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fc0f7bd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""Tools for analyzing and mitigating disparity in Machine Learning models."""
import os
import sys
# Finesse the version
_FAIRLEARN_DEV_VERSION_ENV_VAR = "FAIRLEARN_DEV_VERSION"
_base_version = "0.4.3"
_dev_version = ""
if _FAIRLEARN_DEV_VERSION_ENV_VAR in os.environ.keys():
dev_version_string = os.environ[_FAIRLEARN_DEV_VERSION_ENV_VAR]
try:
dev_version_value = int(dev_version_string)
if dev_version_value >= 0:
_dev_version = ".dev{0}".format(dev_version_value)
else:
msg = "Value of {0} was not greater than or equal to zero. Ignoring"
print(msg.format(_FAIRLEARN_DEV_VERSION_ENV_VAR), file=sys.stderr)
except ValueError:
msg = "Value of {0} in {1} did not parse to integer. Ignoring"
print(msg.format(dev_version_string, _FAIRLEARN_DEV_VERSION_ENV_VAR), file=sys.stderr)
__name__ = "fairlearn"
__version__ = "{0}{1}".format(_base_version, _dev_version)
# Common strings
_NO_PREDICT_BEFORE_FIT = "Must call fit before attempting to make predictions"
# Setup logging infrastructure
import logging # noqa: E402
import atexit # noqa: E402
# Only log to disk if environment variable FAIRLEARN_LOGS specified
fairlearn_logs = os.environ.get('FAIRLEARN_LOGS')
if fairlearn_logs is not None:
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
os.makedirs(os.path.dirname(fairlearn_logs), exist_ok=True)
handler = logging.FileHandler(fairlearn_logs, mode='w')
handler.setLevel(logging.INFO)
logger.addHandler(handler)
logger.info('Initializing logging file for fairlearn')
def close_handler(): # noqa: D103
handler.close()
logger.removeHandler(handler)
atexit.register(close_handler)
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