plaidml.exceptions.Unknown: No enough memory for the current schedule: required 2163167232, available 1825361152
Posted: Thu Aug 20, 2020 2:15 pm
Hi Faceswap dev.
No enough memory for the current schedule: required 2163167232, available 1825361152.
My system has 12GB of memory.
Not sure what's went wrong, been update to the latest version.
Below was the failed log.
Code: Select all
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run', thread_count: 2)
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread(s): '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 1 of 2: '_run_0'
08/20/2020 22:05:44 MainProcess _run_0 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 7557, side: 'a', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 2 of 2: '_run_1'
08/20/2020 22:05:44 MainProcess _run_1 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 7557, side: 'a', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Started all threads '_run': 2
08/20/2020 22:05:44 MainProcess _training_0 _base _load_generator DEBUG Loading generator
08/20/2020 22:05:44 MainProcess _training_0 _base _load_generator DEBUG input_size: 64, output_shapes: [(64, 64, 3)]
08/20/2020 22:05:44 MainProcess _training_0 _base coverage_ratio DEBUG Requested coverage_ratio: 0.875
08/20/2020 22:05:44 MainProcess _training_0 _base coverage_ratio DEBUG Final coverage_ratio: 0.875
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initializing TrainingDataGenerator: (model_input_size: 64, model_output_shapes: [(64, 64, 3)], coverage_ratio: 0.875, augment_color: True, no_flip: False, warp_to_landmarks: False, alignments: ['masks'], config: {'coverage': 87.5, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, '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})
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initialized TrainingDataGenerator
08/20/2020 22:05:44 MainProcess _training_0 training_data minibatch_ab DEBUG Queue batches: (image_count: 1728, batchsize: 12, side: 'b', do_shuffle: True, is_preview, False, is_timelapse: False)
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initializing ImageAugmentation: (batchsize: 12, is_display: False, input_size: 64, output_shapes: [(64, 64, 3)], coverage_ratio: 0.875, config: {'coverage': 87.5, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, '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})
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Output sizes: [64]
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initialized ImageAugmentation
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run', thread_count: 2)
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread(s): '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 1 of 2: '_run_0'
08/20/2020 22:05:44 MainProcess _run_0 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 1728, side: 'b', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 2 of 2: '_run_1'
08/20/2020 22:05:44 MainProcess _run_1 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 1728, side: 'b', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Started all threads '_run': 2
08/20/2020 22:05:44 MainProcess _training_0 _base _set_preview_feed DEBUG Setting preview feed: (side: 'a')
08/20/2020 22:05:44 MainProcess _training_0 _base _load_generator DEBUG Loading generator
08/20/2020 22:05:44 MainProcess _training_0 _base _load_generator DEBUG input_size: 64, output_shapes: [(64, 64, 3)]
08/20/2020 22:05:44 MainProcess _training_0 _base coverage_ratio DEBUG Requested coverage_ratio: 0.875
08/20/2020 22:05:44 MainProcess _training_0 _base coverage_ratio DEBUG Final coverage_ratio: 0.875
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initializing TrainingDataGenerator: (model_input_size: 64, model_output_shapes: [(64, 64, 3)], coverage_ratio: 0.875, augment_color: True, no_flip: False, warp_to_landmarks: False, alignments: ['masks'], config: {'coverage': 87.5, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, '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})
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initialized TrainingDataGenerator
08/20/2020 22:05:44 MainProcess _training_0 training_data minibatch_ab DEBUG Queue batches: (image_count: 7557, batchsize: 14, side: 'a', do_shuffle: True, is_preview, True, is_timelapse: False)
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initializing ImageAugmentation: (batchsize: 14, is_display: True, input_size: 64, output_shapes: [(64, 64, 3)], coverage_ratio: 0.875, config: {'coverage': 87.5, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, '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})
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Output sizes: [64]
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initialized ImageAugmentation
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run', thread_count: 2)
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread(s): '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 1 of 2: '_run_0'
08/20/2020 22:05:44 MainProcess _run_0 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 7557, side: 'a', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 2 of 2: '_run_1'
08/20/2020 22:05:44 MainProcess _run_1 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 7557, side: 'a', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Started all threads '_run': 2
08/20/2020 22:05:44 MainProcess _training_0 _base _set_preview_feed DEBUG Setting preview feed: (side: 'b')
08/20/2020 22:05:44 MainProcess _training_0 _base _load_generator DEBUG Loading generator
08/20/2020 22:05:44 MainProcess _training_0 _base _load_generator DEBUG input_size: 64, output_shapes: [(64, 64, 3)]
08/20/2020 22:05:44 MainProcess _training_0 _base coverage_ratio DEBUG Requested coverage_ratio: 0.875
08/20/2020 22:05:44 MainProcess _training_0 _base coverage_ratio DEBUG Final coverage_ratio: 0.875
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initializing TrainingDataGenerator: (model_input_size: 64, model_output_shapes: [(64, 64, 3)], coverage_ratio: 0.875, augment_color: True, no_flip: False, warp_to_landmarks: False, alignments: ['masks'], config: {'coverage': 87.5, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, '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})
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initialized TrainingDataGenerator
08/20/2020 22:05:44 MainProcess _training_0 training_data minibatch_ab DEBUG Queue batches: (image_count: 1728, batchsize: 14, side: 'b', do_shuffle: True, is_preview, True, is_timelapse: False)
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initializing ImageAugmentation: (batchsize: 14, is_display: True, input_size: 64, output_shapes: [(64, 64, 3)], coverage_ratio: 0.875, config: {'coverage': 87.5, 'mask_type': 'extended', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True, 'loss_function': 'mae', 'icnr_init': False, 'conv_aware_init': False, 'optimizer': 'adam', 'learning_rate': 5e-05, 'reflect_padding': False, 'allow_growth': False, 'mixed_precision': False, '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})
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Output sizes: [64]
08/20/2020 22:05:44 MainProcess _training_0 training_data __init__ DEBUG Initialized ImageAugmentation
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initializing BackgroundGenerator: (target: '_run', thread_count: 2)
08/20/2020 22:05:44 MainProcess _training_0 multithreading __init__ DEBUG Initialized BackgroundGenerator: '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread(s): '_run'
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 1 of 2: '_run_0'
08/20/2020 22:05:44 MainProcess _run_0 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 1728, side: 'b', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Starting thread 2 of 2: '_run_1'
08/20/2020 22:05:44 MainProcess _run_1 training_data _minibatch DEBUG Loading minibatch generator: (image_count: 1728, side: 'b', do_shuffle: True)
08/20/2020 22:05:44 MainProcess _training_0 multithreading start DEBUG Started all threads '_run': 2
08/20/2020 22:05:44 MainProcess _training_0 _base _set_preview_feed DEBUG Set preview feed. Batchsize: 14
08/20/2020 22:05:44 MainProcess _training_0 _base __init__ DEBUG Initialized _Feeder:
08/20/2020 22:05:44 MainProcess _training_0 _base _set_tensorboard DEBUG Enabling TensorBoard Logging
08/20/2020 22:05:44 MainProcess _training_0 _base _set_tensorboard DEBUG Setting up TensorBoard Logging
08/20/2020 22:05:45 MainProcess _run_1 training_data initialize DEBUG Initializing constants. training_size: 256
08/20/2020 22:05:45 MainProcess _run_0 training_data initialize DEBUG Initializing constants. training_size: 256
08/20/2020 22:05:45 MainProcess _run_0 training_data initialize DEBUG Initializing constants. training_size: 256
08/20/2020 22:05:45 MainProcess _run_0 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(16, 240, None), 'warp_mapx': '[[[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]]', 'warp_mapy': '[[[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [253. 253. 253. ... 253. 253. 253.]\n [254. 254. 254. ... 254. 254. 254.]\n [255. 255. 255. ... 255. 255. 255.]]\n\n [[ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n ...\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]]]'}
08/20/2020 22:05:45 MainProcess _run_1 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(16, 240, None), 'warp_mapx': '[[[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]]', 'warp_mapy': '[[[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [253. 253. 253. ... 253. 253. 253.]\n [254. 254. 254. ... 254. 254. 254.]\n [255. 255. 255. ... 255. 255. 255.]]\n\n [[ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n ...\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]]]'}
08/20/2020 22:05:45 MainProcess _run_0 training_data initialize DEBUG Initializing constants. training_size: 256
08/20/2020 22:05:45 MainProcess _run_0 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(16, 240, None), 'warp_mapx': '[[[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]]', 'warp_mapy': '[[[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [253. 253. 253. ... 253. 253. 253.]\n [254. 254. 254. ... 254. 254. 254.]\n [255. 255. 255. ... 255. 255. 255.]]\n\n [[ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n ...\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]]]'}
08/20/2020 22:05:45 MainProcess _run_0 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(16, 240, None), 'warp_mapx': '[[[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]\n\n [[ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]\n [ 16. 72. 128. 184. 240.]]]', 'warp_mapy': '[[[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]\n\n [[ 16. 16. 16. 16. 16.]\n [ 72. 72. 72. 72. 72.]\n [128. 128. 128. 128. 128.]\n [184. 184. 184. 184. 184.]\n [240. 240. 240. 240. 240.]]]', 'warp_pad': 80, 'warp_slices': slice(8, -8, None), 'warp_lm_edge_anchors': '[[[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]\n\n [[ 0 0]\n [ 0 255]\n [255 255]\n [255 0]\n [127 0]\n [127 255]\n [255 127]\n [ 0 127]]]', 'warp_lm_grids': '[[[ 0. 0. 0. ... 0. 0. 0.]\n [ 1. 1. 1. ... 1. 1. 1.]\n [ 2. 2. 2. ... 2. 2. 2.]\n ...\n [253. 253. 253. ... 253. 253. 253.]\n [254. 254. 254. ... 254. 254. 254.]\n [255. 255. 255. ... 255. 255. 255.]]\n\n [[ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n ...\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]\n [ 0. 1. 2. ... 253. 254. 255.]]]'}
08/20/2020 22:05:45 MainProcess _training_0 _base _set_tensorboard VERBOSE Enabled TensorBoard Logging
08/20/2020 22:05:45 MainProcess _training_0 _base coverage_ratio DEBUG Requested coverage_ratio: 0.875
08/20/2020 22:05:45 MainProcess _training_0 _base coverage_ratio DEBUG Final coverage_ratio: 0.875
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initializing _Samples: model: '<plugins.train.model.original.Model object at 0x0000027C593453D0>', coverage_ratio: 0.875)
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initialized _Samples
08/20/2020 22:05:45 MainProcess _training_0 _base coverage_ratio DEBUG Requested coverage_ratio: 0.875
08/20/2020 22:05:45 MainProcess _training_0 _base coverage_ratio DEBUG Final coverage_ratio: 0.875
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initializing _Timelapse: model: <plugins.train.model.original.Model object at 0x0000027C593453D0>, coverage_ratio: 0.875, image_count: 14, feeder: '<plugins.train.trainer._base._Feeder object at 0x0000027C579A6FD0>')
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initializing _Samples: model: '<plugins.train.model.original.Model object at 0x0000027C593453D0>', coverage_ratio: 0.875)
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initialized _Samples
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initialized _Timelapse
08/20/2020 22:05:45 MainProcess _training_0 _base __init__ DEBUG Initialized Trainer
08/20/2020 22:05:45 MainProcess _training_0 train _load_trainer DEBUG Loaded Trainer
08/20/2020 22:05:45 MainProcess _training_0 train _run_training_cycle DEBUG Running Training Cycle
08/20/2020 22:05:48 MainProcess _training_0 library _logger_callback INFO Analyzing Ops: 450 of 826 operations complete
08/20/2020 22:05:50 MainProcess _training_0 library _logger_callback INFO Analyzing Ops: 488 of 826 operations complete
08/20/2020 22:06:11 MainProcess _training_0 multithreading run DEBUG Error in thread (_training_0): No enough memory for the current schedule: required 2163167232, available 1825361152
08/20/2020 22:06:12 MainProcess MainThread train _monitor DEBUG Thread error detected
08/20/2020 22:06:12 MainProcess MainThread train _monitor DEBUG Closed Monitor
08/20/2020 22:06:12 MainProcess MainThread train _end_thread DEBUG Ending Training thread
08/20/2020 22:06:12 MainProcess MainThread train _end_thread CRITICAL Error caught! Exiting...
08/20/2020 22:06:12 MainProcess MainThread multithreading join DEBUG Joining Threads: '_training'
08/20/2020 22:06:12 MainProcess MainThread multithreading join DEBUG Joining Thread: '_training_0'
08/20/2020 22:06:12 MainProcess MainThread multithreading join ERROR Caught exception in thread: '_training_0'
Traceback (most recent call last):
File "C:\Users\karho\faceswap\lib\cli\launcher.py", line 156, in execute_script
process.process()
File "C:\Users\karho\faceswap\scripts\train.py", line 165, in process
self._end_thread(thread, err)
File "C:\Users\karho\faceswap\scripts\train.py", line 205, in _end_thread
thread.join()
File "C:\Users\karho\faceswap\lib\multithreading.py", line 121, in join
raise thread.err[1].with_traceback(thread.err[2])
File "C:\Users\karho\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "C:\Users\karho\faceswap\scripts\train.py", line 227, in _training
raise err
File "C:\Users\karho\faceswap\scripts\train.py", line 217, in _training
self._run_training_cycle(model, trainer)
File "C:\Users\karho\faceswap\scripts\train.py", line 298, in _run_training_cycle
trainer.train_one_step(viewer, timelapse)
File "C:\Users\karho\faceswap\plugins\train\trainer\_base.py", line 198, in train_one_step
loss = self._model.model.train_on_batch(model_inputs, y=model_targets)
File "C:\Users\karho\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "C:\Users\karho\MiniConda3\envs\faceswap\lib\site-packages\plaidml\keras\backend.py", line 189, in __call__
self._invoker.invoke()
File "C:\Users\karho\MiniConda3\envs\faceswap\lib\site-packages\plaidml\__init__.py", line 1475, in invoke
return Invocation(self._ctx, self)
File "C:\Users\karho\MiniConda3\envs\faceswap\lib\site-packages\plaidml\__init__.py", line 1484, in __init__
self._as_parameter_ = _lib().plaidml_schedule_invocation(ctx, invoker)
File "C:\Users\karho\MiniConda3\envs\faceswap\lib\site-packages\plaidml\__init__.py", line 777, in _check_err
self.raise_last_status()
File "C:\Users\karho\MiniConda3\envs\faceswap\lib\site-packages\plaidml\library.py", line 131, in raise_last_status
raise self.last_status()
plaidml.exceptions.Unknown: No enough memory for the current schedule: required 2163167232, available 1825361152
============ System Information ============
encoding: cp1252
git_branch: Not Found
git_commits: Not Found
gpu_cuda: No global version found. Check Conda packages for Conda Cuda
gpu_cudnn: No global version found. Check Conda packages for Conda cuDNN
gpu_devices: GPU_0: Advanced Micro Devices, Inc. - Bonaire (experimental)
gpu_devices_active: GPU_0
gpu_driver: ['3110.7']
gpu_vram: GPU_0: 2048MB
os_machine: AMD64
os_platform: Windows-10-10.0.19041-SP0
os_release: 10
py_command: C:\Users\karho\faceswap\faceswap.py train -A C:/TD/A/A -ala C:/TD/A/a_alignments.fsa -B C:/TD/B/B -alb C:/TD/B/b_alignments.fsa -m C:/TD/3 -t original -bs 12 -it 760000 -s 250 -ss 25000 -tia C:/TD/A/A -tib C:/TD/B/B -to C:/TD/4 -ps 50 -L INFO -gui
py_conda_version: conda 4.8.4
py_implementation: CPython
py_version: 3.8.5
py_virtual_env: True
sys_cores: 4
sys_processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
sys_ram: Total: 12248MB, Available: 8103MB, Used: 4144MB, Free: 8103MB
=============== Pip Packages ===============
absl-py==0.9.0
astunparse==1.6.3
cachetools==4.1.1
certifi==2020.6.20
cffi==1.14.2
chardet==3.0.4
cycler==0.10.0
enum34==1.1.10
fastcluster==1.1.26
ffmpy==0.2.3
gast==0.3.3
google-auth==1.20.1
google-auth-oauthlib==0.4.1
google-pasta==0.2.0
grpcio==1.31.0
h5py==2.10.0
idna==2.10
imageio @ file:///tmp/build/80754af9/imageio_1594161405741/work
imageio-ffmpeg @ file:///home/conda/feedstock_root/build_artifacts/imageio-ffmpeg_1589202782679/work
joblib @ file:///tmp/build/80754af9/joblib_1594236160679/work
Keras==2.2.4
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.2
kiwisolver==1.2.0
Markdown==3.2.2
matplotlib @ file:///C:/ci/matplotlib-base_1592837548929/work
mkl-fft==1.1.0
mkl-random==1.1.1
mkl-service==2.3.0
numpy @ file:///C:/ci/numpy_and_numpy_base_1596215850360/work
nvidia-ml-py3 @ git+https://github.com/deepfakes/nvidia-ml-py3.git@6fc29ac84b32bad877f078cb4a777c1548a00bf6
oauthlib==3.1.0
olefile==0.46
opencv-python==4.4.0.42
opt-einsum==3.3.0
pathlib==1.0.1
Pillow @ file:///C:/ci/pillow_1594298230227/work
plaidml==0.7.0
plaidml-keras==0.7.0
protobuf==3.13.0
psutil==5.7.0
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser==2.20
pyparsing==2.4.7
python-dateutil==2.8.1
pywin32==227
PyYAML==5.3.1
requests==2.24.0
requests-oauthlib==1.3.0
rsa==4.6
scikit-learn @ file:///C:/ci/scikit-learn_1592853510272/work
scipy==1.4.1
sip==4.19.13
six==1.15.0
tensorboard==2.2.2
tensorboard-plugin-wit==1.7.0
tensorflow==2.2.0
tensorflow-estimator==2.2.0
termcolor==1.1.0
threadpoolctl @ file:///tmp/tmp9twdgx9k/threadpoolctl-2.1.0-py3-none-any.whl
tornado==6.0.4
tqdm @ file:///tmp/build/80754af9/tqdm_1596810128862/work
urllib3==1.25.10
Werkzeug==1.0.1
wincertstore==0.2
wrapt==1.12.1
============== Conda Packages ==============
# packages in environment at C:\Users\karho\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
absl-py 0.9.0 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
blas 1.0 mkl
ca-certificates 2020.6.24 0
cachetools 4.1.1 pypi_0 pypi
certifi 2020.6.20 py38_0
cffi 1.14.2 pypi_0 pypi
chardet 3.0.4 pypi_0 pypi
cycler 0.10.0 py38_0
enum34 1.1.10 pypi_0 pypi
fastcluster 1.1.26 py38hbe40bda_1 conda-forge
ffmpeg 4.3.1 ha925a31_0 conda-forge
ffmpy 0.2.3 pypi_0 pypi
freetype 2.10.2 hd328e21_0
gast 0.3.3 pypi_0 pypi
git 2.23.0 h6bb4b03_0
google-auth 1.20.1 pypi_0 pypi
google-auth-oauthlib 0.4.1 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.31.0 pypi_0 pypi
h5py 2.10.0 pypi_0 pypi
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha925a31_3
idna 2.10 pypi_0 pypi
imageio 2.9.0 py_0
imageio-ffmpeg 0.4.2 py_0 conda-forge
intel-openmp 2020.1 216
joblib 0.16.0 py_0
jpeg 9b hb83a4c4_2
keras 2.2.4 pypi_0 pypi
keras-applications 1.0.8 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.2.0 py38h74a9793_0
libpng 1.6.37 h2a8f88b_0
libtiff 4.1.0 h56a325e_1
lz4-c 1.9.2 h62dcd97_1
markdown 3.2.2 pypi_0 pypi
matplotlib 3.2.2 0
matplotlib-base 3.2.2 py38h64f37c6_0
mkl 2020.1 216
mkl-service 2.3.0 py38hb782905_0
mkl_fft 1.1.0 py38h45dec08_0
mkl_random 1.1.1 py38h47e9c7a_0
numpy 1.19.1 py38h5510c5b_0
numpy-base 1.19.1 py38ha3acd2a_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
oauthlib 3.1.0 pypi_0 pypi
olefile 0.46 py_0
opencv-python 4.4.0.42 pypi_0 pypi
openssl 1.1.1g he774522_1
opt-einsum 3.3.0 pypi_0 pypi
pathlib 1.0.1 py_1
pillow 7.2.0 py38hcc1f983_0
pip 20.2.2 py38_0
plaidml 0.7.0 pypi_0 pypi
plaidml-keras 0.7.0 pypi_0 pypi
protobuf 3.13.0 pypi_0 pypi
psutil 5.7.0 py38he774522_0
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycparser 2.20 pypi_0 pypi
pyparsing 2.4.7 py_0
pyqt 5.9.2 py38ha925a31_4
python 3.8.5 he1778fa_0
python-dateutil 2.8.1 py_0
python_abi 3.8 1_cp38 conda-forge
pywin32 227 py38he774522_1
pyyaml 5.3.1 pypi_0 pypi
qt 5.9.7 vc14h73c81de_0
requests 2.24.0 pypi_0 pypi
requests-oauthlib 1.3.0 pypi_0 pypi
rsa 4.6 pypi_0 pypi
scikit-learn 0.23.1 py38h25d0782_0
scipy 1.4.1 pypi_0 pypi
setuptools 49.6.0 py38_0
sip 4.19.13 py38ha925a31_0
six 1.15.0 py_0
sqlite 3.32.3 h2a8f88b_0
tensorboard 2.2.2 pypi_0 pypi
tensorboard-plugin-wit 1.7.0 pypi_0 pypi
tensorflow 2.2.0 pypi_0 pypi
tensorflow-estimator 2.2.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
threadpoolctl 2.1.0 pyh5ca1d4c_0
tk 8.6.10 he774522_0
tornado 6.0.4 py38he774522_1
tqdm 4.48.2 py_0
urllib3 1.25.10 pypi_0 pypi
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_3
werkzeug 1.0.1 pypi_0 pypi
wheel 0.34.2 py38_0
wincertstore 0.2 py38_0
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h62dcd97_0
zlib 1.2.11 h62dcd97_4
zstd 1.4.5 h04227a9_0
================= Configs ==================
--------- .faceswap ---------
backend: amd
--------- convert.ini ---------
[color.color_transfer]
clip: True
preserve_paper: True
[color.manual_balance]
colorspace: HSV
balance_1: 0.0
balance_2: 0.0
balance_3: 0.0
contrast: 0.0
brightness: 0.0
[color.match_hist]
threshold: 99.0
[mask.box_blend]
type: gaussian
distance: 11.0
radius: 5.0
passes: 1
[mask.mask_blend]
type: normalized
kernel_size: 3
passes: 4
threshold: 4
erosion: 0.0
[scaling.sharpen]
method: unsharp_mask
amount: 150
radius: 0.3
threshold: 5.0
[writer.ffmpeg]
container: mp4
codec: libx264
crf: 23
preset: medium
tune: none
profile: auto
level: auto
skip_mux: False
[writer.gif]
fps: 25
loop: 0
palettesize: 256
subrectangles: False
[writer.opencv]
format: png
draw_transparent: False
jpg_quality: 75
png_compress_level: 3
[writer.pillow]
format: png
draw_transparent: False
optimize: False
gif_interlace: True
jpg_quality: 75
png_compress_level: 3
tif_compression: tiff_deflate
--------- extract.ini ---------
[global]
allow_growth: False
[align.fan]
batch-size: 12
[detect.cv2_dnn]
confidence: 50
[detect.mtcnn]
minsize: 20
threshold_1: 0.6
threshold_2: 0.7
threshold_3: 0.7
scalefactor: 0.709
batch-size: 8
[detect.s3fd]
confidence: 70
batch-size: 4
[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]
coverage: 87.5
mask_type: extended
mask_blur_kernel: 3
mask_threshold: 4
learn_mask: False
penalized_mask_loss: True
loss_function: mae
icnr_init: False
conv_aware_init: False
optimizer: adam
learning_rate: 5e-05
reflect_padding: False
allow_growth: False
mixed_precision: False
[model.dfl_h128]
lowmem: False
[model.dfl_sae]
input_size: 128
clipnorm: True
architecture: df
autoencoder_dims: 0
encoder_dims: 42
decoder_dims: 21
multiscale_decoder: False
[model.dlight]
features: best
details: good
output_size: 256
[model.original]
lowmem: False
[model.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
