faceswap/docs/full/lib/model.rst
2022-07-17 17:54:22 +01:00

174 lines
3.9 KiB
ReStructuredText
Executable File

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