Model training crashing on AWS - Memory Error
Posted: Tue Jun 22, 2021 7:58 pm
Everything worked fine while I used my own notebook and I was able to build some models. I am now using and instance in Amazon services (AWS). I managed to install Faceswap, extract faces, sort them and adjust alignment using Manual menu. Now I am train to train the model and the application crashes.
Can you help me please?
Please see below the messages and the message box and, right below, a copy of the Crash Report.
Code: Select all
06/22/2021 19:46:42 INFO Log level set to: INFO
06/22/2021 19:46:44 INFO Model A Directory: 'C:\Users\Administrator\Documents\new project\new extract sorted' (5364 images)
06/22/2021 19:46:44 INFO Model B Directory: 'C:\Users\Administrator\Documents\kt faces extract' (338 images)
06/22/2021 19:46:44 INFO Training data directory: C:\Users\Administrator\Documents\new project\original model
06/22/2021 19:46:44 INFO ===================================================
06/22/2021 19:46:44 INFO Starting
06/22/2021 19:46:44 INFO Press 'Stop' to save and quit
06/22/2021 19:46:44 INFO ===================================================
06/22/2021 19:46:45 INFO Loading data, this may take a while...
06/22/2021 19:46:45 INFO Loading Model from Original plugin...
06/22/2021 19:46:46 INFO No existing state file found. Generating.
06/22/2021 19:46:50 INFO Loading Trainer from Original plugin...
06/22/2021 19:47:10 CRITICAL Error caught! Exiting...
06/22/2021 19:47:10 ERROR Caught exception in thread: '_training_0'
06/22/2021 19:47:13 ERROR Got Exception on main handler:
Traceback (most recent call last):
File "C:\Users\Administrator\faceswap\lib\cli\launcher.py", line 182, in execute_script
process.process()
File "C:\Users\Administrator\faceswap\scripts\train.py", line 190, in process
self._end_thread(thread, err)
File "C:\Users\Administrator\faceswap\scripts\train.py", line 230, in _end_thread
thread.join()
File "C:\Users\Administrator\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Users\Administrator\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\Administrator\faceswap\scripts\train.py", line 252, in _training
raise err
File "C:\Users\Administrator\faceswap\scripts\train.py", line 242, in _training
self._run_training_cycle(model, trainer)
File "C:\Users\Administrator\faceswap\scripts\train.py", line 340, in _run_training_cycle
model.save()
File "C:\Users\Administrator\faceswap\plugins\train\model\_base.py", line 401, in save
self._io._save() # pylint:disable=protected-access
File "C:\Users\Administrator\faceswap\plugins\train\model\_base.py", line 597, in _save
self._plugin.model.save(self._filename, include_optimizer=False)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1978, in save
save.save_model(self, filepath, overwrite, include_optimizer, save_format,
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\saving\save.py", line 130, in save_model
hdf5_format.save_model_to_hdf5(
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\saving\hdf5_format.py", line 119, in save_model_to_hdf5
save_weights_to_hdf5_group(model_weights_group, model_layers)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\saving\hdf5_format.py", line 636, in save_weights_to_hdf5_group
weight_values = K.batch_get_value(weights)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\backend.py", line 3518, in batch_get_value
return [x.numpy() for x in tensors]
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\backend.py", line 3518, in <listcomp>
return [x.numpy() for x in tensors]
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 608, in numpy
return self.read_value().numpy()
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\framework\ops.py", line 1064, in numpy
return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
MemoryError: Unable to allocate 72.0 MiB for an array with shape (3, 3, 1024, 2048) and data type float32
06/22/2021 19:47:13 CRITICAL An unexpected crash has occurred. Crash report written to 'C:\Users\Administrator\faceswap\crash_report.2021.06.22.194710466076.log'. You MUST provide this file if seeking assistance. Please verify you are running the latest version of faceswap before reporting
Process exited.CRASH REPORT:
Code: Select all
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BBFF5550>, weight: 2.0, mask_channel: 5)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BBFF5D30>, weight: 1.0, mask_channel: 2)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC01A550>, weight: 1.0, mask_channel: 3)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC01AD30>, weight: 1.0, mask_channel: 3)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3F3250>, weight: 3.0, mask_channel: 4)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3F3850>, weight: 1.0, mask_channel: 1)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3D2580>, weight: 2.0, mask_channel: 5)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
06/22/2021 19:46:54 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3D2D60>, weight: 1.0, mask_channel: 2)
06/22/2021 19:46:54 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
06/22/2021 19:46:57 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC4FB8E0>, weight: 1.0, mask_channel: 3)
06/22/2021 19:46:57 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
06/22/2021 19:46:57 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC02C910>, weight: 1.0, mask_channel: 3)
06/22/2021 19:46:57 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
06/22/2021 19:46:57 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC0103A0>, weight: 3.0, mask_channel: 4)
06/22/2021 19:46:57 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
06/22/2021 19:46:57 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC010D60>, weight: 1.0, mask_channel: 1)
06/22/2021 19:46:57 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
06/22/2021 19:46:57 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BBFF5550>, weight: 2.0, mask_channel: 5)
06/22/2021 19:46:57 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
06/22/2021 19:46:57 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BBFF5D30>, weight: 1.0, mask_channel: 2)
06/22/2021 19:46:57 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
06/22/2021 19:46:58 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC01A550>, weight: 1.0, mask_channel: 3)
06/22/2021 19:46:58 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
06/22/2021 19:46:58 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC01AD30>, weight: 1.0, mask_channel: 3)
06/22/2021 19:46:58 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 3
06/22/2021 19:46:58 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3F3250>, weight: 3.0, mask_channel: 4)
06/22/2021 19:46:58 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 4
06/22/2021 19:46:58 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3F3850>, weight: 1.0, mask_channel: 1)
06/22/2021 19:46:58 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 1
06/22/2021 19:46:58 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3D2580>, weight: 2.0, mask_channel: 5)
06/22/2021 19:46:58 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 5
06/22/2021 19:46:58 MainProcess _training_0 tmpl99scmcr if_body DEBUG Processing loss function: (func: <tensorflow.python.keras.engine.compile_utils.LossesContainer object at 0x00000229BC3D2D60>, weight: 1.0, mask_channel: 2)
06/22/2021 19:46:58 MainProcess _training_0 losses_tf _apply_mask DEBUG Applying mask from channel 2
06/22/2021 19:47:07 MainProcess _training_0 _base generate_preview DEBUG Generating preview
06/22/2021 19:47:07 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'a', samples: 14)
06/22/2021 19:47:07 MainProcess _training_0 _base compile_sample DEBUG Compiling samples: (side: 'b', samples: 14)
06/22/2021 19:47:07 MainProcess _training_0 _base show_sample DEBUG Showing sample
06/22/2021 19:47:07 MainProcess _training_0 _base _get_predictions DEBUG Getting Predictions
06/22/2021 19:47:07 MainProcess _run_1 generator cache_metadata DEBUG All metadata already cached for: ['01451.png', '03624.png', '00100.png', '02930.png', '05609.png', '02460.png', '02356.png', '03213.png', '04926.png', '04229.png', '04143.png', '03712.png', '01126.png', '04755.png']
06/22/2021 19:47:07 MainProcess _run_1 generator cache_metadata DEBUG All metadata already cached for: ['33622072_0_0.png', '02270001_0_0.png', '_DSC4103_0_0.png', '12140065_0_0.png', '_DSC4302_0_0.png', '12140023_0_0.png', '_DSC5958_0_0.png', 'Copy (3) of DSC_0029_0_0.png', '_DSC4105_0_0.png', '12140004_0_0.png', '_DSC4259_0_0.png', '20_0_0.png', '04160001_0_0.png', '_DSC4096_0_0.png']
06/22/2021 19:47:08 MainProcess _training_0 _base _get_predictions DEBUG Returning predictions: {'a_a': (14, 64, 64, 4), 'b_b': (14, 64, 64, 4), 'a_b': (14, 64, 64, 4), 'b_a': (14, 64, 64, 4)}
06/22/2021 19:47:09 MainProcess _training_0 _base _to_full_frame DEBUG side: 'a', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 4), (14, 64, 64, 4)])
06/22/2021 19:47:09 MainProcess _training_0 _base _process_full DEBUG full_size: 384, prediction_size: 64, color: (0, 0, 255)
06/22/2021 19:47:09 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 384, 384, 3), target_size: 92, scale: 0.23958333333333334)
06/22/2021 19:47:09 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 92, 92, 3))
06/22/2021 19:47:09 MainProcess _training_0 _base _process_full DEBUG Overlayed background. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _compile_masked DEBUG masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)]
06/22/2021 19:47:09 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG side: 'a', width: 92
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG height: 20, total_width: 276
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG texts: ['Original (A)', 'Original > Original', 'Original > Swap'], text_sizes: [(52, 7), (84, 7), (73, 7)], text_x: [20, 96, 193], text_y: 13
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (20, 276, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _to_full_frame DEBUG side: 'b', number of sample arrays: 3, prediction.shapes: [(14, 64, 64, 4), (14, 64, 64, 4)])
06/22/2021 19:47:09 MainProcess _training_0 _base _process_full DEBUG full_size: 384, prediction_size: 64, color: (0, 0, 255)
06/22/2021 19:47:09 MainProcess _training_0 _base _resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 384, 384, 3), target_size: 92, scale: 0.23958333333333334)
06/22/2021 19:47:09 MainProcess _training_0 _base _resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 92, 92, 3))
06/22/2021 19:47:09 MainProcess _training_0 _base _process_full DEBUG Overlayed background. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _compile_masked DEBUG masked shapes: [(14, 64, 64, 3), (14, 64, 64, 3), (14, 64, 64, 3)]
06/22/2021 19:47:09 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _overlay_foreground DEBUG Overlayed foreground. Shape: (14, 92, 92, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG side: 'b', width: 92
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG height: 20, total_width: 276
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG texts: ['Swap (B)', 'Swap > Swap', 'Swap > Original'], text_sizes: [(43, 7), (63, 7), (73, 7)], text_x: [24, 106, 193], text_y: 13
06/22/2021 19:47:09 MainProcess _training_0 _base _get_headers DEBUG header_box.shape: (20, 276, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _duplicate_headers DEBUG side: a header.shape: (20, 276, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _duplicate_headers DEBUG side: b header.shape: (20, 276, 3)
06/22/2021 19:47:09 MainProcess _training_0 _base _stack_images DEBUG Stack images
06/22/2021 19:47:09 MainProcess _training_0 _base get_transpose_axes DEBUG Even number of images to stack
06/22/2021 19:47:09 MainProcess _training_0 _base _stack_images DEBUG Stacked images
06/22/2021 19:47:09 MainProcess _training_0 _base show_sample DEBUG Compiled sample
06/22/2021 19:47:09 MainProcess _training_0 train _show DEBUG Updating preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'ENTER': Save and Quit)
06/22/2021 19:47:09 MainProcess _training_0 train _show DEBUG Generating preview for GUI
06/22/2021 19:47:09 MainProcess _training_0 train _show DEBUG Generated preview for GUI: '.gui_training_preview.jpg'
06/22/2021 19:47:09 MainProcess _training_0 train _show DEBUG Updated preview: (name: Training - 'S': Save Now. 'R': Refresh Preview. 'M': Toggle Mask. 'ENTER': Save and Quit)
06/22/2021 19:47:09 MainProcess _training_0 train _run_training_cycle DEBUG Save Iteration: (iteration: 1
06/22/2021 19:47:09 MainProcess _training_0 _base _save DEBUG Backing up and saving models
06/22/2021 19:47:09 MainProcess _training_0 _base _get_save_averages DEBUG Getting save averages
06/22/2021 19:47:09 MainProcess _training_0 _base _get_save_averages DEBUG Average losses since last save: [0.8635251820087433, 0.7475658655166626]
06/22/2021 19:47:09 MainProcess _training_0 _base _should_backup DEBUG Set initial save iteration loss average for 'a': 0.8635251820087433
06/22/2021 19:47:09 MainProcess _training_0 _base _should_backup DEBUG Set initial save iteration loss average for 'b': 0.7475658655166626
06/22/2021 19:47:09 MainProcess _training_0 _base _should_backup DEBUG Updated lowest historical save iteration averages from: {'a': 0.8635251820087433, 'b': 0.7475658655166626} to: {'a': 0.8635251820087433, 'b': 0.7475658655166626}
06/22/2021 19:47:09 MainProcess _training_0 _base _should_backup DEBUG Should backup: True
06/22/2021 19:47:09 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): Unable to allocate 72.0 MiB for an array with shape (3, 3, 1024, 2048) and data type float32
06/22/2021 19:47:10 MainProcess MainThread train _monitor DEBUG Thread error detected
06/22/2021 19:47:10 MainProcess MainThread train _monitor DEBUG Closed Monitor
06/22/2021 19:47:10 MainProcess MainThread train _end_thread DEBUG Ending Training thread
06/22/2021 19:47:10 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
06/22/2021 19:47:10 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
06/22/2021 19:47:10 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
06/22/2021 19:47:10 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "C:\Users\Administrator\faceswap\lib\cli\launcher.py", line 182, in execute_script
process.process()
File "C:\Users\Administrator\faceswap\scripts\train.py", line 190, in process
self._end_thread(thread, err)
File "C:\Users\Administrator\faceswap\scripts\train.py", line 230, in _end_thread
thread.join()
File "C:\Users\Administrator\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Users\Administrator\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\Administrator\faceswap\scripts\train.py", line 252, in _training
raise err
File "C:\Users\Administrator\faceswap\scripts\train.py", line 242, in _training
self._run_training_cycle(model, trainer)
File "C:\Users\Administrator\faceswap\scripts\train.py", line 340, in _run_training_cycle
model.save()
File "C:\Users\Administrator\faceswap\plugins\train\model\_base.py", line 401, in save
self._io._save() # pylint:disable=protected-access
File "C:\Users\Administrator\faceswap\plugins\train\model\_base.py", line 597, in _save
self._plugin.model.save(self._filename, include_optimizer=False)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1978, in save
save.save_model(self, filepath, overwrite, include_optimizer, save_format,
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\saving\save.py", line 130, in save_model
hdf5_format.save_model_to_hdf5(
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\saving\hdf5_format.py", line 119, in save_model_to_hdf5
save_weights_to_hdf5_group(model_weights_group, model_layers)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\saving\hdf5_format.py", line 636, in save_weights_to_hdf5_group
weight_values = K.batch_get_value(weights)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\backend.py", line 3518, in batch_get_value
return [x.numpy() for x in tensors]
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\keras\backend.py", line 3518, in <listcomp>
return [x.numpy() for x in tensors]
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 608, in numpy
return self.read_value().numpy()
File "C:\Users\Administrator\MiniConda3\envs\faceswap\lib\site-packages\tensorflow\python\framework\ops.py", line 1064, in numpy
return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
MemoryError: Unable to allocate 72.0 MiB for an array with shape (3, 3, 1024, 2048) and data type float32
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: 55bb723 New Model: Phaze-A
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: Tesla T4
gpu_devices_active: GPU_0
gpu_driver: 461.40
gpu_vram: GPU_0: 15360MB
os_machine: AMD64
os_platform: Windows-10-10.0.17763-SP0
os_release: 10
py_command: C:\Users\Administrator\faceswap\faceswap.py train -A C:/Users/Administrator/Documents/new project/new extract sorted -B C:/Users/Administrator/Documents/kt faces extract -m C:/Users/Administrator/Documents/new project/original model -t original -bs 4 -it 500000 -s 250 -ss 25000 -ps 100 -L INFO -gui
py_conda_version: conda 4.10.1
py_implementation: CPython
py_version: 3.8.10
py_virtual_env: True
sys_cores: 4
sys_processor: Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
sys_ram: Total: 16083MB, Available: 11639MB, Used: 4443MB, Free: 11639MB
=============== Pip Packages ===============
absl-py @ file:///C:/ci/absl-py_1615411229697/work
aiohttp @ file:///C:/ci/aiohttp_1614361024229/work
astor==0.8.1
astunparse==1.6.3
async-timeout==3.0.1
attrs @ file:///tmp/build/80754af9/attrs_1620827162558/work
blinker==1.4
brotlipy==0.7.0
cachetools @ file:///tmp/build/80754af9/cachetools_1619597386817/work
certifi==2021.5.30
cffi @ file:///C:/ci/cffi_1613247279197/work
chardet @ file:///C:/ci/chardet_1605303225733/work
click @ file:///tmp/build/80754af9/click_1621604852318/work
coverage @ file:///C:/ci/coverage_1614615074147/work
cryptography @ file:///C:/ci/cryptography_1616769344312/work
cycler==0.10.0
Cython @ file:///C:/ci/cython_1618435363327/work
fastcluster==1.1.26
ffmpy==0.2.3
gast @ file:///tmp/build/80754af9/gast_1597433534803/work
google-auth @ file:///tmp/build/80754af9/google-auth_1623354748502/work
google-auth-oauthlib @ file:///tmp/build/80754af9/google-auth-oauthlib_1617120569401/work
google-pasta==0.2.0
grpcio @ file:///C:/ci/grpcio_1614884412260/work
h5py==2.10.0
idna @ file:///home/linux1/recipes/ci/idna_1610986105248/work
imageio @ file:///tmp/build/80754af9/imageio_1617700267927/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1621542018480/work
importlib-metadata @ file:///C:/ci/importlib-metadata_1617877484576/work
joblib @ file:///tmp/build/80754af9/joblib_1613502643832/work
Keras-Applications @ file:///tmp/build/80754af9/keras-applications_1594366238411/work
Keras-Preprocessing @ file:///tmp/build/80754af9/keras-preprocessing_1612283640596/work
kiwisolver @ file:///C:/ci/kiwisolver_1612282606037/work
Markdown @ file:///C:/ci/markdown_1614364121613/work
matplotlib @ file:///C:/ci/matplotlib-base_1592837548929/work
mkl-fft==1.3.0
mkl-random==1.1.1
mkl-service==2.3.0
multidict @ file:///C:/ci/multidict_1607362065515/work
numpy @ file:///C:/ci/numpy_and_numpy_base_1603466732592/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.5.2.54
opt-einsum @ file:///tmp/build/80754af9/opt_einsum_1621500238896/work
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1617386341487/work
protobuf==3.14.0
psutil @ file:///C:/ci/psutil_1612298324802/work
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work
PyJWT==1.7.1
pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1608057966937/work
pyparsing @ file:///home/linux1/recipes/ci/pyparsing_1610983426697/work
pyreadline==2.1
PySocks @ file:///C:/ci/pysocks_1605287845585/work
python-dateutil @ file:///home/ktietz/src/ci/python-dateutil_1611928101742/work
pywin32==227
requests @ file:///tmp/build/80754af9/requests_1608241421344/work
requests-oauthlib==1.3.0
rsa @ file:///tmp/build/80754af9/rsa_1614366226499/work
scikit-learn @ file:///C:/ci/scikit-learn_1622739500535/work
scipy @ file:///C:/ci/scipy_1616703433439/work
sip==4.19.13
six @ file:///tmp/build/80754af9/six_1623709665295/work
tensorboard @ file:///home/builder/ktietz/aggregate/tensorflow_recipes/ci_te/tensorboard_1614593728657/work/tmp_pip_dir
tensorboard-plugin-wit==1.6.0
tensorflow==2.3.0
tensorflow-estimator @ file:///home/builder/ktietz/aggregate/tensorflow_recipes/ci_baze37/tensorflow-estimator_1622026529081/work/tensorflow_estimator-2.5.0-py2.py3-none-any.whl
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tornado @ file:///C:/ci/tornado_1606942392901/work
tqdm @ file:///tmp/build/80754af9/tqdm_1615925068909/work
typing-extensions @ file:///tmp/build/80754af9/typing_extensions_1611751222202/work
urllib3 @ file:///tmp/build/80754af9/urllib3_1615837158687/work
Werkzeug @ file:///home/ktietz/src/ci/werkzeug_1611932622770/work
win-inet-pton @ file:///C:/ci/win_inet_pton_1605306167264/work
wincertstore==0.2
wrapt==1.12.1
yarl @ file:///C:/ci/yarl_1606940076464/work
zipp @ file:///tmp/build/80754af9/zipp_1615904174917/work
============== Conda Packages ==============
# packages in environment at C:\Users\Administrator\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
_tflow_select 2.3.0 gpu
absl-py 0.12.0 py38haa95532_0
aiohttp 3.7.4 py38h2bbff1b_1
astor 0.8.1 py38haa95532_0
astunparse 1.6.3 py_0
async-timeout 3.0.1 py38haa95532_0
attrs 21.2.0 pyhd3eb1b0_0
blas 1.0 mkl
blinker 1.4 py38haa95532_0
brotlipy 0.7.0 py38h2bbff1b_1003
ca-certificates 2021.5.25 haa95532_1
cachetools 4.2.2 pyhd3eb1b0_0
certifi 2021.5.30 py38haa95532_0
cffi 1.14.5 py38hcd4344a_0
chardet 3.0.4 py38haa95532_1003
click 8.0.1 pyhd3eb1b0_0
coverage 5.5 py38h2bbff1b_2
cryptography 3.4.7 py38h71e12ea_0
cudatoolkit 10.1.243 h74a9793_0
cudnn 7.6.5 cuda10.1_0
cycler 0.10.0 py38_0
cython 0.29.23 py38hd77b12b_0
fastcluster 1.1.26 py38h251f6bf_2 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.2.3 pypi_0 pypi
freetype 2.10.4 hd328e21_0
gast 0.4.0 py_0
git 2.23.0 h6bb4b03_0
google-auth 1.31.0 pyhd3eb1b0_0
google-auth-oauthlib 0.4.4 pyhd3eb1b0_0
google-pasta 0.2.0 py_0
grpcio 1.36.1 py38hc60d5dd_1
h5py 2.10.0 py38h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 pyhd3eb1b0_0
imageio 2.9.0 pyhd3eb1b0_0
imageio-ffmpeg 0.4.4 pyhd8ed1ab_0 conda-forge
importlib-metadata 3.10.0 py38haa95532_0
intel-openmp 2021.2.0 haa95532_616
joblib 1.0.1 pyhd3eb1b0_0
jpeg 9b hb83a4c4_2
keras-applications 1.0.8 py_1
keras-preprocessing 1.1.2 pyhd3eb1b0_0
kiwisolver 1.3.1 py38hd77b12b_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.14.0 h23ce68f_0
libtiff 4.2.0 hd0e1b90_0
lz4-c 1.9.3 h2bbff1b_0
markdown 3.3.4 py38haa95532_0
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py38h64f37c6_0
mkl 2020.2 256
mkl-service 2.3.0 py38h196d8e1_0
mkl_fft 1.3.0 py38h46781fe_0
mkl_random 1.1.1 py38h47e9c7a_0
multidict 5.1.0 py38h2bbff1b_2
numpy 1.19.2 py38hadc3359_0
numpy-base 1.19.2 py38ha3acd2a_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.0 py_0
olefile 0.46 py_0
opencv-python 4.5.2.54 pypi_0 pypi
openssl 1.1.1k h2bbff1b_0
opt_einsum 3.3.0 pyhd3eb1b0_1
pathlib 1.0.1 py_1
pillow 8.2.0 py38h4fa10fc_0
pip 21.1.2 py38haa95532_0
protobuf 3.14.0 py38hd77b12b_1
psutil 5.8.0 py38h2bbff1b_1
pyasn1 0.4.8 py_0
pyasn1-modules 0.2.8 py_0
pycparser 2.20 py_2
pyjwt 1.7.1 py38_0
pyopenssl 20.0.1 pyhd3eb1b0_1
pyparsing 2.4.7 pyhd3eb1b0_0
pyqt 5.9.2 py38ha925a31_4
pyreadline 2.1 py38_1
pysocks 1.7.1 py38haa95532_0
python 3.8.10 hdbf39b2_7
python-dateutil 2.8.1 pyhd3eb1b0_0
python_abi 3.8 1_cp38 conda-forge
pywin32 227 py38he774522_1
qt 5.9.7 vc14h73c81de_0
requests 2.25.1 pyhd3eb1b0_0
requests-oauthlib 1.3.0 py_0
rsa 4.7.2 pyhd3eb1b0_1
scikit-learn 0.24.2 py38hf11a4ad_1
scipy 1.6.2 py38h14eb087_0
setuptools 52.0.0 py38haa95532_0
sip 4.19.13 py38ha925a31_0
six 1.16.0 pyhd3eb1b0_0
sqlite 3.35.4 h2bbff1b_0
tensorboard 2.4.0 pyhc547734_0
tensorboard-plugin-wit 1.6.0 py_0
tensorflow 2.3.0 mkl_py38h1fcfbd6_0
tensorflow-base 2.3.0 gpu_py38h7339f5a_0
tensorflow-estimator 2.5.0 pyh7b7c402_0
tensorflow-gpu 2.3.0 he13fc11_0
termcolor 1.1.0 py38haa95532_1
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tornado 6.1 py38h2bbff1b_0
tqdm 4.59.0 pyhd3eb1b0_1
typing-extensions 3.7.4.3 hd3eb1b0_0
typing_extensions 3.7.4.3 pyh06a4308_0
urllib3 1.26.4 pyhd3eb1b0_0
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 1.0.1 pyhd3eb1b0_0
wheel 0.36.2 pyhd3eb1b0_0
win_inet_pton 1.1.0 py38haa95532_0
wincertstore 0.2 py38_0
wrapt 1.12.1 py38he774522_1
xz 5.2.5 h62dcd97_0
yarl 1.6.3 py38h2bbff1b_0
zipp 3.4.1 pyhd3eb1b0_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.9 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.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 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
jpg_quality: 75
png_compress_level: 3
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: True
[align.fan]
batch-size: 12
[detect.cv2_dnn]
confidence: 50
[detect.mtcnn]
minsize: 20
scalefactor: 0.709
batch-size: 8
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
[detect.s3fd]
confidence: 70
batch-size: 4
[mask.bisenet_fp]
batch-size: 8
include_ears: False
include_hair: False
include_glasses: True
[mask.unet_dfl]
batch-size: 8
[mask.vgg_clear]
batch-size: 6
[mask.vgg_obstructed]
batch-size: 2
--------- gui.ini ---------
[global]
fullscreen: False
tab: extract
options_panel_width: 30
console_panel_height: 20
icon_size: 14
font: default
font_size: 9
autosave_last_session: prompt
timeout: 120
auto_load_model_stats: True
--------- train.ini ---------
[global]
centering: face
coverage: 68.75
icnr_init: False
conv_aware_init: False
optimizer: adam
learning_rate: 5e-05
epsilon_exponent: -7
reflect_padding: False
allow_growth: False
mixed_precision: False
nan_protection: True
convert_batchsize: 16
[global.loss]
loss_function: ssim
mask_loss_function: mse
l2_reg_term: 100
eye_multiplier: 3
mouth_multiplier: 2
penalized_mask_loss: True
mask_type: extended
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: True
[model.dfaker]
output_size: 128
[model.dfl_h128]
lowmem: False
[model.dfl_sae]
input_size: 128
clipnorm: True
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.dlight]
features: best
details: good
output_size: 256
[model.original]
lowmem: True
[model.phaze_a]
output_size: 128
shared_fc: None
enable_gblock: True
split_fc: True
split_gblock: False
split_decoders: False
enc_architecture: fs_original
enc_scaling: 40
enc_load_weights: True
bottleneck_type: dense
bottleneck_norm: None
bottleneck_size: 1024
bottleneck_in_encoder: True
fc_depth: 1
fc_min_filters: 1024
fc_max_filters: 1024
fc_dimensions: 4
fc_filter_slope: -0.5
fc_dropout: 0.0
fc_upsampler: upsample2d
fc_upsamples: 1
fc_upsample_filters: 512
fc_gblock_depth: 3
fc_gblock_min_nodes: 512
fc_gblock_max_nodes: 512
fc_gblock_filter_slope: -0.5
fc_gblock_dropout: 0.0
dec_upscale_method: subpixel
dec_norm: None
dec_min_filters: 64
dec_max_filters: 512
dec_filter_slope: -0.45
dec_res_blocks: 1
dec_output_kernel: 5
dec_gaussian: True
dec_skip_last_residual: True
freeze_layers: keras_encoder
load_layers: encoder
fs_original_depth: 4
fs_original_min_filters: 128
fs_original_max_filters: 1024
mobilenet_width: 1.0
mobilenet_depth: 1
mobilenet_dropout: 0.001
[model.realface]
input_size: 64
output_size: 128
dense_nodes: 1536
complexity_encoder: 128
complexity_decoder: 512
[model.unbalanced]
input_size: 128
lowmem: False
clipnorm: True
nodes: 1024
complexity_encoder: 128
complexity_decoder_a: 384
complexity_decoder_b: 512
[model.villain]
lowmem: False
[trainer.original]
preview_images: 14
zoom_amount: 5
rotation_range: 10
shift_range: 5
flip_chance: 50
color_lightness: 30
color_ab: 8
color_clahe_chance: 50
color_clahe_max_size: 4