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Help! Unknown: CUDNN_STATUS_EXECUTION_FAILED Error out of the blue after PC crashed. Reinstall won't Fix

Posted: Tue Mar 19, 2024 2:27 pm
by hassamc

All was good until PC crashed, after restart I got this and I can't seem to get rid of it.

Code: Select all

03/19/2024 10:13:07 MainProcess     _training                      generator       _load_generator                DEBUG    Loading generator, side: b, is_display: True,  batch_size: 14
03/19/2024 10:13:07 MainProcess     _training                      generator       __init__                       DEBUG    Initializing PreviewDataGenerator: (model: villain, side: b, images: 11756 , batch_size: 14, config: {'centering': 'face', 'coverage': 87.5, 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -7, 'save_optimizer': 'exit', 'lr_finder_iterations': 1000, 'lr_finder_mode': 'set', 'lr_finder_strength': 'default', 'autoclip': False, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ssim', 'loss_function_2': 'mse', 'loss_weight_2': 100, 'loss_function_3': None, 'loss_weight_3': 0, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mse', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'preview_images': 14, 'mask_opacity': 30, 'mask_color': '#ff0000', '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})
03/19/2024 10:13:07 MainProcess     _training                      generator       _get_output_sizes              DEBUG    side: b, model output shapes: [(None, 128, 128, 3), (None, 128, 128, 3)], output sizes: [128]
03/19/2024 10:13:07 MainProcess     _training                      cache           __init__                       DEBUG    Initializing: RingBuffer (batch_size: 14, image_shape: (128, 128, 6), buffer_size: 2, dtype: uint8
03/19/2024 10:13:07 MainProcess     _training                      cache           __init__                       DEBUG    Initialized: RingBuffer
03/19/2024 10:13:07 MainProcess     _training                      generator       __init__                       DEBUG    Initialized PreviewDataGenerator
03/19/2024 10:13:07 MainProcess     _training                      generator       minibatch_ab                   DEBUG    do_shuffle: True
03/19/2024 10:13:07 MainProcess     _training                      multithreading  __init__                       DEBUG    Initializing BackgroundGenerator: (target: '_run_2', thread_count: 1)
03/19/2024 10:13:07 MainProcess     _training                      multithreading  __init__                       DEBUG    Initialized BackgroundGenerator: '_run_2'
03/19/2024 10:13:07 MainProcess     _training                      multithreading  start                          DEBUG    Starting thread(s): '_run_2'
03/19/2024 10:13:07 MainProcess     _training                      multithreading  start                          DEBUG    Starting thread 1 of 1: '_run_2'
03/19/2024 10:13:07 MainProcess     _run_2                         generator       _minibatch                     DEBUG    Loading minibatch generator: (image_count: 11756, do_shuffle: True)
03/19/2024 10:13:07 MainProcess     _training                      multithreading  start                          DEBUG    Started all threads '_run_2': 1
03/19/2024 10:13:07 MainProcess     _training                      generator       __init__                       DEBUG    Initialized Feeder:
03/19/2024 10:13:07 MainProcess     _training                      lr_finder       __init__                       DEBUG    Initializing LearningRateFinder: (model: <plugins.train.model.villain.Model object at 0x00000112679F1A20>, config: {'centering': 'face', 'coverage': 87.5, 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'epsilon_exponent': -7, 'save_optimizer': 'exit', 'lr_finder_iterations': 1000, 'lr_finder_mode': 'set', 'lr_finder_strength': 'default', 'autoclip': False, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, 'nan_protection': True, 'convert_batchsize': 16, 'loss_function': 'ssim', 'loss_function_2': 'mse', 'loss_weight_2': 100, 'loss_function_3': None, 'loss_weight_3': 0, 'loss_function_4': None, 'loss_weight_4': 0, 'mask_loss_function': 'mse', 'eye_multiplier': 3, 'mouth_multiplier': 2, 'penalized_mask_loss': True, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'preview_images': 14, 'mask_opacity': 30, 'mask_color': '#ff0000', '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}, feeder: <lib.training.generator.Feeder object at 0x000001126A3F87C0>, stop_factor: 4, beta: 0.98)
03/19/2024 10:13:07 MainProcess     _training                      lr_finder       __init__                       DEBUG    Initialized LearningRateFinder
03/19/2024 10:13:07 MainProcess     _training                      io              save                           DEBUG    Backing up and saving models
03/19/2024 10:13:07 MainProcess     _training                      io              _get_save_averages             DEBUG    Getting save averages
03/19/2024 10:13:07 MainProcess     _training                      io              _get_save_averages             DEBUG    No loss in history
03/19/2024 10:13:07 MainProcess     _training                      io              _get_save_averages             DEBUG    Average losses since last save: []
03/19/2024 10:13:07 MainProcess     _run                           cache           _validate_version              DEBUG    Setting initial extract version: 2.3
03/19/2024 10:13:08 MainProcess     _training                      attrs           create                         DEBUG    Creating converter from 5 to 3
03/19/2024 10:13:08 MainProcess     _run_0                         cache           _validate_version              DEBUG    Setting initial extract version: 2.3
03/19/2024 10:13:08 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:09 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:09 MainProcess     _training                      model           save                           DEBUG    Saving State
03/19/2024 10:13:09 MainProcess     _training                      serializer      save                           DEBUG    filename: E:\Users\Hassam\Documents\EXP\Models\CLIPV3\villain_state.json, data type: <class 'dict'>
03/19/2024 10:13:09 MainProcess     _training                      serializer      _check_extension               DEBUG    Original filename: 'E:\Users\Hassam\Documents\EXP\Models\CLIPV3\villain_state.json', final filename: 'E:\Users\Hassam\Documents\EXP\Models\CLIPV3\villain_state.json'
03/19/2024 10:13:09 MainProcess     _training                      serializer      marshal                        DEBUG    data type: <class 'dict'>
03/19/2024 10:13:09 MainProcess     _training                      serializer      marshal                        DEBUG    returned data type: <class 'bytes'>
03/19/2024 10:13:09 MainProcess     _training                      model           save                           DEBUG    Saved State
03/19/2024 10:13:09 MainProcess     _training                      io              save                           INFO     [Saved model]
03/19/2024 10:13:09 MainProcess     _training                      lr_finder       _train                         INFO     Finding optimal learning rate...
03/19/2024 10:13:10 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:10 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011265E58FD0>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:11 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831A9E0>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831B7C0>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000112264EA8F0>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831B550>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831A830>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000112283199F0>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:11 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228319CC0>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228319B70>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228319E40>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831ACB0>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228318C40>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:12 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:12 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011265E58FD0>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831A9E0>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:13 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831B7C0>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000112264EA8F0>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831B550>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831A830>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000112283199F0>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228319CC0>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228319B70>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228319E40>, weight: 1.0, mask_channel: 3)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 3
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x000001122831ACB0>, weight: 3.0, mask_channel: 4)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 4
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x0000011228318C40>, weight: 2.0, mask_channel: 5)
03/19/2024 10:13:13 MainProcess     _training                      api             converted_call                 DEBUG    Applying mask from channel 5
03/19/2024 10:13:14 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:15 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:16 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:17 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:18 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:19 MainProcess     preview                        preview_cv      _launch                        DEBUG    Waiting for preview image
03/19/2024 10:13:19 MainProcess     _training                      multithreading  run                            DEBUG    Error in thread (_training): Graph execution error:\n\nDetected at node 'villain/encoder/conv_128_0_conv2d/Conv2D_1' defined at (most recent call last):\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\threading.py", line 973, in _bootstrap\n      self._bootstrap_inner()\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\threading.py", line 1016, in _bootstrap_inner\n      self.run()\n    File "C:\Users\Hassam\faceswap\lib\multithreading.py", line 100, in run\n      self._target(*self._args, **self._kwargs)\n    File "C:\Users\Hassam\faceswap\scripts\train.py", line 260, in _training\n      trainer = self._load_trainer(model)\n    File "C:\Users\Hassam\faceswap\scripts\train.py", line 309, in _load_trainer\n      trainer: TrainerBase = base(model,\n    File "C:\Users\Hassam\faceswap\plugins\train\trainer\original.py", line 10, in __init__\n      super().__init__(*args, **kwargs)\n    File "C:\Users\Hassam\faceswap\plugins\train\trainer\_base.py", line 87, in __init__\n      self._exit_early = self._handle_lr_finder()\n    File "C:\Users\Hassam\faceswap\plugins\train\trainer\_base.py", line 162, in _handle_lr_finder\n      success = lrf.find()\n    File "C:\Users\Hassam\faceswap\lib\training\lr_finder.py", line 182, in find\n      self._train()\n    File "C:\Users\Hassam\faceswap\lib\training\lr_finder.py", line 134, in _train\n      loss: list[float] = self._model.model.train_on_batch(model_inputs, y=model_targets)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 2381, in train_on_batch\n      logs = self.train_function(iterator)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1160, in train_function\n      return step_function(self, iterator)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1146, in step_function\n      outputs = model.distribute_strategy.run(run_step, args=(data,))\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1135, in run_step\n      outputs = model.train_step(data)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 993, in train_step\n      y_pred = self(x, training=True)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 557, in __call__\n      return super().__call__(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 1097, in __call__\n      outputs = call_fn(inputs, *args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 510, in call\n      return self._run_internal_graph(inputs, training=training, mask=mask)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 667, in _run_internal_graph\n      outputs = node.layer(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 557, in __call__\n      return super().__call__(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 1097, in __call__\n      outputs = call_fn(inputs, *args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 510, in call\n      return self._run_internal_graph(inputs, training=training, mask=mask)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 667, in _run_internal_graph\n      outputs = node.layer(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 1097, in __call__\n      outputs = call_fn(inputs, *args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler\n      return fn(*args, **kwargs)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\layers\convolutional\base_conv.py", line 283, in call\n      outputs = self.convolution_op(inputs, self.kernel)\n    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\layers\convolutional\base_conv.py", line 255, in convolution_op\n      return tf.nn.convolution(\nNode: 'villain/encoder/conv_128_0_conv2d/Conv2D_1'\nNo algorithm worked!  Error messages:\n  Profiling failure on CUDNN engine 1#TC: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED\nin tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'\n  Profiling failure on CUDNN engine 1: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED\nin tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'\n  Profiling failure on CUDNN engine 0#TC: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED\nin tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'\n  Profiling failure on CUDNN engine 0: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED\nin tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'\n	 [[{{node villain/encoder/conv_128_0_conv2d/Conv2D_1}}]] [Op:__inference_train_function_17140]
03/19/2024 10:13:20 MainProcess     MainThread                     train           _monitor                       DEBUG    Thread error detected
03/19/2024 10:13:20 MainProcess     MainThread                     train           shutdown                       DEBUG    Sending shutdown to preview viewer
03/19/2024 10:13:20 MainProcess     MainThread                     train           _monitor                       DEBUG    Closed Monitor
03/19/2024 10:13:20 MainProcess     MainThread                     train           _end_thread                    DEBUG    Ending Training thread
03/19/2024 10:13:20 MainProcess     MainThread                     train           _end_thread                    CRITICAL Error caught! Exiting...
03/19/2024 10:13:20 MainProcess     MainThread                     multithreading  join                           DEBUG    Joining Threads: '_training'
03/19/2024 10:13:20 MainProcess     MainThread                     multithreading  join                           DEBUG    Joining Thread: '_training'
03/19/2024 10:13:20 MainProcess     MainThread                     multithreading  join                           ERROR    Caught exception in thread: '_training'
Traceback (most recent call last):
  File "C:\Users\Hassam\faceswap\lib\cli\launcher.py", line 225, in execute_script
    process.process()
  File "C:\Users\Hassam\faceswap\scripts\train.py", line 209, in process
    self._end_thread(thread, err)
  File "C:\Users\Hassam\faceswap\scripts\train.py", line 249, in _end_thread
    thread.join()
  File "C:\Users\Hassam\faceswap\lib\multithreading.py", line 224, in join
    raise thread.err[1].with_traceback(thread.err[2])
  File "C:\Users\Hassam\faceswap\lib\multithreading.py", line 100, in run
    self._target(*self._args, **self._kwargs)
  File "C:\Users\Hassam\faceswap\scripts\train.py", line 274, in _training
    raise err
  File "C:\Users\Hassam\faceswap\scripts\train.py", line 260, in _training
    trainer = self._load_trainer(model)
  File "C:\Users\Hassam\faceswap\scripts\train.py", line 309, in _load_trainer
    trainer: TrainerBase = base(model,
  File "C:\Users\Hassam\faceswap\plugins\train\trainer\original.py", line 10, in __init__
    super().__init__(*args, **kwargs)
  File "C:\Users\Hassam\faceswap\plugins\train\trainer\_base.py", line 87, in __init__
    self._exit_early = self._handle_lr_finder()
  File "C:\Users\Hassam\faceswap\plugins\train\trainer\_base.py", line 162, in _handle_lr_finder
    success = lrf.find()
  File "C:\Users\Hassam\faceswap\lib\training\lr_finder.py", line 182, in find
    self._train()
  File "C:\Users\Hassam\faceswap\lib\training\lr_finder.py", line 134, in _train
    loss: list[float] = self._model.model.train_on_batch(model_inputs, y=model_targets)
  File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 2381, in train_on_batch
    logs = self.train_function(iterator)
  File "C:\Users\Hassam\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\Hassam\miniconda3\envs\faceswap\lib\site-packages\tensorflow\python\eager\execute.py", line 54, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.NotFoundError: Graph execution error:

Detected at node 'villain/encoder/conv_128_0_conv2d/Conv2D_1' defined at (most recent call last):
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\threading.py", line 973, in _bootstrap
      self._bootstrap_inner()
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\threading.py", line 1016, in _bootstrap_inner
      self.run()
    File "C:\Users\Hassam\faceswap\lib\multithreading.py", line 100, in run
      self._target(*self._args, **self._kwargs)
    File "C:\Users\Hassam\faceswap\scripts\train.py", line 260, in _training
      trainer = self._load_trainer(model)
    File "C:\Users\Hassam\faceswap\scripts\train.py", line 309, in _load_trainer
      trainer: TrainerBase = base(model,
    File "C:\Users\Hassam\faceswap\plugins\train\trainer\original.py", line 10, in __init__
      super().__init__(*args, **kwargs)
    File "C:\Users\Hassam\faceswap\plugins\train\trainer\_base.py", line 87, in __init__
      self._exit_early = self._handle_lr_finder()
    File "C:\Users\Hassam\faceswap\plugins\train\trainer\_base.py", line 162, in _handle_lr_finder
      success = lrf.find()
    File "C:\Users\Hassam\faceswap\lib\training\lr_finder.py", line 182, in find
      self._train()
    File "C:\Users\Hassam\faceswap\lib\training\lr_finder.py", line 134, in _train
      loss: list[float] = self._model.model.train_on_batch(model_inputs, y=model_targets)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 2381, in train_on_batch
      logs = self.train_function(iterator)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1160, in train_function
      return step_function(self, iterator)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1146, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1135, in run_step
      outputs = model.train_step(data)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 993, in train_step
      y_pred = self(x, training=True)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 557, in __call__
      return super().__call__(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 1097, in __call__
      outputs = call_fn(inputs, *args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 510, in call
      return self._run_internal_graph(inputs, training=training, mask=mask)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 667, in _run_internal_graph
      outputs = node.layer(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 557, in __call__
      return super().__call__(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 1097, in __call__
      outputs = call_fn(inputs, *args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 510, in call
      return self._run_internal_graph(inputs, training=training, mask=mask)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\functional.py", line 667, in _run_internal_graph
      outputs = node.layer(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 1097, in __call__
      outputs = call_fn(inputs, *args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\utils\traceback_utils.py", line 96, in error_handler
      return fn(*args, **kwargs)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\layers\convolutional\base_conv.py", line 283, in call
      outputs = self.convolution_op(inputs, self.kernel)
    File "C:\Users\Hassam\miniconda3\envs\faceswap\lib\site-packages\keras\layers\convolutional\base_conv.py", line 255, in convolution_op
      return tf.nn.convolution(
Node: 'villain/encoder/conv_128_0_conv2d/Conv2D_1'
No algorithm worked!  Error messages:
  Profiling failure on CUDNN engine 1#TC: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED
in tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'
  Profiling failure on CUDNN engine 1: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED
in tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'
  Profiling failure on CUDNN engine 0#TC: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED
in tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'
  Profiling failure on CUDNN engine 0: UNKNOWN: CUDNN_STATUS_EXECUTION_FAILED
in tensorflow/stream_executor/cuda/cuda_dnn.cc(4031): 'cudnnConvolutionForward( cudnn.handle(), alpha, input_nd_.handle(), input_data.opaque(), filter_.handle(), filter_data.opaque(), conv_.handle(), ToConvForwardAlgo(algo), scratch_memory.opaque(), scratch_memory.size(), beta, output_nd_.handle(), output_data.opaque())'
	 [[{{node villain/encoder/conv_128_0_conv2d/Conv2D_1}}]] [Op:__inference_train_function_17140]

============ System Information ============
backend:             nvidia
encoding:            cp1252
git_branch:          master
git_commits:         63b4d91 Bugfix: Mask tool - correctly name imported mask
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 3080
gpu_devices_active:  GPU_0
gpu_driver:          555.41
gpu_vram:            GPU_0: 10240MB (150MB free)
os_machine:          AMD64
os_platform:         Windows-10-10.0.26080-SP0
os_release:          10
py_command:          C:\Users\Hassam\faceswap\faceswap.py train -A C:/Users/Hassam/Downloads/Pdown/capture -B E:/Users/Hassam/Documents/EXP/TCat/BIS1024ext1 -m E:/Users/Hassam/Documents/EXP/Models/CLIPV3 -t villain -bs 1 -it 200000 -D default -r -s 250 -ss 10000 -p -L INFO -gui
py_conda_version:    conda 24.3.0
py_implementation:   CPython
py_version:          3.10.13
py_virtual_env:      True
sys_cores:           16
sys_processor:       AMD64 Family 25 Model 97 Stepping 2, AuthenticAMD
sys_ram:             Total: 31893MB, Available: 9442MB, Used: 22451MB, Free: 9442MB

=============== Pip Packages ===============
absl-py==2.1.0
astunparse==1.6.3
cachetools==5.3.3
certifi==2024.2.2
charset-normalizer==3.3.2
colorama @ file:///C:/b/abs_a9ozq0l032/croot/colorama_1672387194846/work
contourpy @ file:///C:/b/abs_853rfy8zse/croot/contourpy_1700583617587/work
cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work
fastcluster @ file:///D:/bld/fastcluster_1695650232190/work
ffmpy @ file:///home/conda/feedstock_root/build_artifacts/ffmpy_1659474992694/work
flatbuffers==24.3.7
fonttools==4.25.0
gast==0.4.0
google-auth==2.28.2
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.62.1
h5py==3.10.0
idna==3.6
imageio @ file:///C:/b/abs_aeqerw_nps/croot/imageio_1707247365204/work
imageio-ffmpeg==0.4.9
joblib @ file:///C:/b/abs_1anqjntpan/croot/joblib_1685113317150/work
keras==2.10.0
Keras-Preprocessing==1.1.2
kiwisolver @ file:///C:/b/abs_88mdhvtahm/croot/kiwisolver_1672387921783/work
libclang==18.1.1
Markdown==3.6
MarkupSafe==2.1.5
matplotlib @ file:///C:/b/abs_e26vnvd5s1/croot/matplotlib-suite_1698692153288/work
mkl-fft @ file:///C:/b/abs_19i1y8ykas/croot/mkl_fft_1695058226480/work
mkl-random @ file:///C:/b/abs_edwkj1_o69/croot/mkl_random_1695059866750/work
mkl-service==2.4.0
munkres==1.1.4
numexpr @ file:///C:/b/abs_5fucrty5dc/croot/numexpr_1696515448831/work
numpy @ file:///C:/b/abs_c1ywpu18ar/croot/numpy_and_numpy_base_1708638681471/work/dist/numpy-1.26.4-cp310-cp310-win_amd64.whl#sha256=ebb5aa2b36d8afa5ec3231c19e5a1fc75b6d85e7db483f0fb9e77dad58469977
nvidia-ml-py @ file:///home/conda/feedstock_root/build_artifacts/nvidia-ml-py_1698947663801/work
oauthlib==3.2.2
opencv-python==4.9.0.80
opt-einsum==3.3.0
packaging @ file:///C:/b/abs_cc1h2xfosn/croot/packaging_1710807447479/work
Pillow @ file:///C:/b/abs_153xikw91n/croot/pillow_1695134603563/work
ply==3.11
protobuf==3.19.6
psutil @ file:///C:/Windows/Temp/abs_b2c2fd7f-9fd5-4756-95ea-8aed74d0039flsd9qufz/croots/recipe/psutil_1656431277748/work
pyasn1==0.5.1
pyasn1-modules==0.3.0
pyparsing @ file:///C:/Users/BUILDE~1/AppData/Local/Temp/abs_7f_7lba6rl/croots/recipe/pyparsing_1661452540662/work
PyQt5==5.15.10
PyQt5-sip @ file:///C:/b/abs_c0pi2mimq3/croot/pyqt-split_1698769125270/work/pyqt_sip
python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
pywin32==305.1
pywinpty @ file:///C:/ci_310/pywinpty_1644230983541/work/target/wheels/pywinpty-2.0.2-cp310-none-win_amd64.whl
requests==2.31.0
requests-oauthlib==1.4.0
rsa==4.9
scikit-learn @ file:///C:/b/abs_daon7wm2p4/croot/scikit-learn_1694788586973/work
scipy==1.11.4
sip @ file:///C:/b/abs_edevan3fce/croot/sip_1698675983372/work
six @ file:///tmp/build/80754af9/six_1644875935023/work
tensorboard==2.10.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow==2.10.1
tensorflow-estimator==2.10.0
tensorflow-io-gcs-filesystem==0.31.0
termcolor==2.4.0
threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
tomli @ file:///C:/Windows/TEMP/abs_ac109f85-a7b3-4b4d-bcfd-52622eceddf0hy332ojo/croots/recipe/tomli_1657175513137/work
tornado @ file:///C:/b/abs_0cbrstidzg/croot/tornado_1696937003724/work
tqdm @ file:///C:/b/abs_f76j9hg7pv/croot/tqdm_1679561871187/work
typing_extensions==4.10.0
urllib3==2.2.1
Werkzeug==3.0.1
wrapt==1.16.0

============== Conda Packages ==============
# packages in environment at C:\Users\Hassam\miniconda3\envs\faceswap:
#
# Name                    Version                   Build  Channel
absl-py                   2.1.0                    pypi_0    pypi
aom                       3.7.1                h63175ca_0    conda-forge
astunparse                1.6.3                    pypi_0    pypi
blas                      1.0                         mkl  
brotli                    1.0.9                h2bbff1b_7  
brotli-bin                1.0.9                h2bbff1b_7  
bzip2                     1.0.8                h2bbff1b_5  
ca-certificates           2024.3.11            haa95532_0  
cachetools                5.3.3                    pypi_0    pypi
certifi                   2024.2.2                 pypi_0    pypi
charset-normalizer        3.3.2                    pypi_0    pypi
colorama                  0.4.6           py310haa95532_0  
contourpy                 1.2.0           py310h59b6b97_0  
cudatoolkit               11.2.2              h7d7167e_13    conda-forge
cudnn                     8.1.0.77             h3e0f4f4_0    conda-forge
cycler                    0.11.0             pyhd3eb1b0_0  
dav1d                     1.2.1                hcfcfb64_0    conda-forge
expat                     2.6.2                h63175ca_0    conda-forge
fastcluster               1.2.6           py310hecd3228_3    conda-forge
ffmpeg                    6.1.0           gpl_h0859920_103    conda-forge
ffmpy                     0.3.0              pyhb6f538c_0    conda-forge
flatbuffers               24.3.7                   pypi_0    pypi
font-ttf-dejavu-sans-mono 2.37                 hab24e00_0    conda-forge
font-ttf-inconsolata      3.000                h77eed37_0    conda-forge
font-ttf-source-code-pro  2.038                h77eed37_0    conda-forge
font-ttf-ubuntu           0.83                 h77eed37_1    conda-forge
fontconfig                2.14.2               hbde0cde_0    conda-forge
fonts-conda-ecosystem     1                             0    conda-forge
fonts-conda-forge         1                             0    conda-forge
fonttools                 4.25.0             pyhd3eb1b0_0  
freetype                  2.12.1               ha860e81_0  
gast                      0.4.0                    pypi_0    pypi
giflib                    5.2.1                h8cc25b3_3  
git                       2.40.1               haa95532_1  
google-auth               2.28.2                   pypi_0    pypi
google-auth-oauthlib      0.4.6                    pypi_0    pypi
google-pasta              0.2.0                    pypi_0    pypi
grpcio                    1.62.1                   pypi_0    pypi
h5py                      3.10.0                   pypi_0    pypi
icc_rt                    2022.1.0             h6049295_2  
icu                       73.1                 h6c2663c_0  
idna                      3.6                      pypi_0    pypi
imageio                   2.33.1          py310haa95532_0  
imageio-ffmpeg            0.4.9                    pypi_0    pypi
intel-openmp              2023.1.0         h59b6b97_46320  
joblib                    1.2.0           py310haa95532_0  
jpeg                      9e                   h2bbff1b_1  
keras                     2.10.0                   pypi_0    pypi
keras-preprocessing       1.1.2                    pypi_0    pypi
kiwisolver                1.4.4           py310hd77b12b_0  
krb5                      1.20.1               h5b6d351_0  
lerc                      3.0                  hd77b12b_0  
libbrotlicommon           1.0.9                h2bbff1b_7  
libbrotlidec              1.0.9                h2bbff1b_7  
libbrotlienc              1.0.9                h2bbff1b_7  
libclang                  18.1.1                   pypi_0    pypi
libclang13                14.0.6          default_h8e68704_1  
libdeflate                1.17                 h2bbff1b_1  
libexpat                  2.6.2                h63175ca_0    conda-forge
libffi                    3.4.4                hd77b12b_0  
libiconv                  1.17                 hcfcfb64_2    conda-forge
libopus                   1.3.1                h8ffe710_1    conda-forge
libpng                    1.6.39               h8cc25b3_0  
libpq                     12.17                h906ac69_0  
libtiff                   4.5.1                hd77b12b_0  
libwebp                   1.3.2                hbc33d0d_0  
libwebp-base              1.3.2                h2bbff1b_0  
libxml2                   2.12.6               hc3477c8_0    conda-forge
libzlib                   1.2.13               hcfcfb64_5    conda-forge
libzlib-wapi              1.2.13               hcfcfb64_5    conda-forge
lz4-c                     1.9.4                h2bbff1b_0  
markdown                  3.6                      pypi_0    pypi
markupsafe                2.1.5                    pypi_0    pypi
matplotlib                3.8.0           py310haa95532_0  
matplotlib-base           3.8.0           py310h4ed8f06_0  
mkl                       2023.1.0         h6b88ed4_46358  
mkl-service               2.4.0           py310h2bbff1b_1  
mkl_fft                   1.3.8           py310h2bbff1b_0  
mkl_random                1.2.4           py310h59b6b97_0  
munkres                   1.1.4                      py_0  
numexpr                   2.8.7           py310h2cd9be0_0  
numpy                     1.26.4          py310h055cbcc_0  
numpy-base                1.26.4          py310h65a83cf_0  
nvidia-ml-py              12.535.133         pyhd8ed1ab_0    conda-forge
oauthlib                  3.2.2                    pypi_0    pypi
opencv-python             4.9.0.80                 pypi_0    pypi
openh264                  2.4.0                h63175ca_0    conda-forge
openssl                   3.2.1                hcfcfb64_1    conda-forge
opt-einsum                3.3.0                    pypi_0    pypi
packaging                 23.2            py310haa95532_0  
pillow                    9.4.0           py310hd77b12b_1  
pip                       23.3.1          py310haa95532_0  
ply                       3.11            py310haa95532_0  
protobuf                  3.19.6                   pypi_0    pypi
psutil                    5.9.0           py310h2bbff1b_0  
pyasn1                    0.5.1                    pypi_0    pypi
pyasn1-modules            0.3.0                    pypi_0    pypi
pyparsing                 3.0.9           py310haa95532_0  
pyqt                      5.15.10         py310hd77b12b_0  
pyqt5-sip                 12.13.0         py310h2bbff1b_0  
python                    3.10.13              he1021f5_0  
python-dateutil           2.8.2              pyhd3eb1b0_0  
python_abi                3.10                    2_cp310    conda-forge
pywin32                   305             py310h2bbff1b_0  
pywinpty                  2.0.2           py310h5da7b33_0  
qt-main                   5.15.2              h19c9488_10  
requests                  2.31.0                   pypi_0    pypi
requests-oauthlib         1.4.0                    pypi_0    pypi
rsa                       4.9                      pypi_0    pypi
scikit-learn              1.3.0           py310h4ed8f06_1  
scipy                     1.11.4          py310h309d312_0  
setuptools                68.2.2          py310haa95532_0  
sip                       6.7.12          py310hd77b12b_0  
six                       1.16.0             pyhd3eb1b0_1  
sqlite                    3.41.2               h2bbff1b_0  
svt-av1                   1.7.0                h63175ca_0    conda-forge
tbb                       2021.8.0             h59b6b97_0  
tensorboard               2.10.1                   pypi_0    pypi
tensorboard-data-server   0.6.1                    pypi_0    pypi
tensorboard-plugin-wit    1.8.1                    pypi_0    pypi
tensorflow                2.10.1                   pypi_0    pypi
tensorflow-estimator      2.10.0                   pypi_0    pypi
tensorflow-io-gcs-filesystem 0.31.0                   pypi_0    pypi
termcolor                 2.4.0                    pypi_0    pypi
threadpoolctl             2.2.0              pyh0d69192_0  
tk                        8.6.12               h2bbff1b_0  
tomli                     2.0.1           py310haa95532_0  
tornado                   6.3.3           py310h2bbff1b_0  
tqdm                      4.65.0          py310h9909e9c_0  
typing-extensions         4.10.0                   pypi_0    pypi
tzdata                    2024a                h04d1e81_0  
ucrt                      10.0.22621.0         h57928b3_0    conda-forge
urllib3                   2.2.1                    pypi_0    pypi
vc                        14.2                 h21ff451_1  
vc14_runtime              14.38.33130         h82b7239_18    conda-forge
vs2015_runtime            14.38.33130         hcb4865c_18    conda-forge
werkzeug                  3.0.1                    pypi_0    pypi
wheel                     0.41.2          py310haa95532_0  
winpty                    0.4.3                         4  
wrapt                     1.16.0                   pypi_0    pypi
x264                      1!164.3095           h8ffe710_2    conda-forge
x265                      3.5                  h2d74725_3    conda-forge
xz                        5.4.6                h8cc25b3_0  
zlib                      1.2.13               hcfcfb64_5    conda-forge
zlib-wapi                 1.2.13               hcfcfb64_5    conda-forge
zstd                      1.5.5                hd43e919_0  

=============== State File =================
{
  "name": "villain",
  "sessions": {
    "1": {
      "timestamp": 1710857584.2884378,
      "no_logs": false,
      "loss_names": [
        "total",
        "face_a",
        "face_b"
      ],
      "batchsize": 0,
      "iterations": 0,
      "config": {
        "learning_rate": 5e-05,
        "epsilon_exponent": -7,
        "save_optimizer": "exit",
        "autoclip": false,
        "allow_growth": false,
        "mixed_precision": false,
        "nan_protection": true,
        "convert_batchsize": 16,
        "loss_function": "ssim",
        "loss_function_2": "mse",
        "loss_weight_2": 100,
        "loss_function_3": null,
        "loss_weight_3": 0,
        "loss_function_4": null,
        "loss_weight_4": 0,
        "mask_loss_function": "mse",
        "eye_multiplier": 3,
        "mouth_multiplier": 2
      }
    }
  },
  "lowest_avg_loss": {},
  "iterations": 0,
  "mixed_precision_layers": [
    "conv_128_0_conv2d",
    "leaky_re_lu",
    "residual_128_0_conv2d_0",
    "residual_128_0_leakyrelu_1",
    "residual_128_0_conv2d_1",
    "add",
    "residual_128_0_leakyrelu_3",
    "residual_128_1_conv2d_0",
    "residual_128_1_leakyrelu_1",
    "residual_128_1_conv2d_1",
    "add_1",
    "residual_128_1_leakyrelu_3",
    "residual_128_2_conv2d_0",
    "residual_128_2_leakyrelu_1",
    "residual_128_2_conv2d_1",
    "add_2",
    "residual_128_2_leakyrelu_3",
    "residual_128_3_conv2d_0",
    "residual_128_3_leakyrelu_1",
    "residual_128_3_conv2d_1",
    "add_3",
    "residual_128_3_leakyrelu_3",
    "residual_128_4_conv2d_0",
    "residual_128_4_leakyrelu_1",
    "residual_128_4_conv2d_1",
    "add_4",
    "residual_128_4_leakyrelu_3",
    "residual_128_5_conv2d_0",
    "residual_128_5_leakyrelu_1",
    "residual_128_5_conv2d_1",
    "add_5",
    "residual_128_5_leakyrelu_3",
    "residual_128_6_conv2d_0",
    "residual_128_6_leakyrelu_1",
    "residual_128_6_conv2d_1",
    "add_6",
    "residual_128_6_leakyrelu_3",
    "residual_128_7_conv2d_0",
    "residual_128_7_leakyrelu_1",
    "residual_128_7_conv2d_1",
    "add_7",
    "residual_128_7_leakyrelu_3",
    "residual_128_8_conv2d_0",
    "residual_128_8_leakyrelu_1",
    "residual_128_8_conv2d_1",
    "add_8",
    "residual_128_8_leakyrelu_3",
    "residual_128_9_conv2d_0",
    "residual_128_9_leakyrelu_1",
    "residual_128_9_conv2d_1",
    "add_9",
    "residual_128_9_leakyrelu_3",
    "residual_128_10_conv2d_0",
    "residual_128_10_leakyrelu_1",
    "residual_128_10_conv2d_1",
    "add_10",
    "residual_128_10_leakyrelu_3",
    "residual_128_11_conv2d_0",
    "residual_128_11_leakyrelu_1",
    "residual_128_11_conv2d_1",
    "add_11",
    "residual_128_11_leakyrelu_3",
    "residual_128_12_conv2d_0",
    "residual_128_12_leakyrelu_1",
    "residual_128_12_conv2d_1",
    "add_12",
    "residual_128_12_leakyrelu_3",
    "residual_128_13_conv2d_0",
    "residual_128_13_leakyrelu_1",
    "residual_128_13_conv2d_1",
    "add_13",
    "residual_128_13_leakyrelu_3",
    "residual_128_14_conv2d_0",
    "residual_128_14_leakyrelu_1",
    "residual_128_14_conv2d_1",
    "add_14",
    "residual_128_14_leakyrelu_3",
    "residual_128_15_conv2d_0",
    "residual_128_15_leakyrelu_1",
    "residual_128_15_conv2d_1",
    "add_15",
    "residual_128_15_leakyrelu_3",
    "leaky_re_lu_1",
    "add_16",
    "conv_128_1_conv2d",
    "conv_128_1_leakyrelu",
    "pixel_shuffler",
    "conv_128_2_conv2d",
    "conv_128_2_leakyrelu",
    "pixel_shuffler_1",
    "conv_128_3_conv2d",
    "conv_128_3_leakyrelu",
    "separableconv2d_256_0_seperableconv2d",
    "separableconv2d_256_0_relu",
    "conv_512_0_conv2d",
    "conv_512_0_leakyrelu",
    "separableconv2d_1024_0_seperableconv2d",
    "separableconv2d_1024_0_relu",
    "flatten",
    "dense",
    "dense_1",
    "reshape",
    "upscale_512_0_conv2d_conv2d",
    "upscale_512_0_conv2d_leakyrelu",
    "upscale_512_0_pixelshuffler",
    "upscale_512_1_conv2d_conv2d",
    "upscale_512_1_pixelshuffler",
    "leaky_re_lu_2",
    "residual_512_0_conv2d_0",
    "residual_512_0_leakyrelu_1",
    "residual_512_0_conv2d_1",
    "add_17",
    "residual_512_0_leakyrelu_3",
    "upscale_256_0_conv2d_conv2d",
    "upscale_256_0_pixelshuffler",
    "leaky_re_lu_3",
    "residual_256_0_conv2d_0",
    "residual_256_0_leakyrelu_1",
    "residual_256_0_conv2d_1",
    "add_18",
    "residual_256_0_leakyrelu_3",
    "upscale_128_0_conv2d_conv2d",
    "upscale_128_0_pixelshuffler",
    "leaky_re_lu_4",
    "residual_128_16_conv2d_0",
    "residual_128_16_leakyrelu_1",
    "residual_128_16_conv2d_1",
    "add_19",
    "residual_128_16_leakyrelu_3",
    "face_out_a_0_conv2d",
    "upscale_512_2_conv2d_conv2d",
    "upscale_512_2_pixelshuffler",
    "leaky_re_lu_5",
    "residual_512_1_conv2d_0",
    "residual_512_1_leakyrelu_1",
    "residual_512_1_conv2d_1",
    "add_20",
    "residual_512_1_leakyrelu_3",
    "upscale_256_1_conv2d_conv2d",
    "upscale_256_1_pixelshuffler",
    "leaky_re_lu_6",
    "residual_256_1_conv2d_0",
    "residual_256_1_leakyrelu_1",
    "residual_256_1_conv2d_1",
    "add_21",
    "residual_256_1_leakyrelu_3",
    "upscale_128_1_conv2d_conv2d",
    "upscale_128_1_pixelshuffler",
    "leaky_re_lu_7",
    "residual_128_17_conv2d_0",
    "residual_128_17_leakyrelu_1",
    "residual_128_17_conv2d_1",
    "add_22",
    "residual_128_17_leakyrelu_3",
    "face_out_b_0_conv2d"
  ],
  "config": {
    "centering": "face",
    "coverage": 87.5,
    "optimizer": "adam",
    "learning_rate": 5e-05,
    "epsilon_exponent": -7,
    "save_optimizer": "exit",
    "lr_finder_iterations": 1000,
    "lr_finder_mode": "set",
    "lr_finder_strength": "default",
    "autoclip": false,
    "allow_growth": false,
    "mixed_precision": false,
    "nan_protection": true,
    "convert_batchsize": 16,
    "loss_function": "ssim",
    "loss_function_2": "mse",
    "loss_weight_2": 100,
    "loss_function_3": null,
    "loss_weight_3": 0,
    "loss_function_4": null,
    "loss_weight_4": 0,
    "mask_loss_function": "mse",
    "eye_multiplier": 3,
    "mouth_multiplier": 2,
    "penalized_mask_loss": true,
    "mask_type": "extended",
    "mask_blur_kernel": 3,
    "mask_threshold": 4,
    "learn_mask": false,
    "lowmem": false
  }
}

================= 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.patch]
start_index:              0
index_offset:             0
number_padding:           6
include_filename:         True
face_index_location:      before
origin:                   bottom-left
empty_frames:             blank
json_output:              False
separate_mask:            False
bit_depth:                16
format:                   png
png_compress_level:       3
tiff_compression_method:  lzw

[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
aligner_features:         True
filter_refeed:            True
save_filtered:            False
realign_refeeds:          True
filter_realign:           True

[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:             False
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

--------- 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

--------- train.ini ---------

[global]
centering:                face
coverage:                 87.5
icnr_init:                False
conv_aware_init:          False
optimizer:                adam
learning_rate:            5e-05
epsilon_exponent:         -7
save_optimizer:           exit
lr_finder_iterations:     1000
lr_finder_mode:           set
lr_finder_strength:       default
autoclip:                 False
reflect_padding:          False
allow_growth:             False
mixed_precision:          False
nan_protection:           True
convert_batchsize:        16

[global.loss]
loss_function:            ssim
loss_function_2:          mse
loss_weight_2:            100
loss_function_3:          none
loss_weight_3:            0
loss_function_4:          none
loss_weight_4:            0
mask_loss_function:       mse
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
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:              7
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_upscales_in_fc:       0
dec_norm:                 none
dec_min_filters:          64
dec_max_filters:          512
dec_slope_mode:           full
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
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:           14
mask_opacity:             30
mask_color:               #ff0000
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

Re: Help! Unknown: CUDNN_STATUS_EXECUTION_FAILED Error out of the blue after PC crashed. Reinstall won't Fix

Posted: Tue Mar 19, 2024 4:07 pm
by torzdf

Ok, this is odd that it worked before, but doesn't work now.

I would normally suspect model corruption (when you crashed), but this is not a model corruption error.

See if you can start a new model with these settings... If so, then most likely your model file is corrupted.

If not, then this will probably fix your issue: app.php/faqpage#f1r1