I've been training a DFL SAE model on AWS with a Tesla T4 16GB GPU because my measly R9 390X 8GB can't handle anything above a batch size of 8. My plan was to train the model up to around 200K iterations on AWS and then copy it onto my PC to continue fit training and convert various other clips with a lower BS.
I've spent a bunch on AWS services to get the model to around 150K iterations so far, and decided to try training on my PC using copies of the AWS snapshots. I thought this should be no problem, except the trainer immediately crashes no matter which snapshot I use. I even checked all my training settings to make sure they match the AWS trainer.
My PC does just fine, however, if I use the same settings and training sets but with a model that was never trained on AWS. Am I doing something wrong or is switching a model from one GPU to another not supported? I also get a crash when trying to convert using the AWS model on my PC. I'm really hoping I won't have to spend more on AWS every time I want to use this model
Any help is appreciated.
Code: Select all
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.realface', title: 'input_size', datatype: '<class 'int'>', default: '64', info: 'Resolution (in pixels) of the input image to train on.\nBE AWARE Larger resolution will dramatically increase VRAM requirements.\nHigher resolutions may increase prediction accuracy, but does not effect the resulting output size.\nMust be between 64 and 128 and be divisible by 16.', rounding: '16', min_max: (64, 128), choices: [], gui_radio: False, fixed: True, group: size)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.realface', title: 'output_size', datatype: '<class 'int'>', default: '128', info: 'Output image resolution (in pixels).\nBe aware that larger resolution will increase VRAM requirements.\nNB: Must be between 64 and 256 and be divisible by 16.', rounding: '16', min_max: (64, 256), choices: [], gui_radio: False, fixed: True, group: size)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.realface', title: 'dense_nodes', datatype: '<class 'int'>', default: '1536', info: 'Number of nodes for decoder. Might affect your model's ability to learn in general.\nNote that: Lower values will affect the ability to predict details.', rounding: '64', min_max: (768, 2048), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.realface', title: 'complexity_encoder', datatype: '<class 'int'>', default: '128', info: 'Encoder Convolution Layer Complexity. sensible ranges: 128 to 150.', rounding: '4', min_max: (96, 160), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.realface', title: 'complexity_decoder', datatype: '<class 'int'>', default: '512', info: 'Decoder Complexity.', rounding: '4', min_max: (512, 544), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Added defaults: model.realface
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Adding defaults: (filename: unbalanced_defaults.py, module_path: plugins.train.model, plugin_type: model
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Importing defaults module: plugins.train.model.unbalanced_defaults
08/12/2021 20:02:03 MainProcess _training_0 config add_section DEBUG Add section: (title: 'model.unbalanced', info: 'An unbalanced model with adjustable input size options.\nThis is an unbalanced model so b>a swaps may not work well\n')
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'input_size', datatype: '<class 'int'>', default: '128', info: 'Resolution (in pixels) of the image to train on.\nBE AWARE Larger resolution will dramatically increaseVRAM requirements.\nMake sure your resolution is divisible by 64 (e.g. 64, 128, 256 etc.).\nNB: Your faceset must be at least 1.6x larger than your required input size.\n(e.g. 160 is the maximum input size for a 256x256 faceset).', rounding: '64', min_max: (64, 512), choices: [], gui_radio: False, fixed: True, group: size)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'lowmem', datatype: '<class 'bool'>', default: 'False', info: 'Lower memory mode. Set to 'True' if having issues with VRAM useage.\nNB: Models with a changed lowmem mode are not compatible with each other.\nNB: lowmem will override cutom nodes and complexity settings.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'clipnorm', datatype: '<class 'bool'>', default: 'True', info: 'Controls gradient clipping of the optimizer. Can prevent model corruption at the expense of VRAM.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'nodes', datatype: '<class 'int'>', default: '1024', info: 'Number of nodes for decoder. Don't change this unless you know what you are doing!', rounding: '64', min_max: (512, 4096), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'complexity_encoder', datatype: '<class 'int'>', default: '128', info: 'Encoder Convolution Layer Complexity. sensible ranges: 128 to 160.', rounding: '16', min_max: (64, 1024), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'complexity_decoder_a', datatype: '<class 'int'>', default: '384', info: 'Decoder A Complexity.', rounding: '16', min_max: (64, 1024), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.unbalanced', title: 'complexity_decoder_b', datatype: '<class 'int'>', default: '512', info: 'Decoder B Complexity.', rounding: '16', min_max: (64, 1024), choices: [], gui_radio: False, fixed: True, group: network)
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Added defaults: model.unbalanced
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Adding defaults: (filename: villain_defaults.py, module_path: plugins.train.model, plugin_type: model
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Importing defaults module: plugins.train.model.villain_defaults
08/12/2021 20:02:03 MainProcess _training_0 config add_section DEBUG Add section: (title: 'model.villain', info: 'A Higher resolution version of the Original Model by VillainGuy.\nExtremely VRAM heavy. Don't try to run this if you have a small GPU.\n')
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'model.villain', title: 'lowmem', datatype: '<class 'bool'>', default: 'False', info: 'Lower memory mode. Set to 'True' if having issues with VRAM useage.\nNB: Models with a changed lowmem mode are not compatible with each other.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Added defaults: model.villain
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Adding defaults: (filename: original_defaults.py, module_path: plugins.train.trainer, plugin_type: trainer
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Importing defaults module: plugins.train.trainer.original_defaults
08/12/2021 20:02:03 MainProcess _training_0 config add_section DEBUG Add section: (title: 'trainer.original', info: 'Original Trainer Options.\nWARNING: The defaults for augmentation will be fine for 99.9% of use cases. Only change them if you absolutely know what you are doing!')
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'preview_images', datatype: '<class 'int'>', default: '14', info: 'Number of sample faces to display for each side in the preview when training.', rounding: '2', min_max: (2, 16), choices: None, gui_radio: False, fixed: True, group: evaluation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'zoom_amount', datatype: '<class 'int'>', default: '5', info: 'Percentage amount to randomly zoom each training image in and out.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'rotation_range', datatype: '<class 'int'>', default: '10', info: 'Percentage amount to randomly rotate each training image.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'shift_range', datatype: '<class 'int'>', default: '5', info: 'Percentage amount to randomly shift each training image horizontally and vertically.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'flip_chance', datatype: '<class 'int'>', default: '50', info: 'Percentage chance to randomly flip each training image horizontally.\nNB: This is ignored if the 'no-flip' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: image augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_lightness', datatype: '<class 'int'>', default: '30', info: 'Percentage amount to randomly alter the lightness of each training image.\nNB: This is ignored if the 'no-flip' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: color augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_ab', datatype: '<class 'int'>', default: '8', info: 'Percentage amount to randomly alter the 'a' and 'b' colors of the L*a*b* color space of each training image.\nNB: This is ignored if the 'no-flip' option is enabled', rounding: '1', min_max: (0, 50), choices: None, gui_radio: False, fixed: True, group: color augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_clahe_chance', datatype: '<class 'int'>', default: '50', info: 'Percentage chance to perform Contrast Limited Adaptive Histogram Equalization on each training image.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: False, group: color augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config add_item DEBUG Add item: (section: 'trainer.original', title: 'color_clahe_max_size', datatype: '<class 'int'>', default: '4', info: 'The grid size dictates how much Contrast Limited Adaptive Histogram Equalization is performed on any training image selected for clahe. Contrast will be applied randomly with a gridsize of 0 up to the maximum. This value is a multiplier calculated from the training image size.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (1, 8), choices: None, gui_radio: False, fixed: True, group: color augmentation)
08/12/2021 20:02:03 MainProcess _training_0 config _load_defaults_from_module DEBUG Added defaults: trainer.original
08/12/2021 20:02:03 MainProcess _training_0 config handle_config DEBUG Handling config: (section: model.dfl_sae, configfile: '[hidden]\faceswap\config\train.ini')
08/12/2021 20:02:03 MainProcess _training_0 config check_exists DEBUG Config file exists: '[hidden]\faceswap\config\train.ini'
08/12/2021 20:02:03 MainProcess _training_0 config load_config VERBOSE Loading config: '[hidden]\faceswap\config\train.ini'
08/12/2021 20:02:03 MainProcess _training_0 config validate_config DEBUG Validating config
08/12/2021 20:02:03 MainProcess _training_0 config check_config_change DEBUG Default config has not changed
08/12/2021 20:02:03 MainProcess _training_0 config check_config_choices DEBUG Checking config choices
08/12/2021 20:02:03 MainProcess _training_0 config _parse_list DEBUG Processed raw option 'keras_encoder' to list ['keras_encoder'] for section 'model.phaze_a', option 'freeze_layers'
08/12/2021 20:02:03 MainProcess _training_0 config _parse_list DEBUG Processed raw option 'encoder' to list ['encoder'] for section 'model.phaze_a', option 'load_layers'
08/12/2021 20:02:03 MainProcess _training_0 config check_config_choices DEBUG Checked config choices
08/12/2021 20:02:03 MainProcess _training_0 config validate_config DEBUG Validated config
08/12/2021 20:02:03 MainProcess _training_0 config handle_config DEBUG Handled config
08/12/2021 20:02:03 MainProcess _training_0 config __init__ DEBUG Initialized: Config
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global', option: 'learning_rate')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'float'>, value: 5e-05)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global', option: 'epsilon_exponent')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'int'>, value: -7)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global', option: 'allow_growth')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'bool'>, value: False)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global', option: 'nan_protection')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'bool'>, value: True)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global', option: 'convert_batchsize')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'int'>, value: 16)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global.loss', option: 'eye_multiplier')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'int'>, value: 3)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'global.loss', option: 'mouth_multiplier')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'int'>, value: 2)
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Getting config item: (section: 'model.dfl_sae', option: 'clipnorm')
08/12/2021 20:02:03 MainProcess _training_0 config get DEBUG Returning item: (type: <class 'bool'>, value: True)
08/12/2021 20:02:03 MainProcess _training_0 config changeable_items DEBUG Alterable for existing models: {'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initializing State: (model_dir: 'R:\Apps\nSwap 3\Models\SAE A1_snapshot_30000_iters - Copy', model_name: 'dfl_sae', config_changeable_items: '{'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}', no_logs: False
08/12/2021 20:02:03 MainProcess _training_0 serializer get_serializer DEBUG <lib.serializer._JSONSerializer object at 0x000001D57CFB2850>
08/12/2021 20:02:03 MainProcess _training_0 _base _load DEBUG Loading State
08/12/2021 20:02:03 MainProcess _training_0 serializer load DEBUG filename: R:\Apps\nSwap 3\Models\SAE A1_snapshot_30000_iters - Copy\dfl_sae_state.json
08/12/2021 20:02:03 MainProcess _training_0 serializer load DEBUG stored data type: <class 'bytes'>
08/12/2021 20:02:03 MainProcess _training_0 serializer unmarshal DEBUG data type: <class 'bytes'>
08/12/2021 20:02:03 MainProcess _training_0 serializer unmarshal DEBUG returned data type: <class 'dict'>
08/12/2021 20:02:03 MainProcess _training_0 serializer load DEBUG data type: <class 'dict'>
08/12/2021 20:02:03 MainProcess _training_0 _base _load DEBUG Loaded state: {'name': 'dfl_sae', 'sessions': {'1': {'timestamp': 1628450756.6982133, 'no_logs': False, 'loss_names': ['total', 'face_a', 'face_b'], 'batchsize': 16, 'iterations': 297, 'config': {'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}}, '2': {'timestamp': 1628451474.4808395, 'no_logs': False, 'loss_names': ['total', 'face_a', 'face_b'], 'batchsize': 16, 'iterations': 1, 'config': {'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}}, '3': {'timestamp': 1628451547.4369736, 'no_logs': False, 'loss_names': ['total', 'face_a', 'face_b'], 'batchsize': 32, 'iterations': 1669, 'config': {'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}}, '4': {'timestamp': 1628480266.6708539, 'no_logs': False, 'loss_names': ['total', 'face_a', 'face_b'], 'batchsize': 32, 'iterations': 23106, 'config': {'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}}, '5': {'timestamp': 1628549852.7428732, 'no_logs': False, 'loss_names': ['total', 'face_a', 'face_b'], 'batchsize': 32, 'iterations': 4750, 'config': {'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'nan_protection': True, 'convert_batchsize': 16, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'clipnorm': True}}}, 'lowest_avg_loss': {'a': 0.039280573606491086, 'b': 0.025626418843865396}, 'iterations': 29823, 'config': {'centering': 'face', 'coverage': 68.75, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'mixed_precision': False, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ssim', 'mask_loss_function': 'mse', 'l2_reg_term': 100, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'input_size': 128, 'clipnorm': True, 'architecture': 'df', 'autoencoder_dims': 0, 'encoder_dims': 42, 'decoder_dims': 21, 'multiscale_decoder': False}}
08/12/2021 20:02:03 MainProcess _training_0 _base _update_legacy_config DEBUG Checking for legacy state file update
08/12/2021 20:02:03 MainProcess _training_0 _base _update_legacy_config DEBUG Legacy item 'dssim_loss' not in config. Skipping update
08/12/2021 20:02:03 MainProcess _training_0 _base _update_legacy_config DEBUG State file updated for legacy config: False
08/12/2021 20:02:03 MainProcess _training_0 _base _replace_config DEBUG Replacing config. Old config: {'centering': 'face', 'coverage': 68.75, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'mixed_precision': False, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ssim', 'mask_loss_function': 'mse', 'l2_reg_term': 100, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'input_size': 128, 'clipnorm': True, 'architecture': 'df', 'autoencoder_dims': 0, 'encoder_dims': 42, 'decoder_dims': 21, 'multiscale_decoder': False}
08/12/2021 20:02:03 MainProcess _training_0 _base _replace_config DEBUG Replaced config. New config: {'centering': 'face', 'coverage': 68.75, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -7, 'allow_growth': False, 'mixed_precision': False, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ssim', 'mask_loss_function': 'mse', 'l2_reg_term': 100, 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'input_size': 128, 'clipnorm': True, 'architecture': 'df', 'autoencoder_dims': 0, 'encoder_dims': 42, 'decoder_dims': 21, 'multiscale_decoder': False}
08/12/2021 20:02:03 MainProcess _training_0 _base _replace_config INFO Using configuration saved in state file
08/12/2021 20:02:03 MainProcess _training_0 _base _new_session_id DEBUG 6
08/12/2021 20:02:03 MainProcess _training_0 _base _create_new_session DEBUG Creating new session. id: 6
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initialized State:
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initializing _Settings: (arguments: Namespace(batch_size=8, colab=False, configfile=None, distributed=False, exclude_gpus=None, freeze_weights=False, func=<bound method ScriptExecutor.execute_script of <lib.cli.launcher.ScriptExecutor object at 0x000001D565AF5EB0>>, input_a='R:\\Apps\\nSwap 3\\FaceA Training Set\\AC All Faces', input_b='R:\\Apps\\nSwap2\\FaceB Training Set\\All FaceB Combined Training Set', iterations=1000000, load_weights=None, logfile=None, loglevel='INFO', model_dir='R:\\Apps\\nSwap 3\\Models\\SAE A1_snapshot_30000_iters - Copy', no_augment_color=False, no_flip=False, no_logs=False, no_warp=False, preview=False, preview_scale=100, redirect_gui=True, save_interval=250, snapshot_interval=15000, summary=False, timelapse_input_a=None, timelapse_input_b=None, timelapse_output=None, trainer='dfl-sae', warp_to_landmarks=False, write_image=False), mixed_precision: False, allow_growth: False, is_predict: False)
08/12/2021 20:02:03 MainProcess _training_0 _base _set_keras_mixed_precision DEBUG use_mixed_precision: False, exclude_gpus: False
08/12/2021 20:02:03 MainProcess _training_0 _base _set_keras_mixed_precision DEBUG Not enabling 'mixed_precision' (backend: amd, use_mixed_precision: False)
08/12/2021 20:02:03 MainProcess _training_0 _base _get_strategy DEBUG Using strategy: None
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initialized _Settings
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initializing _Loss
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initialized: _Loss
08/12/2021 20:02:03 MainProcess _training_0 _base __init__ DEBUG Initialized ModelBase (Model)
08/12/2021 20:02:03 MainProcess _training_0 _base strategy_scope DEBUG Using strategy scope: <contextlib.nullcontext object at 0x000001D57CFEB1C0>
08/12/2021 20:02:03 MainProcess _training_0 _base _load DEBUG Loading model: R:\Apps\nSwap 3\Models\SAE A1_snapshot_30000_iters - Copy\dfl_sae.h5
08/12/2021 20:02:03 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): Unknown layer: Functional
08/12/2021 20:02:04 MainProcess MainThread train _monitor DEBUG Thread error detected
08/12/2021 20:02:04 MainProcess MainThread train _monitor DEBUG Closed Monitor
08/12/2021 20:02:04 MainProcess MainThread train _end_thread DEBUG Ending Training thread
08/12/2021 20:02:04 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
08/12/2021 20:02:04 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
08/12/2021 20:02:04 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
08/12/2021 20:02:04 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "[hidden]\faceswap\lib\cli\launcher.py", line 182, in execute_script
process.process()
File "[hidden]\faceswap\scripts\train.py", line 190, in process
self._end_thread(thread, err)
File "[hidden]\faceswap\scripts\train.py", line 230, in _end_thread
thread.join()
File "[hidden]\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "[hidden]\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "[hidden]\faceswap\scripts\train.py", line 252, in _training
raise err
File "[hidden]\faceswap\scripts\train.py", line 240, in _training
model = self._load_model()
File "[hidden]\faceswap\scripts\train.py", line 268, in _load_model
model.build()
File "[hidden]\faceswap\plugins\train\model\_base.py", line 286, in build
model = self._io._load() # pylint:disable=protected-access
File "[hidden]\faceswap\plugins\train\model\_base.py", line 556, in _load
model = load_model(self._filename, compile=False)
File "[hidden]\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\saving.py", line 419, in load_model
model = _deserialize_model(f, custom_objects, compile)
File "[hidden]\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\saving.py", line 225, in _deserialize_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "[hidden]\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\saving.py", line 458, in model_from_config
return deserialize(config, custom_objects=custom_objects)
File "[hidden]\MiniConda3\envs\faceswap\lib\site-packages\keras\layers\__init__.py", line 52, in deserialize
return deserialize_keras_object(config,
File "[hidden]\MiniConda3\envs\faceswap\lib\site-packages\keras\utils\generic_utils.py", line 137, in deserialize_keras_object
raise ValueError('Unknown ' + printable_module_name +
ValueError: Unknown layer: Functional
============ System Information ============
encoding: cp1252
git_branch: Not Found
git_commits: Not Found
gpu_cuda: No global version found. Check Conda packages for Conda Cuda
gpu_cudnn: No global version found. Check Conda packages for Conda cuDNN
gpu_devices: GPU_0: Advanced Micro Devices, Inc. - Hawaii (experimental)
gpu_devices_active: GPU_0
gpu_driver: ['3240.6']
gpu_vram: GPU_0: 8192MB
os_machine: AMD64
os_platform: Windows-10-10.0.19042-SP0
os_release: 10
py_command: [hidden]\faceswap.py train -A R:/Apps/nSwap 3/FaceA Training Set/AC All Faces -B R:/Apps/nSwap2/FaceB Training Set/All FaceB Combined Training Set -m R:/Apps/nSwap 3/Models/SAE A1_snapshot_30000_iters - Copy -t dfl-sae -bs 8 -it 1000000 -s 250 -ss 15000 -ps 100 -L INFO -gui
py_conda_version: conda 4.10.3
py_implementation: CPython
py_version: 3.8.10
py_virtual_env: True
sys_cores: 8
sys_processor: Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
sys_ram: Total: 16311MB, Available: 9451MB, Used: 6859MB, Free: 9451MB
=============== Pip Packages ===============
absl-py==0.13.0
astunparse==1.6.3
cachetools==4.2.2
certifi==2021.5.30
cffi==1.14.6
charset-normalizer==2.0.3
cycler==0.10.0
enum34==1.1.10
fastcluster==1.1.26
ffmpy==0.2.3
gast==0.3.3
google-auth==1.33.1
google-auth-oauthlib==0.4.4
google-pasta==0.2.0
grpcio==1.39.0
h5py==2.10.0
idna==3.2
imageio @ file:///tmp/build/80754af9/imageio_1617700267927/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1621542018480/work
joblib @ file:///tmp/build/80754af9/joblib_1613502643832/work
Keras==2.2.4
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/ci/kiwisolver_1612282606037/work
Markdown==3.3.4
matplotlib @ file:///C:/ci/matplotlib-base_1592837548929/work
mkl-fft==1.3.0
mkl-random==1.1.1
mkl-service==2.3.0
numpy==1.18.5
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.1
olefile==0.46
opencv-python==4.5.3.56
opt-einsum==3.3.0
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1625663293593/work
plaidml==0.7.0
plaidml-keras==0.7.0
protobuf==3.17.3
psutil @ file:///C:/ci/psutil_1612298324802/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser==2.20
pyparsing @ file:///home/linux1/recipes/ci/pyparsing_1610983426697/work
python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
pywin32==227
PyYAML==5.4.1
requests==2.26.0
requests-oauthlib==1.3.0
rsa==4.7.2
scikit-learn @ file:///C:/ci/scikit-learn_1622739500535/work
scipy @ file:///C:/ci/scipy_1616703433439/work
sip==4.19.13
six @ file:///tmp/build/80754af9/six_1623709665295/work
tensorboard==2.2.2
tensorboard-plugin-wit==1.8.0
tensorflow==2.2.3
tensorflow-estimator==2.2.0
termcolor==1.1.0
threadpoolctl @ file:///tmp/build/80754af9/threadpoolctl_1626115094421/work
tornado @ file:///C:/ci/tornado_1606942392901/work
tqdm @ file:///tmp/build/80754af9/tqdm_1625563689033/work
urllib3==1.26.6
Werkzeug==2.0.1
wincertstore==0.2
wrapt==1.12.1
============== Conda Packages ==============
# packages in environment at [hidden]\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
absl-py 0.13.0 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
blas 1.0 mkl
ca-certificates 2021.7.5 haa95532_1
cachetools 4.2.2 pypi_0 pypi
certifi 2021.5.30 py38haa95532_0
cffi 1.14.6 pypi_0 pypi
charset-normalizer 2.0.3 pypi_0 pypi
cycler 0.10.0 py38_0
enum34 1.1.10 pypi_0 pypi
fastcluster 1.1.26 py38h251f6bf_2 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.2.3 pypi_0 pypi
freetype 2.10.4 hd328e21_0
gast 0.3.3 pypi_0 pypi
git 2.23.0 h6bb4b03_0
google-auth 1.33.1 pypi_0 pypi
google-auth-oauthlib 0.4.4 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.39.0 pypi_0 pypi
h5py 2.10.0 pypi_0 pypi
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 3.2 pypi_0 pypi
imageio 2.9.0 pyhd3eb1b0_0
imageio-ffmpeg 0.4.4 pyhd8ed1ab_0 conda-forge
intel-openmp 2021.3.0 haa95532_3372
joblib 1.0.1 pyhd3eb1b0_0
jpeg 9b hb83a4c4_2
keras 2.2.4 pypi_0 pypi
keras-applications 1.0.8 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.3.1 py38hd77b12b_0
libpng 1.6.37 h2a8f88b_0
libtiff 4.2.0 hd0e1b90_0
lz4-c 1.9.3 h2bbff1b_0
markdown 3.3.4 pypi_0 pypi
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py38h64f37c6_0
mkl 2020.2 256
mkl-service 2.3.0 py38h196d8e1_0
mkl_fft 1.3.0 py38h46781fe_0
mkl_random 1.1.1 py38h47e9c7a_0
numpy 1.18.5 pypi_0 pypi
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.1 pypi_0 pypi
olefile 0.46 py_0
opencv-python 4.5.3.56 pypi_0 pypi
openssl 1.1.1k h2bbff1b_0
opt-einsum 3.3.0 pypi_0 pypi
pathlib 1.0.1 py_1
pillow 8.3.1 py38h4fa10fc_0
pip 21.1.3 py38haa95532_0
plaidml 0.7.0 pypi_0 pypi
plaidml-keras 0.7.0 pypi_0 pypi
protobuf 3.17.3 pypi_0 pypi
psutil 5.8.0 py38h2bbff1b_1
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycparser 2.20 pypi_0 pypi
pyparsing 2.4.7 pyhd3eb1b0_0
pyqt 5.9.2 py38ha925a31_4
python 3.8.10 hdbf39b2_7
python-dateutil 2.8.2 pyhd3eb1b0_0
python_abi 3.8 2_cp38 conda-forge
pywin32 227 py38he774522_1
pyyaml 5.4.1 pypi_0 pypi
qt 5.9.7 vc14h73c81de_0
requests 2.26.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
rsa 4.7.2 pypi_0 pypi
scikit-learn 0.24.2 py38hf11a4ad_1
scipy 1.6.2 py38h14eb087_0
setuptools 52.0.0 py38haa95532_0
sip 4.19.13 py38ha925a31_0
six 1.16.0 pyhd3eb1b0_0
sqlite 3.36.0 h2bbff1b_0
tensorboard 2.2.2 pypi_0 pypi
tensorboard-plugin-wit 1.8.0 pypi_0 pypi
tensorflow 2.2.3 pypi_0 pypi
tensorflow-estimator 2.2.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
threadpoolctl 2.2.0 pyhb85f177_0
tk 8.6.10 he774522_0
tornado 6.1 py38h2bbff1b_0
tqdm 4.61.2 pyhd3eb1b0_1
urllib3 1.26.6 pypi_0 pypi
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 2.0.1 pypi_0 pypi
wheel 0.36.2 pyhd3eb1b0_0
wincertstore 0.2 py38_0
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h62dcd97_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.9 h19a0ad4_0
================= Configs ==================
--------- .faceswap ---------
backend: amd
--------- convert.ini ---------
[color.color_transfer]
clip: True
preserve_paper: True
[color.manual_balance]
colorspace: HSV
balance_1: 0.0
balance_2: 0.0
balance_3: 0.0
contrast: 0.0
brightness: 0.0
[color.match_hist]
threshold: 99.0
[mask.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[mask.mask_blend]
type: gaussian
kernel_size: 3
passes: 4
threshold: 4
erosion: 0.0
[scaling.sharpen]
method: gaussian
amount: 150
radius: 0.3
threshold: 5.0
[writer.ffmpeg]
container: mp4
codec: libx264
crf: 23
preset: medium
tune: none
profile: auto
level: auto
skip_mux: False
[writer.gif]
fps: 25
loop: 0
palettesize: 256
subrectangles: False
[writer.opencv]
format: png
draw_transparent: False
jpg_quality: 75
png_compress_level: 3
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: False
[align.fan]
batch-size: 12
[detect.cv2_dnn]
confidence: 50
[detect.mtcnn]
minsize: 20
scalefactor: 0.709
batch-size: 8
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
[detect.s3fd]
confidence: 70
batch-size: 4
[mask.bisenet_fp]
batch-size: 8
include_ears: False
include_hair: False
include_glasses: True
[mask.unet_dfl]
batch-size: 8
[mask.vgg_clear]
batch-size: 6
[mask.vgg_obstructed]
batch-size: 2
--------- gui.ini ---------
[global]
fullscreen: False
tab: extract
options_panel_width: 30
console_panel_height: 20
icon_size: 14
font: default
font_size: 12
autosave_last_session: prompt
timeout: 120
auto_load_model_stats: True
--------- train.ini ---------
[global]
centering: face
coverage: 68.75
icnr_init: False
conv_aware_init: False
optimizer: adam
learning_rate: 5e-05
epsilon_exponent: -7
reflect_padding: False
allow_growth: False
mixed_precision: False
nan_protection: True
convert_batchsize: 16
[global.loss]
loss_function: ssim
mask_loss_function: mse
l2_reg_term: 100
eye_multiplier: 3
mouth_multiplier: 2
penalized_mask_loss: True
mask_type: extended
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: False
[model.dfaker]
output_size: 128
[model.dfl_h128]
lowmem: False
[model.dfl_sae]
input_size: 128
clipnorm: True
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.dlight]
features: best
details: good
output_size: 256
[model.original]
lowmem: False
[model.phaze_a]
output_size: 128
shared_fc: None
enable_gblock: True
split_fc: True
split_gblock: False
split_decoders: False
enc_architecture: fs_original
enc_scaling: 40
enc_load_weights: True
bottleneck_type: dense
bottleneck_norm: None
bottleneck_size: 1024
bottleneck_in_encoder: True
fc_depth: 1
fc_min_filters: 1024
fc_max_filters: 1024
fc_dimensions: 4
fc_filter_slope: -0.5
fc_dropout: 0.0
fc_upsampler: upsample2d
fc_upsamples: 1
fc_upsample_filters: 512
fc_gblock_depth: 3
fc_gblock_min_nodes: 512
fc_gblock_max_nodes: 512
fc_gblock_filter_slope: -0.5
fc_gblock_dropout: 0.0
dec_upscale_method: subpixel
dec_norm: None
dec_min_filters: 64
dec_max_filters: 512
dec_filter_slope: -0.45
dec_res_blocks: 1
dec_output_kernel: 5
dec_gaussian: True
dec_skip_last_residual: True
freeze_layers: keras_encoder
load_layers: encoder
fs_original_depth: 4
fs_original_min_filters: 128
fs_original_max_filters: 1024
mobilenet_width: 1.0
mobilenet_depth: 1
mobilenet_dropout: 0.001
[model.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.unbalanced]
input_size: 128
lowmem: False
clipnorm: True
nodes: 1024
complexity_encoder: 128
complexity_decoder_a: 384
complexity_decoder_b: 512
[model.villain]
lowmem: False
[trainer.original]
preview_images: 14
zoom_amount: 5
rotation_range: 10
shift_range: 5
flip_chance: 50
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4