File size: 2,512 Bytes
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 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import pytest
from fairlearn.postprocessing import ThresholdOptimizer
from fairlearn.reductions import ExponentiatedGradient, GridSearch, EqualizedOdds, \
DemographicParity
try:
from tempeh.execution.azureml.workspace import get_workspace
except ImportError:
raise Exception("fairlearn performance tests require azureml-sdk to be installed.")
from environment_setup import build_package
THRESHOLD_OPTIMIZER = ThresholdOptimizer.__name__
EXPONENTIATED_GRADIENT = ExponentiatedGradient.__name__
GRID_SEARCH = GridSearch.__name__
MEMORY = "memory"
TIME = "time"
ADULT_UCI = 'adult_uci'
COMPAS = 'compas'
RBM_SVM = 'rbm_svm'
DECISION_TREE_CLASSIFIER = 'decision_tree_classifier'
DATASETS = [ADULT_UCI, COMPAS]
PREDICTORS = [RBM_SVM, DECISION_TREE_CLASSIFIER]
MITIGATORS = [THRESHOLD_OPTIMIZER, EXPONENTIATED_GRADIENT, GRID_SEARCH]
class PerfTestConfiguration:
def __init__(self, dataset, predictor, mitigator, disparity_metric):
self.dataset = dataset
self.predictor = predictor
self.mitigator = mitigator
self.disparity_metric = disparity_metric
def __repr__(self):
return "[dataset: {}, predictor: {}, mitigator: {}, disparity_metric: {}]" \
.format(self.dataset, self.predictor, self.mitigator, self.disparity_metric)
def get_all_perf_test_configurations():
perf_test_configurations = []
for dataset in DATASETS:
for predictor in PREDICTORS:
for mitigator in MITIGATORS:
if mitigator == THRESHOLD_OPTIMIZER:
disparity_metrics = ["equalized_odds", "demographic_parity"]
elif mitigator == EXPONENTIATED_GRADIENT:
disparity_metrics = [EqualizedOdds.__name__, DemographicParity.__name__]
elif mitigator == GRID_SEARCH:
disparity_metrics = [EqualizedOdds.__name__, DemographicParity.__name__]
else:
raise Exception("Unknown mitigator {}".format(mitigator))
for disparity_metric in disparity_metrics:
perf_test_configurations.append(
PerfTestConfiguration(dataset, predictor, mitigator, disparity_metric))
return perf_test_configurations
@pytest.fixture(scope="session")
def workspace():
return get_workspace()
@pytest.fixture(scope="session")
def wheel_file():
return build_package()
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