wehub-resource-sync
145 lines
6.1 KiB
Python
145 lines
6.1 KiB
Python
"""DO NOT EDIT.
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This file was autogenerated. Do not edit it by hand,
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since your modifications would be overwritten.
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"""
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from keras.src.losses.losses import binary_crossentropy as binary_crossentropy
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from keras.src.losses.losses import (
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binary_focal_crossentropy as binary_focal_crossentropy,
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)
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from keras.src.losses.losses import (
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categorical_crossentropy as categorical_crossentropy,
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)
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from keras.src.losses.losses import (
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categorical_focal_crossentropy as categorical_focal_crossentropy,
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)
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from keras.src.losses.losses import categorical_hinge as categorical_hinge
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from keras.src.losses.losses import hinge as hinge
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from keras.src.losses.losses import huber as huber
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from keras.src.losses.losses import kl_divergence as kl_divergence
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from keras.src.losses.losses import log_cosh as log_cosh
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from keras.src.losses.losses import mean_absolute_error as mean_absolute_error
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from keras.src.losses.losses import (
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mean_absolute_percentage_error as mean_absolute_percentage_error,
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)
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from keras.src.losses.losses import mean_squared_error as mean_squared_error
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from keras.src.losses.losses import (
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mean_squared_logarithmic_error as mean_squared_logarithmic_error,
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)
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from keras.src.losses.losses import poisson as poisson
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from keras.src.losses.losses import (
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sparse_categorical_crossentropy as sparse_categorical_crossentropy,
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)
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from keras.src.losses.losses import squared_hinge as squared_hinge
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from keras.src.metrics import deserialize as deserialize
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from keras.src.metrics import get as get
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from keras.src.metrics import serialize as serialize
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from keras.src.metrics.accuracy_metrics import Accuracy as Accuracy
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from keras.src.metrics.accuracy_metrics import BinaryAccuracy as BinaryAccuracy
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from keras.src.metrics.accuracy_metrics import (
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CategoricalAccuracy as CategoricalAccuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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SparseCategoricalAccuracy as SparseCategoricalAccuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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SparseTopKCategoricalAccuracy as SparseTopKCategoricalAccuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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TopKCategoricalAccuracy as TopKCategoricalAccuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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binary_accuracy as binary_accuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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categorical_accuracy as categorical_accuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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sparse_categorical_accuracy as sparse_categorical_accuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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sparse_top_k_categorical_accuracy as sparse_top_k_categorical_accuracy,
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)
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from keras.src.metrics.accuracy_metrics import (
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top_k_categorical_accuracy as top_k_categorical_accuracy,
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)
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from keras.src.metrics.confusion_metrics import AUC as AUC
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from keras.src.metrics.confusion_metrics import FalseNegatives as FalseNegatives
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from keras.src.metrics.confusion_metrics import FalsePositives as FalsePositives
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from keras.src.metrics.confusion_metrics import Precision as Precision
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from keras.src.metrics.confusion_metrics import (
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PrecisionAtRecall as PrecisionAtRecall,
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)
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from keras.src.metrics.confusion_metrics import Recall as Recall
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from keras.src.metrics.confusion_metrics import (
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RecallAtPrecision as RecallAtPrecision,
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)
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from keras.src.metrics.confusion_metrics import (
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SensitivityAtSpecificity as SensitivityAtSpecificity,
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)
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from keras.src.metrics.confusion_metrics import (
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SpecificityAtSensitivity as SpecificityAtSensitivity,
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)
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from keras.src.metrics.confusion_metrics import TrueNegatives as TrueNegatives
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from keras.src.metrics.confusion_metrics import TruePositives as TruePositives
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from keras.src.metrics.correlation_metrics import (
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ConcordanceCorrelation as ConcordanceCorrelation,
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)
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from keras.src.metrics.correlation_metrics import (
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PearsonCorrelation as PearsonCorrelation,
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)
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from keras.src.metrics.correlation_metrics import (
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concordance_correlation as concordance_correlation,
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)
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from keras.src.metrics.correlation_metrics import (
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pearson_correlation as pearson_correlation,
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)
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from keras.src.metrics.f_score_metrics import F1Score as F1Score
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from keras.src.metrics.f_score_metrics import FBetaScore as FBetaScore
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from keras.src.metrics.hinge_metrics import CategoricalHinge as CategoricalHinge
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from keras.src.metrics.hinge_metrics import Hinge as Hinge
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from keras.src.metrics.hinge_metrics import SquaredHinge as SquaredHinge
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from keras.src.metrics.iou_metrics import BinaryIoU as BinaryIoU
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from keras.src.metrics.iou_metrics import IoU as IoU
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from keras.src.metrics.iou_metrics import MeanIoU as MeanIoU
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from keras.src.metrics.iou_metrics import OneHotIoU as OneHotIoU
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from keras.src.metrics.iou_metrics import OneHotMeanIoU as OneHotMeanIoU
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from keras.src.metrics.metric import Metric as Metric
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from keras.src.metrics.probabilistic_metrics import (
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BinaryCrossentropy as BinaryCrossentropy,
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)
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from keras.src.metrics.probabilistic_metrics import (
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CategoricalCrossentropy as CategoricalCrossentropy,
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)
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from keras.src.metrics.probabilistic_metrics import KLDivergence as KLDivergence
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from keras.src.metrics.probabilistic_metrics import Poisson as Poisson
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from keras.src.metrics.probabilistic_metrics import (
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SparseCategoricalCrossentropy as SparseCategoricalCrossentropy,
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)
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from keras.src.metrics.reduction_metrics import Mean as Mean
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from keras.src.metrics.reduction_metrics import (
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MeanMetricWrapper as MeanMetricWrapper,
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)
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from keras.src.metrics.reduction_metrics import Sum as Sum
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from keras.src.metrics.regression_metrics import (
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CosineSimilarity as CosineSimilarity,
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)
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from keras.src.metrics.regression_metrics import LogCoshError as LogCoshError
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from keras.src.metrics.regression_metrics import (
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MeanAbsoluteError as MeanAbsoluteError,
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)
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from keras.src.metrics.regression_metrics import (
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MeanAbsolutePercentageError as MeanAbsolutePercentageError,
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)
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from keras.src.metrics.regression_metrics import (
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MeanSquaredError as MeanSquaredError,
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)
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from keras.src.metrics.regression_metrics import (
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MeanSquaredLogarithmicError as MeanSquaredLogarithmicError,
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)
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from keras.src.metrics.regression_metrics import R2Score as R2Score
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from keras.src.metrics.regression_metrics import (
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RootMeanSquaredError as RootMeanSquaredError,
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)
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