StoJo preset is crashing

If training is failing to start, and you are not receiving an error message telling you what to do, tell us about it here


Forum rules

Read the FAQs and search the forum before posting a new topic.

This forum is for reporting errors with the Training process. If you want to get tips, or better understand the Training process, then you should look in the Training Discussion forum.

Please mark any answers that fixed your problems so others can find the solutions.

Post Reply
User avatar
shini719
Posts: 2
Joined: Tue Nov 01, 2022 9:40 pm

StoJo preset is crashing

Post by shini719 »

For some reason i cant even start the training with the StoJo preset. It simply crashes.

Code: Select all

11/02/2022 03:03:33 MainProcess     _training                      config          _load_defaults_from_module     DEBUG    Importing defaults module: plugins.train.trainer.original_defaults
11/02/2022 03:03:33 MainProcess     _training                      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!')
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      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-augment-color' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: color augmentation)
11/02/2022 03:03:33 MainProcess     _training                      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-augment-color' optionis enabled', rounding: '1', min_max: (0, 50), choices: None, gui_radio: False, fixed: True, group: color augmentation)
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      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)
11/02/2022 03:03:33 MainProcess     _training                      config          _load_defaults_from_module     DEBUG    Added defaults: trainer.original
11/02/2022 03:03:33 MainProcess     _training                      config          handle_config                  DEBUG    Handling config: (section: model.phaze_a, configfile: 'G:\faceswap\config\train.ini')
11/02/2022 03:03:33 MainProcess     _training                      config          check_exists                   DEBUG    Config file exists: 'G:\faceswap\config\train.ini'
11/02/2022 03:03:33 MainProcess     _training                      config          load_config                    VERBOSE  Loading config: 'G:\faceswap\config\train.ini'
11/02/2022 03:03:33 MainProcess     _training                      config          validate_config                DEBUG    Validating config
11/02/2022 03:03:33 MainProcess     _training                      config          check_config_change            DEBUG    Default config has not changed
11/02/2022 03:03:33 MainProcess     _training                      config          check_config_choices           DEBUG    Checking config choices
11/02/2022 03:03:33 MainProcess     _training                      config          _parse_list                    DEBUG    Processed raw option 'keras_encoder' to list ['keras_encoder'] for section 'model.phaze_a', option 'freeze_layers'
11/02/2022 03:03:33 MainProcess     _training                      config          _parse_list                    DEBUG    Processed raw option 'encoder' to list ['encoder'] for section 'model.phaze_a', option 'load_layers'
11/02/2022 03:03:33 MainProcess     _training                      config          check_config_choices           DEBUG    Checked config choices
11/02/2022 03:03:33 MainProcess     _training                      config          validate_config                DEBUG    Validated config
11/02/2022 03:03:33 MainProcess     _training                      config          handle_config                  DEBUG    Handled config
11/02/2022 03:03:33 MainProcess     _training                      config          __init__                       DEBUG    Initialized: Config
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'learning_rate')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'float'>, value: 5e-05)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'epsilon_exponent')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: -16)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'autoclip')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'bool'>, value: False)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'allow_growth')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'bool'>, value: False)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'mixed_precision')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'bool'>, value: True)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'nan_protection')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'bool'>, value: True)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global', option: 'convert_batchsize')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: 16)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_function')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'str'>, value: ms_ssim)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_function_2')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'str'>, value: mae)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_weight_2')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: 25)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_function_3')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'str'>, value: ffl)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_weight_3')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: 100)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_function_4')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'str'>, value: None)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'loss_weight_4')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: 0)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'mask_loss_function')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'str'>, value: mae)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'eye_multiplier')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: 3)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'global.loss', option: 'mouth_multiplier')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'int'>, value: 2)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'model.phaze_a', option: 'fc_dropout')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'float'>, value: 0.0)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'model.phaze_a', option: 'fc_gblock_dropout')
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'float'>, value: 0.0)
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Getting config item: (section: 'model.phaze_a', option: 'freeze_layers')
11/02/2022 03:03:33 MainProcess     _training                      config          _parse_list                    DEBUG    Processed raw option 'keras_encoder' to list ['keras_encoder'] for section 'model.phaze_a', option 'freeze_layers'
11/02/2022 03:03:33 MainProcess     _training                      config          get                            DEBUG    Returning item: (type: <class 'list'>, value: ['keras_encoder'])
11/02/2022 03:03:33 MainProcess     _training                      config          changeable_items               DEBUG    Alterable for existing models: {'learning_rate': 5e-05, 'epsilon_exponent': -16, 'autoclip': False, 'allow_growth': False, 'mixed_precision': True, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ms_ssim', 'loss_function_2': 'mae', 'loss_weight_2': 25, 'loss_function_3': 'ffl', 'loss_weight_3': 100, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mae', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'fc_dropout': 0.0, 'fc_gblock_dropout': 0.0, 'freeze_layers': ['keras_encoder']}
11/02/2022 03:03:33 MainProcess     _training                      model           __init__                       DEBUG    Initializing State: (model_dir: 'F:\Pinscreen_Data\HERE_Training_Data\FaceSwap_Avi_stojo', model_name: 'phaze_a', config_changeable_items: '{'learning_rate': 5e-05, 'epsilon_exponent': -16, 'autoclip': False, 'allow_growth': False, 'mixed_precision': True, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ms_ssim', 'loss_function_2': 'mae', 'loss_weight_2': 25, 'loss_function_3': 'ffl', 'loss_weight_3': 100, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mae', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'fc_dropout': 0.0, 'fc_gblock_dropout': 0.0, 'freeze_layers': ['keras_encoder']}', no_logs: False
11/02/2022 03:03:33 MainProcess     _training                      serializer      get_serializer                 DEBUG    <lib.serializer._JSONSerializer object at 0x000001FF0CE13760>
11/02/2022 03:03:33 MainProcess     _training                      model           _load                          DEBUG    Loading State
11/02/2022 03:03:33 MainProcess     _training                      model           _load                          INFO     No existing state file found. Generating.
11/02/2022 03:03:33 MainProcess     _training                      model           _new_session_id                DEBUG    1
11/02/2022 03:03:33 MainProcess     _training                      model           _create_new_session            DEBUG    Creating new session. id: 1
11/02/2022 03:03:33 MainProcess     _training                      model           __init__                       DEBUG    Initialized State:
11/02/2022 03:03:33 MainProcess     _training                      settings        __init__                       DEBUG    Initializing Settings: (arguments: Namespace(func=<bound method ScriptExecutor.execute_script of <lib.cli.launcher.ScriptExecutor object at 0x000001FF7F8E8970>>, exclude_gpus=None, configfile=None, loglevel='INFO', logfile=None, redirect_gui=True, colab=False, input_a='F:\\Pinscreen_Data\\HERE_Training_Data\\A_256', input_b='F:\\Pinscreen_Data\\HERE_Training_Data\\B_256', model_dir='F:\\Pinscreen_Data\\HERE_Training_Data\\FaceSwap_Avi_stojo', load_weights=None, trainer='phaze-a', summary=False, freeze_weights=False, batch_size=8, iterations=1000000, distributed=False, distribution_strategy='default', save_interval=250, snapshot_interval=25000, timelapse_input_a=None, timelapse_input_b=None, timelapse_output=None, preview=False, write_image=False, no_logs=False, warp_to_landmarks=False, no_flip=False, no_augment_color=False, no_warp=False), mixed_precision: True, allow_growth: False, is_predict: False)
11/02/2022 03:03:33 MainProcess     _training                      settings        _set_tf_settings               DEBUG    Not setting any specific Tensorflow settings
11/02/2022 03:03:33 MainProcess     _training                      settings        _set_keras_mixed_precision     DEBUG    use_mixed_precision: True
11/02/2022 03:03:33 MainProcess     _training                      device_compatibility_check _log_device_compatibility_check INFO     Mixed precision compatibility check (mixed_float16): OK\nYour GPUs will likely run quickly with dtype policy mixed_float16 as they all have compute capability of at least 7.0
11/02/2022 03:03:33 MainProcess     _training                      settings        _set_keras_mixed_precision     DEBUG    Enabled mixed precision. (Compute dtype: float16, variable_dtype: float32)
11/02/2022 03:03:33 MainProcess     _training                      settings        __init__                       INFO     Enabling Mixed Precision Training.
11/02/2022 03:03:33 MainProcess     _training                      settings        _get_strategy                  DEBUG    Using strategy: <tensorflow.python.distribute.distribute_lib._DefaultDistributionStrategy object at 0x000001FF0DDB2520>
11/02/2022 03:03:33 MainProcess     _training                      settings        __init__                       DEBUG    Initialized Settings
11/02/2022 03:03:33 MainProcess     _training                      settings        __init__                       DEBUG    Initializing Loss: (color_order: bgr)
11/02/2022 03:03:33 MainProcess     _training                      settings        _get_mask_channels             DEBUG    uses_masks: (True, True, True), mask_channels: [3, 4, 5]
11/02/2022 03:03:33 MainProcess     _training                      settings        __init__                       DEBUG    Initialized: Loss
11/02/2022 03:03:33 MainProcess     _training                      model           __init__                       DEBUG    Initialized ModelBase (Model)
11/02/2022 03:03:33 MainProcess     _training                      phaze_a         _select_freeze_layers          DEBUG    Substituting 'keras_encoder' for 'efficientnet_b4'
11/02/2022 03:03:33 MainProcess     _training                      phaze_a         _get_input_shape               DEBUG    Encoder input set to: (224, 224, 3)
11/02/2022 03:03:33 MainProcess     _training                      phaze_a         build                          DEBUG    New model, inference or summary. Falling back to default build: (exists: False, inference: False, is_summary: False)
11/02/2022 03:03:33 MainProcess     _training                      settings        strategy_scope                 DEBUG    Using strategy scope: <tensorflow.python.distribute.distribute_lib._DefaultDistributionContext object at 0x000001FF0CC258C0>
11/02/2022 03:03:33 MainProcess     _training                      model           _get_inputs                    DEBUG    Getting inputs
11/02/2022 03:03:33 MainProcess     _training                      model           _get_inputs                    DEBUG    inputs: [<KerasTensor: shape=(None, 224, 224, 3) dtype=float32 (created by layer 'face_in_a')>, <KerasTensor: shape=(None, 224, 224, 3) dtype=float32 (created by layer 'face_in_b')>]
11/02/2022 03:03:33 MainProcess     _training                      phaze_a         __call__                       DEBUG    Scaling to (0, 255) for 'efficientnet_b4'
11/02/2022 03:03:34 MainProcess     _training                      multithreading  run                            DEBUG    Error in thread (_training): Exception encountered when calling layer "tf.math.truediv" (type TFOpLambda).\n\n`x` and `y` must have the same dtype, got tf.float16 != tf.float32.\n\nCall arguments received by layer "tf.math.truediv" (type TFOpLambda):\n  • x=tf.Tensor(shape=(None, 224, 224, 3), dtype=float16)\n  • y=tf.Tensor(shape=(3,), dtype=float32)\n  • name=None
11/02/2022 03:03:35 MainProcess     MainThread                     train           _monitor                       DEBUG    Thread error detected
11/02/2022 03:03:35 MainProcess     MainThread                     train           _monitor                       DEBUG    Closed Monitor
11/02/2022 03:03:35 MainProcess     MainThread                     train           _end_thread                    DEBUG    Ending Training thread
11/02/2022 03:03:35 MainProcess     MainThread                     train           _end_thread                    CRITICAL Error caught! Exiting...
11/02/2022 03:03:35 MainProcess     MainThread                     multithreading  join                           DEBUG    Joining Threads: '_training'
11/02/2022 03:03:35 MainProcess     MainThread                     multithreading  join                           DEBUG    Joining Thread: '_training'
11/02/2022 03:03:35 MainProcess     MainThread                     multithreading  join                           ERROR    Caught exception in thread: '_training'
Traceback (most recent call last):
  File "G:\faceswap\lib\cli\launcher.py", line 217, in execute_script
    process.process()
  File "G:\faceswap\scripts\train.py", line 218, in process
    self._end_thread(thread, err)
  File "G:\faceswap\scripts\train.py", line 258, in _end_thread
    thread.join()
  File "G:\faceswap\lib\multithreading.py", line 217, in join
    raise thread.err[1].with_traceback(thread.err[2])
  File "G:\faceswap\lib\multithreading.py", line 96, in run
    self._target(*self._args, **self._kwargs)
  File "G:\faceswap\scripts\train.py", line 280, in _training
    raise err
  File "G:\faceswap\scripts\train.py", line 268, in _training
    model = self._load_model()
  File "G:\faceswap\scripts\train.py", line 296, in _load_model
    model.build()
  File "G:\faceswap\plugins\train\model\phaze_a.py", line 201, in build
    super().build()
  File "G:\faceswap\plugins\train\model\_base\model.py", line 315, in build
    self._model = self.build_model(inputs)
  File "G:\faceswap\plugins\train\model\phaze_a.py", line 358, in build_model
    encoders = self._build_encoders(inputs)
  File "G:\faceswap\plugins\train\model\phaze_a.py", line 382, in _build_encoders
    encoder = Encoder(self.input_shape, self.config)()
  File "G:\faceswap\plugins\train\model\phaze_a.py", line 737, in __call__
    var_x = self._get_encoder_model()(var_x)
  File "G:\faceswap\plugins\train\model\phaze_a.py", line 760, in _get_encoder_model
    retval = getattr(kapp, model.keras_name)(**kwargs)
  File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\applications\efficientnet.py", line 652, in EfficientNetB4
    return EfficientNet(
  File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\applications\efficientnet.py", line 334, in EfficientNet
    x = x / tf.math.sqrt(IMAGENET_STDDEV_RGB)
  File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\util\traceback_utils.py", line 153, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\layers\core\tf_op_layer.py", line 107, in handle
    return TFOpLambda(op)(*args, **kwargs)
  File "C:\Users\avira\MiniConda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 67, in error_handler
    raise e.with_traceback(filtered_tb) from None
TypeError: Exception encountered when calling layer "tf.math.truediv" (type TFOpLambda).

`x` and `y` must have the same dtype, got tf.float16 != tf.float32.

Call arguments received by layer "tf.math.truediv" (type TFOpLambda):
  • x=tf.Tensor(shape=(None, 224, 224, 3), dtype=float16)
  • y=tf.Tensor(shape=(3,), dtype=float32)
  • name=None

============ System Information ============
encoding:            cp1252
git_branch:          master
git_commits:         d1a7f7a bugfix: Don't error if preview unsuccessfully read
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: NVIDIA GeForce RTX 3090, GPU_1: NVIDIA GeForce RTX 3090
gpu_devices_active:  GPU_0, GPU_1
gpu_driver:          522.30
gpu_vram:            GPU_0: 24576MB, GPU_1: 24576MB
os_machine:          AMD64
os_platform:         Windows-10-10.0.22621-SP0
os_release:          10
py_command:          G:\faceswap\faceswap.py train -A F:/Pinscreen_Data/HERE_Training_Data/A_256 -B F:/Pinscreen_Data/HERE_Training_Data/B_256 -m F:/Pinscreen_Data/HERE_Training_Data/FaceSwap_Avi_stojo -t phaze-a -bs 8 -it 1000000 -D default -s 250 -ss 25000 -L INFO -gui
py_conda_version:    conda 22.9.0
py_implementation:   CPython
py_version:          3.9.13
py_virtual_env:      True
sys_cores:           32
sys_processor:       AMD64 Family 25 Model 33 Stepping 0, AuthenticAMD
sys_ram:             Total: 130993MB, Available: 107001MB, Used: 23992MB, Free: 107001MB

=============== Pip Packages ===============
absl-py @ file:///C:/b/abs_5babsu7y5x/croot/absl-py_1666362945682/work
astunparse==1.6.3
cachetools==5.2.0
certifi==2022.9.24
charset-normalizer==2.1.1
cloudpickle @ file:///tmp/build/80754af9/cloudpickle_1632508026186/work
colorama @ file:///C:/Windows/TEMP/abs_9439aeb1-0254-449a-96f7-33ab5eb17fc8apleb4yn/croots/recipe/colorama_1657009099097/work
cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work
decorator @ file:///opt/conda/conda-bld/decorator_1643638310831/work
dm-tree==0.1.5
fastcluster @ file:///D:/bld/fastcluster_1649783471014/work
ffmpy==0.3.0
flatbuffers==1.12
fonttools==4.25.0
gast==0.4.0
google-auth==2.13.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.50.0
h5py==3.7.0
idna==3.4
imageio @ file:///C:/Windows/TEMP/abs_24c1b783-7540-4ca9-a1b1-0e8aa8e6ae64hb79ssux/croots/recipe/imageio_1658785038775/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1649960641006/work
importlib-metadata==5.0.0
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1663332044897/work
keras==2.9.0
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/ci/kiwisolver_1653292407425/work
libclang==14.0.6
Markdown==3.4.1
MarkupSafe==2.1.1
matplotlib @ file:///C:/ci/matplotlib-suite_1660169687702/work
mkl-fft==1.3.1
mkl-random @ file:///C:/ci/mkl_random_1626186184308/work
mkl-service==2.4.0
munkres==1.1.4
numexpr @ file:///C:/Windows/Temp/abs_e2036a32-9fe9-47f3-a04c-dbb1c232ba4b334exiur/croots/recipe/numexpr_1656940304835/work
numpy @ file:///C:/b/abs_53f_dbvhzc/croot/numpy_and_numpy_base_1665773185489/work
nvidia-ml-py==11.515.75
oauthlib==3.2.2
opencv-python==4.6.0.66
opt-einsum==3.3.0
packaging @ file:///tmp/build/80754af9/packaging_1637314298585/work
Pillow==9.2.0
ply==3.11
protobuf==3.19.6
psutil @ file:///C:/Windows/Temp/abs_b2c2fd7f-9fd5-4756-95ea-8aed74d0039flsd9qufz/croots/recipe/psutil_1656431277748/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pyparsing @ file:///C:/Users/BUILDE~1/AppData/Local/Temp/abs_7f_7lba6rl/croots/recipe/pyparsing_1661452540662/work
PyQt5==5.15.7
PyQt5-sip @ file:///C:/Windows/Temp/abs_d7gmd2jg8i/croots/recipe/pyqt-split_1659273064801/work/pyqt_sip
python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
pywin32==302
pywinpty @ file:///C:/ci_310/pywinpty_1644230983541/work/target/wheels/pywinpty-2.0.2-cp39-none-win_amd64.whl
requests==2.28.1
requests-oauthlib==1.3.1
rsa==4.9
scikit-learn @ file:///D:/bld/scikit-learn_1652976858669/work
scipy @ file:///C:/bld/scipy_1658811088396/work
sip @ file:///C:/Windows/Temp/abs_b8fxd17m2u/croots/recipe/sip_1659012372737/work
six @ file:///tmp/build/80754af9/six_1644875935023/work
tensorboard==2.9.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow-estimator==2.9.0
tensorflow-gpu==2.9.2
tensorflow-io-gcs-filesystem==0.27.0
tensorflow-probability @ file:///tmp/build/80754af9/tensorflow-probability_1633017132682/work
termcolor==2.0.1
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1643647933166/work
toml @ file:///tmp/build/80754af9/toml_1616166611790/work
tornado @ file:///C:/ci/tornado_1662458743919/work
tqdm @ file:///C:/b/abs_0axbz66qik/croots/recipe/tqdm_1664392691071/work
typing_extensions @ file:///C:/Windows/TEMP/abs_dd2d0moa85/croots/recipe/typing_extensions_1659638831135/work
urllib3==1.26.12
Werkzeug==2.2.2
wincertstore==0.2
wrapt==1.14.1
zipp==3.10.0

============== Conda Packages ==============
# packages in environment at C:\Users\avira\MiniConda3\envs\faceswap:
#
# Name                    Version                   Build  Channel
absl-py                   1.3.0            py39haa95532_0  
astunparse 1.6.3 pypi_0 pypi blas 1.0 mkl
brotli 1.0.9 h2bbff1b_7
brotli-bin 1.0.9 h2bbff1b_7
ca-certificates 2022.9.24 h5b45459_0 conda-forge cachetools 5.2.0 pypi_0 pypi certifi 2022.9.24 pyhd8ed1ab_0 conda-forge charset-normalizer 2.1.1 pypi_0 pypi cloudpickle 2.0.0 pyhd3eb1b0_0
colorama 0.4.5 py39haa95532_0
cudatoolkit 11.2.2 h933977f_10 conda-forge cudnn 8.1.0.77 h3e0f4f4_0 conda-forge cycler 0.11.0 pyhd3eb1b0_0
decorator 5.1.1 pyhd3eb1b0_0
dm-tree 0.1.5 py39hf11a4ad_0
fastcluster 1.2.6 py39h2e25243_1 conda-forge ffmpeg 4.3.1 ha925a31_0 conda-forge ffmpy 0.3.0 pypi_0 pypi flatbuffers 1.12 pypi_0 pypi fonttools 4.25.0 pyhd3eb1b0_0
freetype 2.12.1 ha860e81_0
gast 0.4.0 pypi_0 pypi git 2.34.1 haa95532_0
glib 2.69.1 h5dc1a3c_1
google-auth 2.13.0 pypi_0 pypi google-auth-oauthlib 0.4.6 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.50.0 pypi_0 pypi gst-plugins-base 1.18.5 h9e645db_0
gstreamer 1.18.5 hd78058f_0
h5py 3.7.0 pypi_0 pypi icu 58.2 ha925a31_3
idna 3.4 pypi_0 pypi imageio 2.19.3 py39haa95532_0
imageio-ffmpeg 0.4.7 pyhd8ed1ab_0 conda-forge importlib-metadata 5.0.0 pypi_0 pypi intel-openmp 2021.4.0 haa95532_3556
joblib 1.2.0 pyhd8ed1ab_0 conda-forge jpeg 9e h2bbff1b_0
keras 2.9.0 pypi_0 pypi keras-preprocessing 1.1.2 pypi_0 pypi kiwisolver 1.4.2 py39hd77b12b_0
lerc 3.0 hd77b12b_0
libblas 3.9.0 1_h8933c1f_netlib conda-forge libbrotlicommon 1.0.9 h2bbff1b_7
libbrotlidec 1.0.9 h2bbff1b_7
libbrotlienc 1.0.9 h2bbff1b_7
libcblas 3.9.0 5_hd5c7e75_netlib conda-forge libclang 14.0.6 pypi_0 pypi libdeflate 1.8 h2bbff1b_5
libffi 3.4.2 hd77b12b_4
libiconv 1.16 h2bbff1b_2
liblapack 3.9.0 5_hd5c7e75_netlib conda-forge libogg 1.3.5 h2bbff1b_1
libpng 1.6.37 h2a8f88b_0
libtiff 4.4.0 h8a3f274_0
libvorbis 1.3.7 he774522_0
libwebp 1.2.4 h2bbff1b_0
libwebp-base 1.2.4 h2bbff1b_0
libxml2 2.9.14 h0ad7f3c_0
libxslt 1.1.35 h2bbff1b_0
lz4-c 1.9.3 h2bbff1b_1
m2w64-gcc-libgfortran 5.3.0 6 conda-forge m2w64-gcc-libs 5.3.0 7 conda-forge m2w64-gcc-libs-core 5.3.0 7 conda-forge m2w64-gmp 6.1.0 2 conda-forge m2w64-libwinpthread-git 5.0.0.4634.697f757 2 conda-forge markdown 3.4.1 pypi_0 pypi markupsafe 2.1.1 pypi_0 pypi matplotlib 3.5.2 py39haa95532_0
matplotlib-base 3.5.2 py39hd77b12b_0
mkl 2021.4.0 haa95532_640
mkl-service 2.4.0 py39h2bbff1b_0
mkl_fft 1.3.1 py39h277e83a_0
mkl_random 1.2.2 py39hf11a4ad_0
msys2-conda-epoch 20160418 1 conda-forge munkres 1.1.4 py_0
numexpr 2.8.3 py39hb80d3ca_0
numpy 1.23.3 py39h3b20f71_0
numpy-base 1.23.3 py39h4da318b_0
nvidia-ml-py 11.515.75 pypi_0 pypi oauthlib 3.2.2 pypi_0 pypi opencv-python 4.6.0.66 pypi_0 pypi openssl 1.1.1q h8ffe710_0 conda-forge opt-einsum 3.3.0 pypi_0 pypi packaging 21.3 pyhd3eb1b0_0
pcre 8.45 hd77b12b_0
pillow 9.2.0 py39hdc2b20a_1
pip 22.2.2 py39haa95532_0
ply 3.11 py39haa95532_0
protobuf 3.19.6 pypi_0 pypi psutil 5.9.0 py39h2bbff1b_0
pyasn1 0.4.8 pypi_0 pypi pyasn1-modules 0.2.8 pypi_0 pypi pyparsing 3.0.9 py39haa95532_0
pyqt 5.15.7 py39hd77b12b_0
pyqt5-sip 12.11.0 py39hd77b12b_0
python 3.9.13 h6244533_2
python-dateutil 2.8.2 pyhd3eb1b0_0
python_abi 3.9 2_cp39 conda-forge pywin32 302 py39h2bbff1b_2
pywinpty 2.0.2 py39h5da7b33_0
qt-main 5.15.2 he8e5bd7_7
qt-webengine 5.15.9 hb9a9bb5_4
qtwebkit 5.212 h3ad3cdb_4
requests 2.28.1 pypi_0 pypi requests-oauthlib 1.3.1 pypi_0 pypi rsa 4.9 pypi_0 pypi scikit-learn 1.1.1 py39he931e04_0 conda-forge scipy 1.8.1 py39h5567194_2 conda-forge setuptools 63.4.1 py39haa95532_0
sip 6.6.2 py39hd77b12b_0
six 1.16.0 pyhd3eb1b0_1
sqlite 3.39.3 h2bbff1b_0
tensorboard 2.9.1 pypi_0 pypi tensorboard-data-server 0.6.1 pypi_0 pypi tensorboard-plugin-wit 1.8.1 pypi_0 pypi tensorflow-estimator 2.9.0 pypi_0 pypi tensorflow-gpu 2.9.2 pypi_0 pypi tensorflow-io-gcs-filesystem 0.27.0 pypi_0 pypi tensorflow-probability 0.14.0 pyhd3eb1b0_0
termcolor 2.0.1 pypi_0 pypi threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge tk 8.6.12 h2bbff1b_0
toml 0.10.2 pyhd3eb1b0_0
tornado 6.2 py39h2bbff1b_0
tqdm 4.64.1 py39haa95532_0
typing-extensions 4.3.0 py39haa95532_0
typing_extensions 4.3.0 py39haa95532_0
tzdata 2022e h04d1e81_0
urllib3 1.26.12 pypi_0 pypi vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 2.2.2 pypi_0 pypi wheel 0.37.1 pyhd3eb1b0_0
wincertstore 0.2 py39haa95532_2
winpty 0.4.3 4
wrapt 1.14.1 pypi_0 pypi xz 5.2.6 h8cc25b3_0
zipp 3.10.0 pypi_0 pypi zlib 1.2.13 h8cc25b3_0
zstd 1.5.2 h19a0ad4_0 ================= Configs ================== --------- .faceswap --------- backend: nvidia --------- 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.mask_blend] type: normalized kernel_size: 3 passes: 4 threshold: 4 erosion: 0.0 erosion_top: 0.0 erosion_bottom: 0.0 erosion_left: 0.0 erosion_right: 0.0 [scaling.sharpen] method: none 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 separate_mask: False jpg_quality: 75 png_compress_level: 3 [writer.pillow] format: png draw_transparent: False separate_mask: False optimize: False gif_interlace: True jpg_quality: 75 png_compress_level: 3 tif_compression: tiff_deflate --------- extract.ini --------- [global] allow_growth: False aligner_min_scale: 0.07 aligner_max_scale: 2.0 aligner_distance: 22.5 aligner_roll: 45.0 save_filtered: False [align.fan] batch-size: 12 [detect.cv2_dnn] confidence: 50 [detect.mtcnn] minsize: 20 scalefactor: 0.709 batch-size: 8 cpu: True 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 cpu: False weights: faceswap include_ears: True include_hair: False include_glasses: True [mask.custom] batch-size: 8 centering: face fill: False [mask.unet_dfl] batch-size: 8 [mask.vgg_clear] batch-size: 6 [mask.vgg_obstructed] batch-size: 2 [recognition.vgg_face2] batch-size: 16 cpu: False --------- train.ini --------- [global] centering: head coverage: 100.0 icnr_init: False conv_aware_init: False optimizer: adabelief learning_rate: 5e-05 epsilon_exponent: -16 autoclip: False reflect_padding: False allow_growth: False mixed_precision: True nan_protection: True convert_batchsize: 16 [global.loss] loss_function: ms_ssim loss_function_2: mae loss_weight_2: 25 loss_function_3: ffl loss_weight_3: 100 loss_function_4: None loss_weight_4: 0 mask_loss_function: mae eye_multiplier: 3 mouth_multiplier: 2 penalized_mask_loss: True mask_type: bisenet-fp_face 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 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: 256 shared_fc: none enable_gblock: True split_fc: True split_gblock: False split_decoders: False enc_architecture: efficientnet_b4 enc_scaling: 60 enc_load_weights: True bottleneck_type: dense bottleneck_norm: none bottleneck_size: 512 bottleneck_in_encoder: True fc_depth: 1 fc_min_filters: 1280 fc_max_filters: 1280 fc_dimensions: 8 fc_filter_slope: -0.5 fc_dropout: 0.0 fc_upsampler: upsample2d fc_upsamples: 1 fc_upsample_filters: 1280 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: resize_images dec_upscales_in_fc: 0 dec_norm: none dec_min_filters: 160 dec_max_filters: 640 dec_slope_mode: full dec_filter_slope: -0.33 dec_res_blocks: 1 dec_output_kernel: 3 dec_gaussian: True dec_skip_last_residual: False freeze_layers: keras_encoder load_layers: encoder fs_original_depth: 4 fs_original_min_filters: 128 fs_original_max_filters: 1024 fs_original_use_alt: False mobilenet_width: 1.0 mobilenet_depth: 1 mobilenet_dropout: 0.001 mobilenet_minimalistic: False [model.realface] input_size: 64 output_size: 128 dense_nodes: 1536 complexity_encoder: 128 complexity_decoder: 512 [model.unbalanced] input_size: 128 lowmem: False nodes: 1024 complexity_encoder: 128 complexity_decoder_a: 384 complexity_decoder_b: 512 [model.villain] lowmem: False [trainer.original] preview_images: 4 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 --------- gui.ini --------- [global] fullscreen: False tab: extract options_panel_width: 30 console_panel_height: 20 icon_size: 14 font: default font_size: 9 autosave_last_session: prompt timeout: 120 auto_load_model_stats: True
User avatar
torzdf
Posts: 2202
Joined: Fri Jul 12, 2019 12:53 am
Answers: 141
Has thanked: 108 times
Been thanked: 502 times

Re: StoJo preset is crashing

Post by torzdf »

This is a bug which appears to have been introduced into EfficientNet by Tensorflow itself. It is caused by enabling 'mixed-precision' training. I am not sure whether it is fixable by me, seeing as it occurs within the model rather than within faceswap code.

I have flagged this as a bug to investigate (I am hoping the issue resolves itself on the next tensorflow update).

In the meantime, I suggest either disabling Mixed Precision (if you can) or swapping the encoder for EfficientNetV2_S

My word is final

User avatar
shini719
Posts: 2
Joined: Tue Nov 01, 2022 9:40 pm

Re: StoJo preset is crashing

Post by shini719 »

Oh changing it to EfficientNet V2 S worked! Thanks!

User avatar
torzdf
Posts: 2202
Joined: Fri Jul 12, 2019 12:53 am
Answers: 141
Has thanked: 108 times
Been thanked: 502 times

Re: StoJo preset is crashing

Post by torzdf »

This bug has been patched, and StoJo (and EffnetV1 more widely) should now be functional again.

My word is final

Post Reply