Source code for azure.cognitiveservices.vision.customvision.training.models.iteration_performance_py3
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.serialization import Model
[docs]class IterationPerformance(Model):
"""Represents the detailed performance data for a trained iteration.
Variables are only populated by the server, and will be ignored when
sending a request.
:ivar per_tag_performance: Gets the per-tag performance details for this
iteration
:vartype per_tag_performance:
list[~azure.cognitiveservices.vision.customvision.training.models.TagPerformance]
:ivar precision: Gets the precision
:vartype precision: float
:ivar precision_std_deviation: Gets the standard deviation for the
precision
:vartype precision_std_deviation: float
:ivar recall: Gets the recall
:vartype recall: float
:ivar recall_std_deviation: Gets the standard deviation for the recall
:vartype recall_std_deviation: float
:ivar average_precision: Gets the average precision when applicable
:vartype average_precision: float
"""
_validation = {
'per_tag_performance': {'readonly': True},
'precision': {'readonly': True},
'precision_std_deviation': {'readonly': True},
'recall': {'readonly': True},
'recall_std_deviation': {'readonly': True},
'average_precision': {'readonly': True},
}
_attribute_map = {
'per_tag_performance': {'key': 'perTagPerformance', 'type': '[TagPerformance]'},
'precision': {'key': 'precision', 'type': 'float'},
'precision_std_deviation': {'key': 'precisionStdDeviation', 'type': 'float'},
'recall': {'key': 'recall', 'type': 'float'},
'recall_std_deviation': {'key': 'recallStdDeviation', 'type': 'float'},
'average_precision': {'key': 'averagePrecision', 'type': 'float'},
}
def __init__(self, **kwargs) -> None:
super(IterationPerformance, self).__init__(**kwargs)
self.per_tag_performance = None
self.precision = None
self.precision_std_deviation = None
self.recall = None
self.recall_std_deviation = None
self.average_precision = None