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torzdf
837bc2d51d
* FaceSwap 3 (#1515) * Update extract pipeline * Update requirements + setup for nvidia * Remove allow-growth option * tf.keras to keras updates * lib.model.losses - Port + fix all loss functions for Keras3 * lib.model - port initializers, layers. normalization to Keras3 * lib.model.autoclip to Keras 3 * Update mixed precision layer storage * model file to .keras format * Restructure nn_blocks to initialize layers in __init__ * Tensorboard - Trainer: Add Torch compatible Tensorboard callbacks - GUI event reader remove TF dependency * Loss logging - Flush TB logs on save - Replace TB live iterator for GUI * Backup models on total loss drop rather than per side * Update all models to Keras3 Compat * Remove lib.model.session * Update clip ViT to Keras 3 * plugins.extract.mask.unet-dfl - Fix for Keras3/Torch backend * Port AdaBelief to Keras 3 * setup.py: - Add --dev flag for dev tool install * Fix Keras 3 syntax * Fix LR Finder for Keras 3 * Fix mixed precision switching for Keras 3 * Add more optimizers + open up config setting * train: Remove updating FS1 weights to FS2 models * Alignments: Remove support for legacy .json files * tools.model: - Remove TF Saved Format saving - Fix Backup/Restore + Nan-Scan * Fix inference model creation for Keras 3 * Preview tool: Fix for Keras3 * setup.py: Configure keras backend * train: Migration of FS2 models to FS3 * Training: Default coverage to 100% * Remove DirectML backend * Update setup for MacOS * GUI: Force line reading to UTF-8 * Remove redundant Tensorflow references * Remove redundant code * Legacy model loading: Fix TFLamdaOp scalar ops and DepthwiseConv2D * Add vertical offset option for training * Github actions: Add more python versions * Add python version to workflow names * Github workflow: Exclude Python 3.12 for macOS * Implement custom training loop * Fs3 - Add RTX5xxx and ROCm 6.1-6.4 support (#1511) * setup.py: Add Cuda/ROCm version select options * bump minimum python version to 3.11 * Switch from setup.cgf to pyproject.toml * Documentation: Update all docs to use automodapi * Allow sysinfo to run with missing packages + correctly install tk under Linux * Bugfix: dot naming convention in clip models * lib.config: Centralise globally rather than passing as object - Add torch DataParallel for multi-gpu training - GUI: Group switches together when generating cli args - CLI: Remove deprecated multi-character argparse args - Refactor: - Centralise tensorboard reading/writing + unit tests - Create trainer plugin interfaces + add original + distributed * Update installers
65 lines
2.4 KiB
Python
65 lines
2.4 KiB
Python
#!/usr/bin/env python3
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""" Command Line Arguments for tools """
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import gettext
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import typing as T
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from lib.cli.args import FaceSwapArgs
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from lib.cli.actions import DirFullPaths, Radio
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from lib.utils import get_module_objects
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# LOCALES
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_LANG = gettext.translation("tools.restore.cli", localedir="locales", fallback=True)
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_ = _LANG.gettext
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_HELPTEXT = _("This tool lets you perform actions on saved Faceswap models.")
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class ModelArgs(FaceSwapArgs):
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""" Class to perform actions on model files """
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@staticmethod
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def get_info() -> str:
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""" Return command information """
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return _("A tool for performing actions on Faceswap trained model files")
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@staticmethod
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def get_argument_list() -> list[dict[str, T.Any]]:
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""" Put the arguments in a list so that they are accessible from both argparse and gui """
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argument_list = []
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argument_list.append({
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"opts": ("-m", "--model-dir"),
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"action": DirFullPaths,
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"dest": "model_dir",
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"required": True,
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"help": _(
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"Model directory. A directory containing the model you wish to perform an action "
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"on.")})
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argument_list.append({
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"opts": ("-j", "--job"),
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"action": Radio,
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"type": str,
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"choices": ("inference", "nan-scan", "restore"),
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"required": True,
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"help": _(
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"R|Choose which action you want to perform."
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"\nL|'inference' - Create an inference only copy of the model. Strips any layers "
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"from the model which are only required for training. NB: This is for exporting "
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"the model for use in external applications. Inference generated models cannot be "
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"used within Faceswap. See the 'format' option for specifying the model output "
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"format."
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"\nL|'nan-scan' - Scan the model file for NaNs or Infs (invalid data)."
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"\nL|'restore' - Restore a model from backup.")})
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argument_list.append({
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"opts": ("-s", "--swap-model"),
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"action": "store_true",
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"dest": "swap_model",
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"default": False,
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"group": _("inference"),
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"help": _(
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"Only used for 'inference' job. Generate the inference model for B -> A instead "
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"of A -> B.")})
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return argument_list
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__all__ = get_module_objects(__name__)
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