wehub-resource-sync
83 lines
3.6 KiB
Python
83 lines
3.6 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 import deserialize as deserialize
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from keras.src.losses import get as get
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from keras.src.losses import serialize as serialize
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from keras.src.losses.loss import Loss as Loss
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from keras.src.losses.losses import CTC as CTC
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from keras.src.losses.losses import BinaryCrossentropy as BinaryCrossentropy
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from keras.src.losses.losses import (
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BinaryFocalCrossentropy as BinaryFocalCrossentropy,
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)
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from keras.src.losses.losses import (
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CategoricalCrossentropy as CategoricalCrossentropy,
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)
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from keras.src.losses.losses import (
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CategoricalFocalCrossentropy as CategoricalFocalCrossentropy,
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)
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from keras.src.losses.losses import (
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CategoricalGeneralizedCrossEntropy as CategoricalGeneralizedCrossEntropy,
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)
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from keras.src.losses.losses import CategoricalHinge as CategoricalHinge
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from keras.src.losses.losses import Circle as Circle
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from keras.src.losses.losses import CosineSimilarity as CosineSimilarity
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from keras.src.losses.losses import Dice as Dice
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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 KLDivergence as KLDivergence
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from keras.src.losses.losses import LogCosh as LogCosh
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from keras.src.losses.losses import MeanAbsoluteError as MeanAbsoluteError
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from keras.src.losses.losses import (
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MeanAbsolutePercentageError as MeanAbsolutePercentageError,
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)
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from keras.src.losses.losses import MeanSquaredError as MeanSquaredError
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from keras.src.losses.losses import (
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MeanSquaredLogarithmicError as MeanSquaredLogarithmicError,
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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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SparseCategoricalCrossentropy as SparseCategoricalCrossentropy,
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)
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from keras.src.losses.losses import SquaredHinge as SquaredHinge
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from keras.src.losses.losses import Tversky as Tversky
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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 (
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categorical_generalized_cross_entropy as categorical_generalized_cross_entropy,
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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 circle as circle
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from keras.src.losses.losses import cosine_similarity as cosine_similarity
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from keras.src.losses.losses import ctc as ctc
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from keras.src.losses.losses import dice as dice
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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.losses.losses import tversky as tversky
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