ActorFactoryAtariDQN,
IntermediateModuleFactoryAtariDQNFeatures,
@ -20,6 +17,8 @@ from tianshou.highlevel.params.policy_params import DiscreteSACParams
from tianshou.highlevel.params.policy_wrapper import (
PolicyWrapperFactoryIntrinsicCuriosity,
)
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

4
examples/mujoco/mujoco_a2c_hl.py
View File

@ -4,8 +4,6 @@ import os
from collections.abc import Sequence
from typing import Literal
from sensai.util import logging
from sensai.util.logging import datetime_tag
from torch import nn
from examples.mujoco.mujoco_env import MujocoEnvFactory
@ -17,6 +15,8 @@ from tianshou.highlevel.experiment import (
from tianshou.highlevel.optim import OptimizerFactoryRMSprop
from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
from tianshou.highlevel.params.policy_params import A2CParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

5
examples/mujoco/mujoco_ddpg_hl.py
View File

@ -3,9 +3,6 @@
import os
from collections.abc import Sequence
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
from tianshou.highlevel.experiment import (
@ -14,6 +11,8 @@ from tianshou.highlevel.experiment import (
)
from tianshou.highlevel.params.noise import MaxActionScaledGaussian
from tianshou.highlevel.params.policy_params import DDPGParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

4
examples/mujoco/mujoco_npg_hl.py
View File

@ -5,8 +5,6 @@ from collections.abc import Sequence
from typing import Literal
import torch
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
@ -19,6 +17,8 @@ from tianshou.highlevel.params.dist_fn import (
)
from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
from tianshou.highlevel.params.policy_params import NPGParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

4
examples/mujoco/mujoco_ppo_hl.py
View File

@ -5,8 +5,6 @@ from collections.abc import Sequence
from typing import Literal
import torch
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
@ -19,6 +17,8 @@ from tianshou.highlevel.params.dist_fn import (
)
from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
from tianshou.highlevel.params.policy_params import PPOParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

5
examples/mujoco/mujoco_redq_hl.py
View File

@ -4,9 +4,6 @@ import os
from collections.abc import Sequence
from typing import Literal
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
from tianshou.highlevel.experiment import (
@ -15,6 +12,8 @@ from tianshou.highlevel.experiment import (
)
from tianshou.highlevel.params.alpha import AutoAlphaFactoryDefault
from tianshou.highlevel.params.policy_params import REDQParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

4
examples/mujoco/mujoco_reinforce_hl.py
View File

@ -5,8 +5,6 @@ from collections.abc import Sequence
from typing import Literal
import torch
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
@ -16,6 +14,8 @@ from tianshou.highlevel.experiment import (
)
from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
from tianshou.highlevel.params.policy_params import PGParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

5
examples/mujoco/mujoco_sac_hl.py
View File

@ -3,9 +3,6 @@
import os
from collections.abc import Sequence
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
from tianshou.highlevel.experiment import (
@ -14,6 +11,8 @@ from tianshou.highlevel.experiment import (
)
from tianshou.highlevel.params.alpha import AutoAlphaFactoryDefault
from tianshou.highlevel.params.policy_params import SACParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

4
examples/mujoco/mujoco_td3_hl.py
View File

@ -4,8 +4,6 @@ import os
from collections.abc import Sequence
import torch
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
@ -18,6 +16,8 @@ from tianshou.highlevel.params.noise import (
MaxActionScaledGaussian,
)
from tianshou.highlevel.params.policy_params import TD3Params
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

4
examples/mujoco/mujoco_trpo_hl.py
View File

@ -5,8 +5,6 @@ from collections.abc import Sequence
from typing import Literal
import torch
from sensai.util import logging
from sensai.util.logging import datetime_tag
from examples.mujoco.mujoco_env import MujocoEnvFactory
from tianshou.highlevel.config import SamplingConfig
@ -19,6 +17,8 @@ from tianshou.highlevel.params.dist_fn import (
)
from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
from tianshou.highlevel.params.policy_params import TRPOParams
from tianshou.utils import logging
from tianshou.utils.logging import datetime_tag
def main(

688
poetry.lock generated
View File

@ -403,139 +403,6 @@ files = [
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
]
[[package]]
name = "contourpy"
version = "1.1.0"
description = "Python library for calculating contours of 2D quadrilateral grids"
optional = false
python-versions = ">=3.8"
files = [
{file = "contourpy-1.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:89f06eff3ce2f4b3eb24c1055a26981bffe4e7264acd86f15b97e40530b794bc"},
{file = "contourpy-1.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:dffcc2ddec1782dd2f2ce1ef16f070861af4fb78c69862ce0aab801495dda6a3"},
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]
[package.dependencies]
numpy = ">=1.16"
[package.extras]
bokeh = ["bokeh", "selenium"]
docs = ["furo", "sphinx-copybutton"]
mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.2.0)", "types-Pillow"]
test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
[[package]]
name = "contourpy"
version = "1.1.1"
description = "Python library for calculating contours of 2D quadrilateral grids"
optional = false
python-versions = ">=3.8"
files = [
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version = "1.0.11"
@ -3937,17 +3275,6 @@ files = [
{file = "tensorboard_data_server-0.7.1-py3-none-manylinux2014_x86_64.whl", hash = "sha256:255c02b7f5b03dd5c0a88c928e563441ff39e1d4b4a234cdbe09f016e53d9594"},
]
[[package]]
name = "threadpoolctl"
version = "3.2.0"
description = "threadpoolctl"
optional = false
python-versions = ">=3.8"
files = [
{file = "threadpoolctl-3.2.0-py3-none-any.whl", hash = "sha256:2b7818516e423bdaebb97c723f86a7c6b0a83d3f3b0970328d66f4d9104dc032"},
{file = "threadpoolctl-3.2.0.tar.gz", hash = "sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"},
]
[[package]]
name = "tomli"
version = "2.0.1"
@ -4093,17 +3420,6 @@ files = [
{file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"},
]
[[package]]
name = "tzdata"
version = "2023.3"
description = "Provider of IANA time zone data"
optional = false
python-versions = ">=2"
files = [
{file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
{file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
]
[[package]]
name = "urllib3"
version = "2.0.7"
@ -4239,4 +3555,4 @@ pybullet = ["pybullet"]
[metadata]
lock-version = "2.0"
python-versions = "^3.11"
content-hash = "e499017c223bdbf75f0b15489dedc38cab5b3a9c5f449d65dcf2f177025b4747"

3
pyproject.toml
View File

@ -34,7 +34,6 @@ numpy = "^1"
overrides = "^7.4.0"
packaging = "*"
pettingzoo = "^1.22"
sensai = "1.0.0b3"
tensorboard = "^2.5.0"
# Torch 2.0.1 causes problems, see https://github.com/pytorch/pytorch/issues/100974
torch = "^2.0.0, !=2.0.1, !=2.1.0"
@ -105,7 +104,7 @@ warn_redundant_casts = true
warn_unreachable = true
warn_unused_configs = true
warn_unused_ignores = true
exclude = "^build/|^docs/|^temp/"
exclude = "^build/|^docs/|^tianshou/utils/(string|logging).py|^temp*.py"
[tool.doc8]
max-line-length = 1000

12
tianshou/__init__.py
View File

@ -10,15 +10,3 @@ __all__ = [
"trainer",
"exploration",
]
def _configure_logging() -> None:
from sensai.util import logging
def logging_configure_callback() -> None:
logging.getLogger("numba").setLevel(logging.INFO)
logging.set_configure_callback(logging_configure_callback)
_configure_logging()

2
tianshou/highlevel/agent.py
View File

@ -4,7 +4,6 @@ from abc import ABC, abstractmethod
from typing import Any, Generic, TypeVar, cast
import gymnasium
from sensai.util.string import ToStringMixin
from tianshou.data import Collector, ReplayBuffer, VectorReplayBuffer
from tianshou.highlevel.config import SamplingConfig
@ -60,6 +59,7 @@ from tianshou.policy import (
)
from tianshou.trainer import BaseTrainer, OffpolicyTrainer, OnpolicyTrainer
from tianshou.utils.net.common import ActorCritic
from tianshou.utils.string import ToStringMixin
CHECKPOINT_DICT_KEY_MODEL = "model"
CHECKPOINT_DICT_KEY_OBS_RMS = "obs_rms"

2
tianshou/highlevel/config.py
View File

@ -1,7 +1,7 @@
import multiprocessing
from dataclasses import dataclass
from sensai.util.string import ToStringMixin
from tianshou.utils.string import ToStringMixin
@dataclass

2
tianshou/highlevel/env.py
View File

@ -4,7 +4,6 @@ from enum import Enum
from typing import Any, TypeAlias, cast
import gymnasium as gym
from sensai.util.string import ToStringMixin
from tianshou.env import (
BaseVectorEnv,
@ -15,6 +14,7 @@ from tianshou.env import (
)
from tianshou.highlevel.persistence import Persistence
from tianshou.utils.net.common import TActionShape
from tianshou.utils.string import ToStringMixin
TObservationShape: TypeAlias = int | Sequence[int]

7
tianshou/highlevel/experiment.py
View File

@ -8,9 +8,6 @@ from typing import Any, Self
import numpy as np
import torch
from sensai.util import logging
from sensai.util.logging import datetime_tag
from sensai.util.string import ToStringMixin
from tianshou.data import Collector
from tianshou.highlevel.agent import (
@ -80,8 +77,10 @@ from tianshou.highlevel.trainer import (
)
from tianshou.highlevel.world import World
from tianshou.policy import BasePolicy
from tianshou.utils import LazyLogger
from tianshou.utils import LazyLogger, logging
from tianshou.utils.logging import datetime_tag
from tianshou.utils.net.common import ModuleType
from tianshou.utils.string import ToStringMixin
log = logging.getLogger(__name__)

2
tianshou/highlevel/logger.py
View File

@ -2,10 +2,10 @@ import os
from abc import ABC, abstractmethod
from typing import Literal, TypeAlias
from sensai.util.string import ToStringMixin
from torch.utils.tensorboard import SummaryWriter
from tianshou.utils import BaseLogger, TensorboardLogger, WandbLogger
from tianshou.utils.string import ToStringMixin
TLogger: TypeAlias = BaseLogger

2
tianshou/highlevel/module/actor.py
View File

@ -5,7 +5,6 @@ from enum import Enum
from typing import Protocol
import torch
from sensai.util.string import ToStringMixin
from torch import nn
from tianshou.highlevel.env import Environments, EnvType
@ -22,6 +21,7 @@ from tianshou.highlevel.module.module_opt import ModuleOpt
from tianshou.highlevel.optim import OptimizerFactory
from tianshou.utils.net import continuous, discrete
from tianshou.utils.net.common import BaseActor, ModuleType, Net
from tianshou.utils.string import ToStringMixin
class ContinuousActorType(Enum):

2
tianshou/highlevel/module/critic.py
View File

@ -2,7 +2,6 @@ from abc import ABC, abstractmethod
from collections.abc import Sequence
import numpy as np
from sensai.util.string import ToStringMixin
from torch import nn
from tianshou.highlevel.env import Environments, EnvType
@ -12,6 +11,7 @@ from tianshou.highlevel.module.module_opt import ModuleOpt
from tianshou.highlevel.optim import OptimizerFactory
from tianshou.utils.net import continuous, discrete
from tianshou.utils.net.common import BaseActor, EnsembleLinear, ModuleType, Net
from tianshou.utils.string import ToStringMixin
class CriticFactory(ToStringMixin, ABC):

2
tianshou/highlevel/module/intermediate.py
View File

@ -2,10 +2,10 @@ from abc import ABC, abstractmethod
from dataclasses import dataclass
import torch
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import Environments
from tianshou.highlevel.module.core import ModuleFactory, TDevice
from tianshou.utils.string import ToStringMixin
@dataclass

3
tianshou/highlevel/module/special.py
View File

@ -1,11 +1,10 @@
from collections.abc import Sequence
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import Environments
from tianshou.highlevel.module.core import ModuleFactory, TDevice
from tianshou.highlevel.module.intermediate import IntermediateModuleFactory
from tianshou.utils.net.discrete import ImplicitQuantileNetwork
from tianshou.utils.string import ToStringMixin
class ImplicitQuantileNetworkFactory(ModuleFactory, ToStringMixin):

3
tianshou/highlevel/optim.py
View File

@ -2,9 +2,10 @@ from abc import ABC, abstractmethod
from typing import Any, Protocol
import torch
from sensai.util.string import ToStringMixin
from torch.optim import Adam, RMSprop
from tianshou.utils.string import ToStringMixin
class OptimizerWithLearningRateProtocol(Protocol):
def __call__(self, parameters: Any, lr: float, **kwargs: Any) -> torch.optim.Optimizer:

2
tianshou/highlevel/params/alpha.py
View File

@ -2,11 +2,11 @@ from abc import ABC, abstractmethod
import numpy as np
import torch
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import Environments
from tianshou.highlevel.module.core import TDevice
from tianshou.highlevel.optim import OptimizerFactory
from tianshou.utils.string import ToStringMixin
class AutoAlphaFactory(ToStringMixin, ABC):

2
tianshou/highlevel/params/dist_fn.py
View File

@ -1,10 +1,10 @@
from abc import ABC, abstractmethod
import torch
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import Environments, EnvType
from tianshou.policy.modelfree.pg import TDistributionFunction
from tianshou.utils.string import ToStringMixin
class DistributionFunctionFactory(ToStringMixin, ABC):

3
tianshou/highlevel/params/env_param.py
View File

@ -2,9 +2,8 @@
from abc import ABC, abstractmethod
from typing import Generic, TypeVar
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import ContinuousEnvironments, Environments
from tianshou.utils.string import ToStringMixin
TValue = TypeVar("TValue")
TEnvs = TypeVar("TEnvs", bound=Environments)

2
tianshou/highlevel/params/lr_scheduler.py
View File

@ -2,10 +2,10 @@ from abc import ABC, abstractmethod
import numpy as np
import torch
from sensai.util.string import ToStringMixin
from torch.optim.lr_scheduler import LambdaLR, LRScheduler
from tianshou.highlevel.config import SamplingConfig
from tianshou.utils.string import ToStringMixin
class LRSchedulerFactory(ToStringMixin, ABC):

3
tianshou/highlevel/params/noise.py
View File

@ -1,9 +1,8 @@
from abc import ABC, abstractmethod
from sensai.util.string import ToStringMixin
from tianshou.exploration import BaseNoise, GaussianNoise
from tianshou.highlevel.env import ContinuousEnvironments, Environments
from tianshou.utils.string import ToStringMixin
class NoiseFactory(ToStringMixin, ABC):

2
tianshou/highlevel/params/policy_params.py
View File

@ -4,7 +4,6 @@ from dataclasses import asdict, dataclass
from typing import Any, Literal, Protocol
import torch
from sensai.util.string import ToStringMixin
from torch.optim.lr_scheduler import LRScheduler
from tianshou.exploration import BaseNoise
@ -22,6 +21,7 @@ from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactory
from tianshou.highlevel.params.noise import NoiseFactory
from tianshou.policy.modelfree.pg import TDistributionFunction
from tianshou.utils import MultipleLRSchedulers
from tianshou.utils.string import ToStringMixin
@dataclass(kw_only=True)

3
tianshou/highlevel/params/policy_wrapper.py
View File

@ -2,14 +2,13 @@ from abc import ABC, abstractmethod
from collections.abc import Sequence
from typing import Generic, TypeVar
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import Environments
from tianshou.highlevel.module.core import TDevice
from tianshou.highlevel.module.intermediate import IntermediateModuleFactory
from tianshou.highlevel.optim import OptimizerFactory
from tianshou.policy import BasePolicy, ICMPolicy
from tianshou.utils.net.discrete import IntrinsicCuriosityModule
from tianshou.utils.string import ToStringMixin
TPolicyOut = TypeVar("TPolicyOut", bound=BasePolicy)

3
tianshou/highlevel/trainer.py
View File

@ -3,11 +3,10 @@ from collections.abc import Callable
from dataclasses import dataclass
from typing import TypeVar
from sensai.util.string import ToStringMixin
from tianshou.highlevel.env import Environments
from tianshou.highlevel.logger import TLogger
from tianshou.policy import BasePolicy
from tianshou.utils.string import ToStringMixin
TPolicy = TypeVar("TPolicy", bound=BasePolicy)

158
tianshou/utils/logging.py Normal file
View File

@ -0,0 +1,158 @@
"""
Partial copy of sensai.util.logging
"""
# ruff: noqa
import atexit
import logging as lg
import sys
from collections.abc import Callable
from datetime import datetime
from io import StringIO
from logging import *
from typing import Any
log = getLogger(__name__)
LOG_DEFAULT_FORMAT = "%(levelname)-5s %(asctime)-15s %(name)s:%(funcName)s - %(message)s"
# Holds the log format that is configured by the user (using function `configure`), such
# that it can be reused in other places
_logFormat = LOG_DEFAULT_FORMAT
def remove_log_handlers():
"""Removes all current log handlers."""
logger = getLogger()
while logger.hasHandlers():
logger.removeHandler(logger.handlers[0])
def remove_log_handler(handler):
getLogger().removeHandler(handler)
def is_log_handler_active(handler):
"""Checks whether the given handler is active.
:param handler: a log handler
:return: True if the handler is active, False otherwise
"""
return handler in getLogger().handlers
# noinspection PyShadowingBuiltins
def configure(format=LOG_DEFAULT_FORMAT, level=lg.DEBUG):
"""Configures logging to stdout with the given format and log level,
also configuring the default log levels of some overly verbose libraries as well as some pandas output options.
:param format: the log format
:param level: the minimum log level
"""
global _logFormat
_logFormat = format
remove_log_handlers()
basicConfig(level=level, format=format, stream=sys.stdout)
# set log levels of third-party libraries
getLogger("numba").setLevel(INFO)
# noinspection PyShadowingBuiltins
def run_main(main_fn: Callable[[], Any], format=LOG_DEFAULT_FORMAT, level=lg.DEBUG):
"""Configures logging with the given parameters, ensuring that any exceptions that occur during
the execution of the given function are logged.
Logs two additional messages, one before the execution of the function, and one upon its completion.
:param main_fn: the function to be executed
:param format: the log message format
:param level: the minimum log level
:return: the result of `main_fn`
"""
configure(format=format, level=level)
log.info("Starting")
try:
result = main_fn()
log.info("Done")
return result
except Exception as e:
log.error("Exception during script execution", exc_info=e)
def run_cli(main_fn: Callable[[], Any], format=LOG_DEFAULT_FORMAT, level=lg.DEBUG):
"""
Configures logging with the given parameters and runs the given main function as a
CLI using `jsonargparse` (which is configured to also parse attribute docstrings, such
that dataclasses can be used as function arguments).
Using this function requires that `jsonargparse` and `docstring_parser` be available.
Like `run_main`, two additional log messages will be logged (at the beginning and end
of the execution), and it is ensured that all exceptions will be logged.
:param main_fn: the function to be executed
:param format: the log message format
:param level: the minimum log level
:return: the result of `main_fn`
"""
from jsonargparse import set_docstring_parse_options, CLI
set_docstring_parse_options(attribute_docstrings=True)
return run_main(lambda: CLI(main_fn), format=format, level=level)
def datetime_tag() -> str:
""":return: a string tag for use in log file names which contains the current date and time (compact but readable)"""
return datetime.now().strftime("%Y%m%d-%H%M%S")
_fileLoggerPaths: list[str] = []
_isAtExitReportFileLoggerRegistered = False
_memoryLogStream: StringIO | None = None
def _at_exit_report_file_logger():
for path in _fileLoggerPaths:
print(f"A log file was saved to {path}")
def add_file_logger(path, register_atexit=True):
global _isAtExitReportFileLoggerRegistered
log.info(f"Logging to {path} ...")
handler = FileHandler(path)
handler.setFormatter(Formatter(_logFormat))
Logger.root.addHandler(handler)
_fileLoggerPaths.append(path)
if not _isAtExitReportFileLoggerRegistered and register_atexit:
atexit.register(_at_exit_report_file_logger)
_isAtExitReportFileLoggerRegistered = True
return handler
def add_memory_logger() -> None:
"""Enables in-memory logging (if it is not already enabled), i.e. all log statements are written to a memory buffer and can later be
read via function `get_memory_log()`.
"""
global _memoryLogStream
if _memoryLogStream is not None:
return
_memoryLogStream = StringIO()
handler = StreamHandler(_memoryLogStream)
handler.setFormatter(Formatter(_logFormat))
Logger.root.addHandler(handler)
def get_memory_log():
""":return: the in-memory log (provided that `add_memory_logger` was called beforehand)"""
return _memoryLogStream.getvalue()
class FileLoggerContext:
def __init__(self, path: str, enabled=True):
self.enabled = enabled
self.path = path
self._log_handler = None
def __enter__(self):
if self.enabled:
self._log_handler = add_file_logger(self.path, register_atexit=False)
def __exit__(self, exc_type, exc_value, traceback):
if self._log_handler is not None:
remove_log_handler(self._log_handler)

536
tianshou/utils/string.py Normal file
View File

@ -0,0 +1,536 @@
"""Copy of sensai.util.string from sensAI commit d7b4afcc89b4d2e922a816cb07dffde27f297354."""
import functools
import logging
import re
import sys
import types
from abc import ABC, abstractmethod
from collections.abc import Callable, Iterable, Mapping, Sequence
from typing import (
Any,
)
reCommaWhitespacePotentiallyBreaks = re.compile(r",\s+")
log = logging.getLogger(__name__)
class StringConverter(ABC):
"""Abstraction for a string conversion mechanism."""
@abstractmethod
def to_string(self, x) -> str:
pass
def dict_string(d: Mapping, brackets: str | None = None, converter: StringConverter = None):
"""Converts a dictionary to a string of the form "<key>=<value>, <key>=<value>, ...", optionally enclosed
by brackets.
:param d: the dictionary
:param brackets: a two-character string containing the opening and closing bracket to use, e.g. ``"{}"``;
if None, do not use enclosing brackets
:param converter: the string converter to use for values
:return: the string representation
"""
s = ", ".join([f"{k}={to_string(v, converter=converter, context=k)}" for k, v in d.items()])
if brackets is not None:
return brackets[:1] + s + brackets[-1:]
else:
return s
def list_string(
l: Iterable[Any],
brackets="[]",
quote: str | None = None,
converter: StringConverter = None,
):
"""Converts a list or any other iterable to a string of the form "[<value>, <value>, ...]", optionally enclosed
by different brackets or with the values quoted.
:param l: the list
:param brackets: a two-character string containing the opening and closing bracket to use, e.g. ``"[]"``;
if None, do not use enclosing brackets
:param quote: a 1-character string defining the quote to use around each value, e.g. ``"'"``.
:param converter: the string converter to use for values
:return: the string representation
"""
def item(x):
x = to_string(x, converter=converter, context="list")
if quote is not None:
return quote + x + quote
else:
return x
s = ", ".join(item(x) for x in l)
if brackets is not None:
return brackets[:1] + s + brackets[-1:]
else:
return s
def to_string(
x,
converter: StringConverter = None,
apply_converter_to_non_complex_objects=True,
context=None,
):
"""Converts the given object to a string, with proper handling of lists, tuples and dictionaries, optionally using a converter.
The conversion also removes unwanted line breaks (as present, in particular, in sklearn's string representations).
:param x: the object to convert
:param converter: the converter with which to convert objects to strings
:param apply_converter_to_non_complex_objects: whether to apply/pass on the converter (if any) not only when converting complex objects
but also non-complex, primitive objects; use of this flag enables converters to implement their conversion functionality using this
function for complex objects without causing an infinite recursion.
:param context: context in which the object is being converted (e.g. dictionary key for case where x is the corresponding
dictionary value), only for debugging purposes (will be reported in log messages upon recursion exception)
:return: the string representation
"""
try:
if isinstance(x, list):
return list_string(x, converter=converter)
elif isinstance(x, tuple):
return list_string(x, brackets="()", converter=converter)
elif isinstance(x, dict):
return dict_string(x, brackets="{}", converter=converter)
elif isinstance(x, types.MethodType):
# could be bound method of a ToStringMixin instance (which would print the repr of the instance, which can potentially cause
# an infinite recursion)
return f"Method[{x.__name__}]"
else:
if converter and apply_converter_to_non_complex_objects:
s = converter.to_string(x)
else:
s = str(x)
# remove any unwanted line breaks and indentation after commas (as generated, for example, by sklearn objects)
return reCommaWhitespacePotentiallyBreaks.sub(", ", s)
except RecursionError:
log.error(f"Recursion in string conversion detected; context={context}")
raise
def object_repr(obj, member_names_or_dict: list[str] | dict[str, Any]):
"""Creates a string representation for the given object based on the given members.
The string takes the form "ClassName[attr1=value1, attr2=value2, ...]"
"""
if isinstance(member_names_or_dict, dict):
members_dict = member_names_or_dict
else:
members_dict = {m: to_string(getattr(obj, m)) for m in member_names_or_dict}
return f"{obj.__class__.__name__}[{dict_string(members_dict)}]"
def or_regex_group(allowed_names: Sequence[str]):
""":param allowed_names: strings to include as literals in the regex
:return: a regular expression string of the form (<name1>| ...|<nameN>), which any of the given names
"""
allowed_names = [re.escape(name) for name in allowed_names]
return r"(%s)" % "|".join(allowed_names)
def function_name(x: Callable) -> str:
"""Attempts to retrieve the name of the given function/callable object, taking the possibility
of the function being defined via functools.partial into account.
:param x: a callable object
:return: name of the function or str(x) as a fallback
"""
if isinstance(x, functools.partial):
return function_name(x.func)
elif hasattr(x, "__name__"):
return x.__name__
else:
return str(x)
class ToStringMixin:
"""Provides implementations for ``__str__`` and ``__repr__`` which are based on the format ``"<class name>[<object info>]"`` and
``"<class name>[id=<object id>, <object info>]"`` respectively, where ``<object info>`` is usually a list of entries of the
form ``"<name>=<value>, ..."``.
By default, ``<class name>`` will be the qualified name of the class, and ``<object info>`` will include all properties
of the class, including private ones starting with an underscore (though the underscore will be dropped in the string
representation).
* To exclude private properties, override :meth:`_toStringExcludePrivate` to return True. If there are exceptions
(and some private properties shall be retained), additionally override :meth:`_toStringExcludeExceptions`.
* To exclude a particular set of properties, override :meth:`_toStringExcludes`.
* To include only select properties (introducing inclusion semantics), override :meth:`_toStringIncludes`.
* To add values to the properties list that aren't actually properties of the object (i.e. derived properties),
override :meth:`_toStringAdditionalEntries`.
* To define a fully custom representation for ``<object info>`` which is not based on the above principles, override
:meth:`_toStringObjectInfo`.
For well-defined string conversions within a class hierarchy, it can be a good practice to define additional
inclusions/exclusions by overriding the respective method once more and basing the return value on an extended
version of the value returned by superclass.
In some cases, the requirements of a subclass can be at odds with the definitions in the superclass: The superclass
may make use of exclusion semantics, but the subclass may want to use inclusion semantics (and include
only some of the many properties it adds). In this case, if the subclass used :meth:`_toStringInclude`, the exclusion semantics
of the superclass would be void and none of its properties would actually be included.
In such cases, override :meth:`_toStringIncludesForced` to add inclusions regardless of the semantics otherwise used along
the class hierarchy.
.. document private functions
.. automethod:: _tostring_class_name
.. automethod:: _tostring_object_info
.. automethod:: _tostring_excludes
.. automethod:: _tostring_exclude_exceptions
.. automethod:: _tostring_includes
.. automethod:: _tostring_includes_forced
.. automethod:: _tostring_additional_entries
.. automethod:: _tostring_exclude_private
"""
_TOSTRING_INCLUDE_ALL = "__all__"
def _tostring_class_name(self):
""":return: the string use for <class name> in the string representation ``"<class name>[<object info]"``"""
return type(self).__qualname__
def _tostring_properties(
self,
exclude: str | Iterable[str] | None = None,
include: str | Iterable[str] | None = None,
exclude_exceptions: list[str] | None = None,
include_forced: list[str] | None = None,
additional_entries: dict[str, Any] | None = None,
converter: StringConverter = None,
) -> str:
"""Creates a string of the class attributes, with optional exclusions/inclusions/additions.
Exclusions take precedence over inclusions.
:param exclude: attributes to be excluded
:param include: attributes to be included; if non-empty, only the specified attributes will be printed (bar the ones
excluded by ``exclude``)
:param include_forced: additional attributes to be included
:param additional_entries: additional key-value entries to be added
:param converter: the string converter to use; if None, use default (which avoids infinite recursions)
:return: a string containing entry/property names and values
"""
def mklist(x):
if x is None:
return []
if isinstance(x, str):
return [x]
return x
exclude = mklist(exclude)
include = mklist(include)
include_forced = mklist(include_forced)
exclude_exceptions = mklist(exclude_exceptions)
def is_excluded(k):
if k in include_forced or k in exclude_exceptions:
return False
if k in exclude:
return True
if self._tostring_exclude_private():
return k.startswith("_")
else:
return False
# determine relevant attribute dictionary
if (
len(include) == 1 and include[0] == self._TOSTRING_INCLUDE_ALL
): # exclude semantics (include everything by default)
attribute_dict = self.__dict__
else: # include semantics (include only inclusions)
attribute_dict = {
k: getattr(self, k)
for k in set(include + include_forced)
if hasattr(self, k) and k != self._TOSTRING_INCLUDE_ALL
}
# apply exclusions and remove underscores from attribute names
d = {k.strip("_"): v for k, v in attribute_dict.items() if not is_excluded(k)}
if additional_entries is not None:
d.update(additional_entries)
if converter is None:
converter = self._StringConverterAvoidToStringMixinRecursion(self)
return dict_string(d, converter=converter)
def _tostring_object_info(self) -> str:
"""Override this method to use a fully custom definition of the ``<object info>`` part in the full string
representation ``"<class name>[<object info>]"`` to be generated.
As soon as this method is overridden, any property-based exclusions, inclusions, etc. will have no effect
(unless the implementation is specifically designed to make use of them - as is the default
implementation).
NOTE: Overrides must not internally use super() because of a technical limitation in the proxy
object that is used for nested object structures.
:return: a string containing the string to use for ``<object info>``
"""
return self._tostring_properties(
exclude=self._tostring_excludes(),
include=self._tostring_includes(),
exclude_exceptions=self._tostring_exclude_exceptions(),
include_forced=self._tostring_includes_forced(),
additional_entries=self._tostring_additional_entries(),
)
def _tostring_excludes(self) -> list[str]:
"""Makes the string representation exclude the returned attributes.
This method can be conveniently overridden by subclasses which can call super and extend the list returned.
This method will only have no effect if :meth:`_toStringObjectInfo` is overridden to not use its result.
:return: a list of attribute names
"""
return []
def _tostring_includes(self) -> list[str]:
"""Makes the string representation include only the returned attributes (i.e. introduces inclusion semantics);
By default, the list contains only a marker element, which is interpreted as "all attributes included".
This method can be conveniently overridden by sub-classes which can call super and extend the list returned.
Note that it is not a problem for a list containing the aforementioned marker element (which stands for all attributes)
to be extended; the marker element will be ignored and only the user-added elements will be considered as included.
Note: To add an included attribute in a sub-class, regardless of any super-classes using exclusion or inclusion semantics,
use _toStringIncludesForced instead.
This method will have no effect if :meth:`_toStringObjectInfo` is overridden to not use its result.
:return: a list of attribute names to be included in the string representation
"""
return [self._TOSTRING_INCLUDE_ALL]
# noinspection PyMethodMayBeStatic
def _tostring_includes_forced(self) -> list[str]:
"""Defines a list of attribute names that are required to be present in the string representation, regardless of the
instance using include semantics or exclude semantics, thus facilitating added inclusions in sub-classes.
This method will have no effect if :meth:`_toStringObjectInfo` is overridden to not use its result.
:return: a list of attribute names
"""
return []
def _tostring_additional_entries(self) -> dict[str, Any]:
""":return: a dictionary of entries to be included in the ``<object info>`` part of the string representation"""
return {}
def _tostring_exclude_private(self) -> bool:
""":return: whether to exclude properties that are private (start with an underscore); explicitly included attributes
will still be considered - as will properties exempt from the rule via :meth:`toStringExcludeException`.
"""
return False
def _tostring_exclude_exceptions(self) -> list[str]:
"""Defines attribute names which should not be excluded even though other rules (particularly the exclusion of private members
via :meth:`_toStringExcludePrivate`) would otherwise exclude them.
:return: a list of attribute names
"""
return []
def __str__(self):
return f"{self._tostring_class_name()}[{self._tostring_object_info()}]"
def __repr__(self):
info = f"id={id(self)}"
property_info = self._tostring_object_info()
if len(property_info) > 0:
info += ", " + property_info
return f"{self._tostring_class_name()}[{info}]"
def pprint(self, file=sys.stdout):
"""Prints a prettily formatted string representation of the object (with line breaks and indentations)
to ``stdout`` or the given file.
:param file: the file to print to
"""
print(self.pprints(), file=file)
def pprints(self) -> str:
""":return: a prettily formatted string representation with line breaks and indentations"""
return pretty_string_repr(self)
class _StringConverterAvoidToStringMixinRecursion(StringConverter):
"""Avoids recursions when converting objects implementing :class:`ToStringMixin` which may contain themselves to strings.
Use of this object prevents infinite recursions caused by a :class:`ToStringMixin` instance recursively containing itself in
either a property of another :class:`ToStringMixin`, a list or a tuple.
It handles all :class:`ToStringMixin` instances recursively encountered.
A previously handled instance is converted to a string of the form "<class name>[<<]".
"""
def __init__(self, *handled_objects: "ToStringMixin"):
""":param handled_objects: objects which are initially assumed to have been handled already"""
self._handled_to_string_mixin_ids = {id(o) for o in handled_objects}
def to_string(self, x) -> str:
if isinstance(x, ToStringMixin):
oid = id(x)
if oid in self._handled_to_string_mixin_ids:
return f"{x._tostring_class_name()}[<<]"
self._handled_to_string_mixin_ids.add(oid)
return str(self._ToStringMixinProxy(x, self))
else:
return to_string(
x,
converter=self,
apply_converter_to_non_complex_objects=False,
context=x.__class__,
)
class _ToStringMixinProxy:
"""A proxy object which wraps a ToStringMixin to ensure that the converter is applied when creating the properties string.
The proxy is to achieve that all ToStringMixin methods that aren't explicitly overwritten are bound to this proxy
(rather than the original object), such that the transitive call to _toStringProperties will call the new
implementation.
"""
# methods where we assume that they could transitively call _toStringProperties (others are assumed not to)
TOSTRING_METHODS_TRANSITIVELY_CALLING_TOSTRINGPROPERTIES = {"_tostring_object_info"}
def __init__(self, x: "ToStringMixin", converter):
self.x = x
self.converter = converter
def _tostring_properties(self, *args, **kwargs):
return self.x._tostring_properties(*args, **kwargs, converter=self.converter)
def _tostring_class_name(self):
return self.x._tostring_class_name()
def __getattr__(self, attr: str):
if attr.startswith(
"_tostring",
): # ToStringMixin method which we may bind to use this proxy to ensure correct transitive call
method = getattr(self.x.__class__, attr)
obj = (
self
if attr in self.TOSTRING_METHODS_TRANSITIVELY_CALLING_TOSTRINGPROPERTIES
else self.x
)
return lambda *args, **kwargs: method(obj, *args, **kwargs)
else:
return getattr(self.x, attr)
def __str__(self: "ToStringMixin"):
return ToStringMixin.__str__(self)
def pretty_string_repr(s: Any, initial_indentation_level=0, indentation_string=" "):
"""Creates a pretty string representation (using indentations) from the given object/string representation (as generated, for example, via
ToStringMixin). An indentation level is added for every opening bracket.
:param s: an object or object string representation
:param initial_indentation_level: the initial indentation level
:param indentation_string: the string which corresponds to a single indentation level
:return: a reformatted version of the input string with added indentations and line breaks
"""
if not isinstance(s, str):
s = str(s)
indent = initial_indentation_level
result = indentation_string * indent
i = 0
def nl():
nonlocal result
result += "\n" + (indentation_string * indent)
def take(cnt=1):
nonlocal result, i
result += s[i : i + cnt]
i += cnt
def find_matching(j):
start = j
op = s[j]
cl = {"[": "]", "(": ")", "'": "'"}[s[j]]
is_bracket = cl != s[j]
stack = 0
while j < len(s):
if s[j] == op and (is_bracket or j == start):
stack += 1
elif s[j] == cl:
stack -= 1
if stack == 0:
return j
j += 1
return None
brackets = "[("
quotes = "'"
while i < len(s):
is_bracket = s[i] in brackets
is_quote = s[i] in quotes
if is_bracket or is_quote:
i_match = find_matching(i)
take_full_match_without_break = False
if i_match is not None:
k = i_match + 1
full_match = s[i:k]
take_full_match_without_break = is_quote or not (
"=" in full_match and "," in full_match
)
if take_full_match_without_break:
take(k - i)
if not take_full_match_without_break:
take(1)
indent += 1
nl()
elif s[i] in "])":
take(1)
indent -= 1
elif s[i : i + 2] == ", ":
take(2)
nl()
else:
take(1)
return result
class TagBuilder:
"""Assists in building strings made up of components that are joined via a glue string."""
def __init__(self, *initial_components: str, glue="_"):
""":param initial_components: initial components to always include at the beginning
:param glue: the glue string which joins components
"""
self.glue = glue
self.components = list(initial_components)
def with_component(self, component: str):
self.components.append(component)
def with_conditional(self, cond: bool, component: str):
"""Conditionally adds the given component.
:param cond: the condition
:param component: the component to add if the condition holds
:return: the builder
"""
if cond:
self.components.append(component)
return self
def with_alternative(self, cond: bool, true_component: str, false_component: str):
"""Adds a component depending on a condition.
:param cond: the condition
:param true_component: the component to add if the condition holds
:param false_component: the component to add if the condition does not hold
:return: the builder
"""
self.components.append(true_component if cond else false_component)
return self
def build(self):
""":return: the string (with all components joined)"""
return self.glue.join(self.components)