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#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""This file contains code related to drift check baselines"""
from __future__ import absolute_import
from typing import Optional
from sagemaker.model_metrics import MetricsSource, FileSource
class DriftCheckBaselines(object):
"""Accepts drift check baselines parameters for conversion to request dict."""
def __init__(
self,
model_statistics: Optional[MetricsSource] = None,
model_constraints: Optional[MetricsSource] = None,
model_data_statistics: Optional[MetricsSource] = None,
model_data_constraints: Optional[MetricsSource] = None,
bias_config_file: Optional[FileSource] = None,
bias_pre_training_constraints: Optional[MetricsSource] = None,
bias_post_training_constraints: Optional[MetricsSource] = None,
explainability_constraints: Optional[MetricsSource] = None,
explainability_config_file: Optional[FileSource] = None,
):
"""Initialize a ``DriftCheckBaselines`` instance and turn parameters into dict.
Args:
model_statistics (MetricsSource): A metric source object that represents
model statistics (default: None).
model_constraints (MetricsSource): A metric source object that represents
model constraints (default: None).
model_data_statistics (MetricsSource): A metric source object that represents
model data statistics (default: None).
model_data_constraints (MetricsSource): A metric source object that represents
model data constraints (default: None).
bias_config_file (FileSource): A file source object that represents bias config
(default: None).
bias_pre_training_constraints (MetricsSource):
A metric source object that represents Pre-training constraints (default: None).
bias_post_training_constraints (MetricsSource):
A metric source object that represents Post-training constraits (default: None).
explainability_constraints (MetricsSource):
A metric source object that represents explainability constraints (default: None).
explainability_config_file (FileSource): A file source object that represents
explainability config (default: None).
"""
self.model_statistics = model_statistics
self.model_constraints = model_constraints
self.model_data_statistics = model_data_statistics
self.model_data_constraints = model_data_constraints
self.bias_config_file = bias_config_file
self.bias_pre_training_constraints = bias_pre_training_constraints
self.bias_post_training_constraints = bias_post_training_constraints
self.explainability_constraints = explainability_constraints
self.explainability_config_file = explainability_config_file
def _to_request_dict(self):
"""Generates a request dictionary using the parameters provided to the class."""
drift_check_baselines_request = {}
model_quality = {}
if self.model_statistics is not None:
model_quality["Statistics"] = self.model_statistics._to_request_dict()
if self.model_constraints is not None:
model_quality["Constraints"] = self.model_constraints._to_request_dict()
if model_quality:
drift_check_baselines_request["ModelQuality"] = model_quality
model_data_quality = {}
if self.model_data_statistics is not None:
model_data_quality["Statistics"] = self.model_data_statistics._to_request_dict()
if self.model_data_constraints is not None:
model_data_quality["Constraints"] = self.model_data_constraints._to_request_dict()
if model_data_quality:
drift_check_baselines_request["ModelDataQuality"] = model_data_quality
bias = {}
if self.bias_config_file is not None:
bias["ConfigFile"] = self.bias_config_file._to_request_dict()
if self.bias_pre_training_constraints is not None:
bias["PreTrainingConstraints"] = self.bias_pre_training_constraints._to_request_dict()
if self.bias_post_training_constraints is not None:
bias["PostTrainingConstraints"] = self.bias_post_training_constraints._to_request_dict()
if bias:
drift_check_baselines_request["Bias"] = bias
explainability = {}
if self.explainability_constraints is not None:
explainability["Constraints"] = self.explainability_constraints._to_request_dict()
if self.explainability_config_file is not None:
explainability["ConfigFile"] = self.explainability_config_file._to_request_dict()
if explainability:
drift_check_baselines_request["Explainability"] = explainability
return drift_check_baselines_request
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