2 commits

Author	SHA1	Message	Date
torzdf	d8557c1970	Faceswap 2.0 (#1045) ... * Core Updates - Remove lib.utils.keras_backend_quiet and replace with get_backend() where relevant - Document lib.gpu_stats and lib.sys_info - Remove call to GPUStats.is_plaidml from convert and replace with get_backend() - lib.gui.menu - typofix * Update Dependencies Bump Tensorflow Version Check * Port extraction to tf2 * Add custom import finder for loading Keras or tf.keras depending on backend * Add `tensorflow` to KerasFinder search path * Basic TF2 training running * model.initializers - docstring fix * Fix and pass tests for tf2 * Replace Keras backend tests with faceswap backend tests * Initial optimizers update * Monkey patch tf.keras optimizer * Remove custom Adam Optimizers and Memory Saving Gradients * Remove multi-gpu option. Add Distribution to cli * plugins.train.model._base: Add Mirror, Central and Default distribution strategies * Update tensorboard kwargs for tf2 * Penalized Loss - Fix for TF2 and AMD * Fix syntax for tf2.1 * requirements typo fix * Explicit None for clipnorm if using a distribution strategy * Fix penalized loss for distribution strategies * Update Dlight * typo fix * Pin to TF2.2 * setup.py - Install tensorflow from pip if not available in Conda * Add reduction options and set default for mirrored distribution strategy * Explicitly use default strategy rather than nullcontext * lib.model.backup_restore documentation * Remove mirrored strategy reduction method and default based on OS * Initial restructure - training * Remove PingPong Start model.base refactor * Model saving and resuming enabled * More tidying up of model.base * Enable backup and snapshotting * Re-enable state file Remove loss names from state file Fix print loss function Set snapshot iterations correctly * Revert original model to Keras Model structure rather than custom layer Output full model and sub model summary Change NNBlocks to callables rather than custom keras layers * Apply custom Conv2D layer * Finalize NNBlock restructure Update Dfaker blocks * Fix reloading model under a different distribution strategy * Pass command line arguments through to trainer * Remove training_opts from model and reference params directly * Tidy up model __init__ * Re-enable tensorboard logging Suppress "Model Not Compiled" warning * Fix timelapse * lib.model.nnblocks - Bugfix residual block Port dfaker bugfix original * dfl-h128 ported * DFL SAE ported * IAE Ported * dlight ported * port lightweight * realface ported * unbalanced ported * villain ported * lib.cli.args - Update Batchsize + move allow_growth to config * Remove output shape definition Get image sizes per side rather than globally * Strip mask input from encoder * Fix learn mask and output learned mask to preview * Trigger Allow Growth prior to setting strategy * Fix GUI Graphing * GUI - Display batchsize correctly + fix training graphs * Fix penalized loss * Enable mixed precision training * Update analysis displayed batch to match input * Penalized Loss - Multi-GPU Fix * Fix all losses for TF2 * Fix Reflect Padding * Allow different input size for each side of the model * Fix conv-aware initialization on reload * Switch allow_growth order * Move mixed_precision to cli * Remove distrubution strategies * Compile penalized loss sub-function into LossContainer * Bump default save interval to 250 Generate preview on first iteration but don't save Fix iterations to start at 1 instead of 0 Remove training deprecation warnings Bump some scripts.train loglevels * Add ability to refresh preview on demand on pop-up window * Enable refresh of training preview from GUI * Fix Convert Debug logging in Initializers * Fix Preview Tool * Update Legacy TF1 weights to TF2 Catch stats error on loading stats with missing logs * lib.gui.popup_configure - Make more responsive + document * Multiple Outputs supported in trainer Original Model - Mask output bugfix * Make universal inference model for convert Remove scaling from penalized mask loss (now handled at input to y_true) * Fix inference model to work properly with all models * Fix multi-scale output for convert * Fix clipnorm issue with distribution strategies Edit error message on OOM * Update plaidml losses * Add missing file * Disable gmsd loss for plaidnl * PlaidML - Basic training working * clipnorm rewriting for mixed-precision * Inference model creation bugfixes * Remove debug code * Bugfix: Default clipnorm to 1.0 * Remove all mask inputs from training code * Remove mask inputs from convert * GUI - Analysis Tab - Docstrings * Fix rate in totals row * lib.gui - Only update display pages if they have focus * Save the model on first iteration * plaidml - Fix SSIM loss with penalized loss * tools.alignments - Remove manual and fix jobs * GUI - Remove case formatting on help text * gui MultiSelect custom widget - Set default values on init * vgg_face2 - Move to plugins.extract.recognition and use plugins._base base class cli - Add global GPU Exclude Option tools.sort - Use global GPU Exlude option for backend lib.model.session - Exclude all GPUs when running in CPU mode lib.cli.launcher - Set backend to CPU mode when all GPUs excluded * Cascade excluded devices to GPU Stats * Explicit GPU selection for Train and Convert * Reduce Tensorflow Min GPU Multiprocessor Count to 4 * remove compat.v1 code from extract * Force TF to skip mixed precision compatibility check if GPUs have been filtered * Add notes to config for non-working AMD losses * Rasie error if forcing extract to CPU mode * Fix loading of legace dfl-sae weights + dfl-sae typo fix * Remove unused requirements Update sphinx requirements Fix broken rst file locations * docs: lib.gui.display * clipnorm amd condition check * documentation - gui.display_analysis * Documentation - gui.popup_configure * Documentation - lib.logger * Documentation - lib.model.initializers * Documentation - lib.model.layers * Documentation - lib.model.losses * Documentation - lib.model.nn_blocks * Documetation - lib.model.normalization * Documentation - lib.model.session * Documentation - lib.plaidml_stats * Documentation: lib.training_data * Documentation: lib.utils * Documentation: plugins.train.model._base * GUI Stats: prevent stats from using GPU * Documentation - Original Model * Documentation: plugins.model.trainer._base * linting * unit tests: initializers + losses * unit tests: nn_blocks * bugfix - Exclude gpu devices in train, not include * Enable Exclude-Gpus in Extract * Enable exclude gpus in tools * Disallow multiple plugin types in a single model folder * Automatically add exclude_gpus argument in for cpu backends * Cpu backend fixes * Relax optimizer test threshold * Default Train settings - Set mask to Extended * Update Extractor cli help text Update to Python 3.8 * Fix FAN to run on CPU * lib.plaidml_tools - typofix * Linux installer - check for curl * linux installer - typo fix	2020-08-12 10:36:41 +01:00
torzdf	815c843f63	Simple backend unit tests (#1020) ... * Add simple backend tests for lib.model * Document lib.model * Fix GMSD Loss for AMD * Remove obsolete code from lib.model	2020-05-12 23:46:04 +01:00