Module TeachMyAgent.students.openai_baselines.common.misc_util

Expand source code
import gym
import numpy as np
import os
import pickle
import random
import tempfile
import zipfile


def zipsame(*seqs):
    L = len(seqs[0])
    assert all(len(seq) == L for seq in seqs[1:])
    return zip(*seqs)


class EzPickle(object):
    """Objects that are pickled and unpickled via their constructor
    arguments.

    Example usage:

        class Dog(Animal, EzPickle):
            def __init__(self, furcolor, tailkind="bushy"):
                Animal.__init__()
                EzPickle.__init__(furcolor, tailkind)
                ...

    When this object is unpickled, a new Dog will be constructed by passing the provided
    furcolor and tailkind into the constructor. However, philosophers are still not sure
    whether it is still the same dog.

    This is generally needed only for environments which wrap C/C++ code, such as MuJoCo
    and Atari.
    """

    def __init__(self, *args, **kwargs):
        self._ezpickle_args = args
        self._ezpickle_kwargs = kwargs

    def __getstate__(self):
        return {"_ezpickle_args": self._ezpickle_args, "_ezpickle_kwargs": self._ezpickle_kwargs}

    def __setstate__(self, d):
        out = type(self)(*d["_ezpickle_args"], **d["_ezpickle_kwargs"])
        self.__dict__.update(out.__dict__)


def set_global_seeds(i):
    try:
        import MPI
        rank = MPI.COMM_WORLD.Get_rank()
    except ImportError:
        rank = 0

    myseed = i  + 1000 * rank if i is not None else None
    try:
        import tensorflow as tf
        tf.set_random_seed(myseed)
    except ImportError:
        pass
    np.random.seed(myseed)
    random.seed(myseed)


def pretty_eta(seconds_left):
    """Print the number of seconds in human readable format.

    Examples:
    2 days
    2 hours and 37 minutes
    less than a minute

    Paramters
    ---------
    seconds_left: int
        Number of seconds to be converted to the ETA
    Returns
    -------
    eta: str
        String representing the pretty ETA.
    """
    minutes_left = seconds_left // 60
    seconds_left %= 60
    hours_left = minutes_left // 60
    minutes_left %= 60
    days_left = hours_left // 24
    hours_left %= 24

    def helper(cnt, name):
        return "{} {}{}".format(str(cnt), name, ('s' if cnt > 1 else ''))

    if days_left > 0:
        msg = helper(days_left, 'day')
        if hours_left > 0:
            msg += ' and ' + helper(hours_left, 'hour')
        return msg
    if hours_left > 0:
        msg = helper(hours_left, 'hour')
        if minutes_left > 0:
            msg += ' and ' + helper(minutes_left, 'minute')
        return msg
    if minutes_left > 0:
        return helper(minutes_left, 'minute')
    return 'less than a minute'


class RunningAvg(object):
    def __init__(self, gamma, init_value=None):
        """Keep a running estimate of a quantity. This is a bit like mean
        but more sensitive to recent changes.

        Parameters
        ----------
        gamma: float
            Must be between 0 and 1, where 0 is the most sensitive to recent
            changes.
        init_value: float or None
            Initial value of the estimate. If None, it will be set on the first update.
        """
        self._value = init_value
        self._gamma = gamma

    def update(self, new_val):
        """Update the estimate.

        Parameters
        ----------
        new_val: float
            new observated value of estimated quantity.
        """
        if self._value is None:
            self._value = new_val
        else:
            self._value = self._gamma * self._value + (1.0 - self._gamma) * new_val

    def __float__(self):
        """Get the current estimate"""
        return self._value

def boolean_flag(parser, name, default=False, help=None):
    """Add a boolean flag to argparse parser.

    Parameters
    ----------
    parser: argparse.Parser
        parser to add the flag to
    name: str
        --<name> will enable the flag, while --no-<name> will disable it
    default: bool or None
        default value of the flag
    help: str
        help string for the flag
    """
    dest = name.replace('-', '_')
    parser.add_argument("--" + name, action="store_true", default=default, dest=dest, help=help)
    parser.add_argument("--no-" + name, action="store_false", dest=dest)


def get_wrapper_by_name(env, classname):
    """Given an a gym environment possibly wrapped multiple times, returns a wrapper
    of class named classname or raises ValueError if no such wrapper was applied

    Parameters
    ----------
    env: gym.Env of gym.Wrapper
        gym environment
    classname: str
        name of the wrapper

    Returns
    -------
    wrapper: gym.Wrapper
        wrapper named classname
    """
    currentenv = env
    while True:
        if classname == currentenv.class_name():
            return currentenv
        elif isinstance(currentenv, gym.Wrapper):
            currentenv = currentenv.env
        else:
            raise ValueError("Couldn't find wrapper named %s" % classname)


def relatively_safe_pickle_dump(obj, path, compression=False):
    """This is just like regular pickle dump, except from the fact that failure cases are
    different:

        - It's never possible that we end up with a pickle in corrupted state.
        - If a there was a different file at the path, that file will remain unchanged in the
          even of failure (provided that filesystem rename is atomic).
        - it is sometimes possible that we end up with useless temp file which needs to be
          deleted manually (it will be removed automatically on the next function call)

    The indended use case is periodic checkpoints of experiment state, such that we never
    corrupt previous checkpoints if the current one fails.

    Parameters
    ----------
    obj: object
        object to pickle
    path: str
        path to the output file
    compression: bool
        if true pickle will be compressed
    """
    temp_storage = path + ".relatively_safe"
    if compression:
        # Using gzip here would be simpler, but the size is limited to 2GB
        with tempfile.NamedTemporaryFile() as uncompressed_file:
            pickle.dump(obj, uncompressed_file)
            uncompressed_file.file.flush()
            with zipfile.ZipFile(temp_storage, "w", compression=zipfile.ZIP_DEFLATED) as myzip:
                myzip.write(uncompressed_file.name, "data")
    else:
        with open(temp_storage, "wb") as f:
            pickle.dump(obj, f)
    os.rename(temp_storage, path)


def pickle_load(path, compression=False):
    """Unpickle a possible compressed pickle.

    Parameters
    ----------
    path: str
        path to the output file
    compression: bool
        if true assumes that pickle was compressed when created and attempts decompression.

    Returns
    -------
    obj: object
        the unpickled object
    """

    if compression:
        with zipfile.ZipFile(path, "r", compression=zipfile.ZIP_DEFLATED) as myzip:
            with myzip.open("data") as f:
                return pickle.load(f)
    else:
        with open(path, "rb") as f:
            return pickle.load(f)

Functions

def boolean_flag(parser, name, default=False, help=None)

Add a boolean flag to argparse parser.

Parameters

parser : argparse.Parser
parser to add the flag to
name : str
will enable the flag, while –no- will disable it
default : bool or None
default value of the flag
help : str
help string for the flag
Expand source code
def boolean_flag(parser, name, default=False, help=None):
    """Add a boolean flag to argparse parser.

    Parameters
    ----------
    parser: argparse.Parser
        parser to add the flag to
    name: str
        --<name> will enable the flag, while --no-<name> will disable it
    default: bool or None
        default value of the flag
    help: str
        help string for the flag
    """
    dest = name.replace('-', '_')
    parser.add_argument("--" + name, action="store_true", default=default, dest=dest, help=help)
    parser.add_argument("--no-" + name, action="store_false", dest=dest)
def get_wrapper_by_name(env, classname)

Given an a gym environment possibly wrapped multiple times, returns a wrapper of class named classname or raises ValueError if no such wrapper was applied

Parameters

env : gym.Env of gym.Wrapper
gym environment
classname : str
name of the wrapper

Returns

wrapper : gym.Wrapper
wrapper named classname
Expand source code
def get_wrapper_by_name(env, classname):
    """Given an a gym environment possibly wrapped multiple times, returns a wrapper
    of class named classname or raises ValueError if no such wrapper was applied

    Parameters
    ----------
    env: gym.Env of gym.Wrapper
        gym environment
    classname: str
        name of the wrapper

    Returns
    -------
    wrapper: gym.Wrapper
        wrapper named classname
    """
    currentenv = env
    while True:
        if classname == currentenv.class_name():
            return currentenv
        elif isinstance(currentenv, gym.Wrapper):
            currentenv = currentenv.env
        else:
            raise ValueError("Couldn't find wrapper named %s" % classname)
def pickle_load(path, compression=False)

Unpickle a possible compressed pickle.

Parameters

path : str
path to the output file
compression : bool
if true assumes that pickle was compressed when created and attempts decompression.

Returns

obj : object
the unpickled object
Expand source code
def pickle_load(path, compression=False):
    """Unpickle a possible compressed pickle.

    Parameters
    ----------
    path: str
        path to the output file
    compression: bool
        if true assumes that pickle was compressed when created and attempts decompression.

    Returns
    -------
    obj: object
        the unpickled object
    """

    if compression:
        with zipfile.ZipFile(path, "r", compression=zipfile.ZIP_DEFLATED) as myzip:
            with myzip.open("data") as f:
                return pickle.load(f)
    else:
        with open(path, "rb") as f:
            return pickle.load(f)
def pretty_eta(seconds_left)

Print the number of seconds in human readable format.

Examples: 2 days 2 hours and 37 minutes less than a minute

Paramters

seconds_left: int Number of seconds to be converted to the ETA Returns


eta : str
String representing the pretty ETA.
Expand source code
def pretty_eta(seconds_left):
    """Print the number of seconds in human readable format.

    Examples:
    2 days
    2 hours and 37 minutes
    less than a minute

    Paramters
    ---------
    seconds_left: int
        Number of seconds to be converted to the ETA
    Returns
    -------
    eta: str
        String representing the pretty ETA.
    """
    minutes_left = seconds_left // 60
    seconds_left %= 60
    hours_left = minutes_left // 60
    minutes_left %= 60
    days_left = hours_left // 24
    hours_left %= 24

    def helper(cnt, name):
        return "{} {}{}".format(str(cnt), name, ('s' if cnt > 1 else ''))

    if days_left > 0:
        msg = helper(days_left, 'day')
        if hours_left > 0:
            msg += ' and ' + helper(hours_left, 'hour')
        return msg
    if hours_left > 0:
        msg = helper(hours_left, 'hour')
        if minutes_left > 0:
            msg += ' and ' + helper(minutes_left, 'minute')
        return msg
    if minutes_left > 0:
        return helper(minutes_left, 'minute')
    return 'less than a minute'
def relatively_safe_pickle_dump(obj, path, compression=False)

This is just like regular pickle dump, except from the fact that failure cases are different:

- It's never possible that we end up with a pickle in corrupted state.
- If a there was a different file at the path, that file will remain unchanged in the
  even of failure (provided that filesystem rename is atomic).
- it is sometimes possible that we end up with useless temp file which needs to be
  deleted manually (it will be removed automatically on the next function call)

The indended use case is periodic checkpoints of experiment state, such that we never corrupt previous checkpoints if the current one fails.

Parameters

obj : object
object to pickle
path : str
path to the output file
compression : bool
if true pickle will be compressed
Expand source code
def relatively_safe_pickle_dump(obj, path, compression=False):
    """This is just like regular pickle dump, except from the fact that failure cases are
    different:

        - It's never possible that we end up with a pickle in corrupted state.
        - If a there was a different file at the path, that file will remain unchanged in the
          even of failure (provided that filesystem rename is atomic).
        - it is sometimes possible that we end up with useless temp file which needs to be
          deleted manually (it will be removed automatically on the next function call)

    The indended use case is periodic checkpoints of experiment state, such that we never
    corrupt previous checkpoints if the current one fails.

    Parameters
    ----------
    obj: object
        object to pickle
    path: str
        path to the output file
    compression: bool
        if true pickle will be compressed
    """
    temp_storage = path + ".relatively_safe"
    if compression:
        # Using gzip here would be simpler, but the size is limited to 2GB
        with tempfile.NamedTemporaryFile() as uncompressed_file:
            pickle.dump(obj, uncompressed_file)
            uncompressed_file.file.flush()
            with zipfile.ZipFile(temp_storage, "w", compression=zipfile.ZIP_DEFLATED) as myzip:
                myzip.write(uncompressed_file.name, "data")
    else:
        with open(temp_storage, "wb") as f:
            pickle.dump(obj, f)
    os.rename(temp_storage, path)
def set_global_seeds(i)
Expand source code
def set_global_seeds(i):
    try:
        import MPI
        rank = MPI.COMM_WORLD.Get_rank()
    except ImportError:
        rank = 0

    myseed = i  + 1000 * rank if i is not None else None
    try:
        import tensorflow as tf
        tf.set_random_seed(myseed)
    except ImportError:
        pass
    np.random.seed(myseed)
    random.seed(myseed)
def zipsame(*seqs)
Expand source code
def zipsame(*seqs):
    L = len(seqs[0])
    assert all(len(seq) == L for seq in seqs[1:])
    return zip(*seqs)

Classes

class EzPickle (*args, **kwargs)

Objects that are pickled and unpickled via their constructor arguments.

Example usage:

class Dog(Animal, EzPickle):
    def __init__(self, furcolor, tailkind="bushy"):
        Animal.__init__()
        EzPickle.__init__(furcolor, tailkind)
        ...

When this object is unpickled, a new Dog will be constructed by passing the provided furcolor and tailkind into the constructor. However, philosophers are still not sure whether it is still the same dog.

This is generally needed only for environments which wrap C/C++ code, such as MuJoCo and Atari.

Expand source code
class EzPickle(object):
    """Objects that are pickled and unpickled via their constructor
    arguments.

    Example usage:

        class Dog(Animal, EzPickle):
            def __init__(self, furcolor, tailkind="bushy"):
                Animal.__init__()
                EzPickle.__init__(furcolor, tailkind)
                ...

    When this object is unpickled, a new Dog will be constructed by passing the provided
    furcolor and tailkind into the constructor. However, philosophers are still not sure
    whether it is still the same dog.

    This is generally needed only for environments which wrap C/C++ code, such as MuJoCo
    and Atari.
    """

    def __init__(self, *args, **kwargs):
        self._ezpickle_args = args
        self._ezpickle_kwargs = kwargs

    def __getstate__(self):
        return {"_ezpickle_args": self._ezpickle_args, "_ezpickle_kwargs": self._ezpickle_kwargs}

    def __setstate__(self, d):
        out = type(self)(*d["_ezpickle_args"], **d["_ezpickle_kwargs"])
        self.__dict__.update(out.__dict__)
class RunningAvg (gamma, init_value=None)

Keep a running estimate of a quantity. This is a bit like mean but more sensitive to recent changes.

Parameters

gamma : float
Must be between 0 and 1, where 0 is the most sensitive to recent changes.
init_value : float or None
Initial value of the estimate. If None, it will be set on the first update.
Expand source code
class RunningAvg(object):
    def __init__(self, gamma, init_value=None):
        """Keep a running estimate of a quantity. This is a bit like mean
        but more sensitive to recent changes.

        Parameters
        ----------
        gamma: float
            Must be between 0 and 1, where 0 is the most sensitive to recent
            changes.
        init_value: float or None
            Initial value of the estimate. If None, it will be set on the first update.
        """
        self._value = init_value
        self._gamma = gamma

    def update(self, new_val):
        """Update the estimate.

        Parameters
        ----------
        new_val: float
            new observated value of estimated quantity.
        """
        if self._value is None:
            self._value = new_val
        else:
            self._value = self._gamma * self._value + (1.0 - self._gamma) * new_val

    def __float__(self):
        """Get the current estimate"""
        return self._value

Methods

def update(self, new_val)

Update the estimate.

Parameters

new_val : float
new observated value of estimated quantity.
Expand source code
def update(self, new_val):
    """Update the estimate.

    Parameters
    ----------
    new_val: float
        new observated value of estimated quantity.
    """
    if self._value is None:
        self._value = new_val
    else:
        self._value = self._gamma * self._value + (1.0 - self._gamma) * new_val