mirror of
https://github.com/zebrajr/faceswap.git
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174 lines
3.9 KiB
ReStructuredText
Executable File
174 lines
3.9 KiB
ReStructuredText
Executable File
*************
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model package
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*************
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The Model Package handles interfacing with the neural network backend and holds custom objects.
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.. contents:: Contents
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:local:
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model.backup_restore module
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===========================
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.. automodule:: lib.model.backup_restore
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:members:
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:undoc-members:
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:show-inheritance:
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model.initializers module
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=========================
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.initializers.ConvolutionAware
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~lib.model.initializers.ICNR
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~lib.model.initializers.compute_fans
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.. automodule:: lib.model.initializers
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:members:
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:undoc-members:
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:show-inheritance:
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model.layers module
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===================
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.layers.GlobalMinPooling2D
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~lib.model.layers.GlobalStdDevPooling2D
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~lib.model.layers.L2_normalize
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~lib.model.layers.PixelShuffler
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~lib.model.layers.ReflectionPadding2D
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~lib.model.layers.SubPixelUpscaling
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.. automodule:: lib.model.layers
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:members:
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:undoc-members:
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:show-inheritance:
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model.losses module
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===================
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The losses listed here are generated from the docstrings in :mod:`lib.model.losses_tf`, however
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the functions are exactly the same for :mod:`lib.model.losses_plaid`. The correct loss module will
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be imported as :mod:`lib.model.losses` depending on the backend in use.
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.loss.loss_tf.FocalFrequencyLoss
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~lib.model.loss.loss_tf.GeneralizedLoss
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~lib.model.loss.loss_tf.GradientLoss
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~lib.model.loss.loss_tf.LaplacianPyramidLoss
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~lib.model.loss.loss_tf.LInfNorm
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~lib.model.loss.loss_tf.LossWrapper
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~lib.model.loss.feature_loss_tf.LPIPSLoss
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~lib.model.loss.perceptual_loss_tf.DSSIMObjective
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~lib.model.loss.perceptual_loss_tf.GMSDLoss
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~lib.model.loss.perceptual_loss_tf.LDRFLIPLoss
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~lib.model.loss.perceptual_loss_tf.MSSIMLoss
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.. automodule:: lib.model.loss.loss_tf
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:members:
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:undoc-members:
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:show-inheritance:
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.. automodule:: lib.model.loss.feature_loss_tf
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:members:
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:undoc-members:
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:show-inheritance:
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.. automodule:: lib.model.loss.perceptual_loss_tf
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:members:
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:undoc-members:
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:show-inheritance:
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model.nets module
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=================
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.nets.AlexNet
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~lib.model.nets.SqueezeNet
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.. automodule:: lib.model.nets
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:members:
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:undoc-members:
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:show-inheritance:
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model.nn_blocks module
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======================
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.nn_blocks.Conv2D
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~lib.model.nn_blocks.Conv2DBlock
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~lib.model.nn_blocks.Conv2DOutput
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~lib.model.nn_blocks.ResidualBlock
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~lib.model.nn_blocks.SeparableConv2DBlock
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~lib.model.nn_blocks.Upscale2xBlock
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~lib.model.nn_blocks.UpscaleBlock
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~lib.model.nn_blocks.set_config
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.. automodule:: lib.model.nn_blocks
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:members:
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:undoc-members:
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:show-inheritance:
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model.normalization module
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==========================
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.normalization.InstanceNormalization
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.. automodule:: lib.model.normalization
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:members:
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:undoc-members:
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:show-inheritance:
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model.optimizers module
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=======================
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The optimizers listed here are generated from the docstrings in :mod:`lib.model.optimizers_tf`, however
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the functions are excactly the same for :mod:`lib.model.optimizers_plaid`. The correct optimizers module will
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be imported as :mod:`lib.model.optimizers` depending on the backend in use.
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.. rubric:: Module Summary
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.. autosummary::
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:nosignatures:
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~lib.model.optimizers_tf.AdaBelief
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.. automodule:: lib.model.optimizers_tf
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:members:
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:undoc-members:
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:show-inheritance:
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model.session module
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=====================
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.. automodule:: lib.model.session
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:members:
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:undoc-members:
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:show-inheritance:
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