Encountered CRITICAL An unexpected crash has occurred.
Posted: Fri Nov 08, 2019 10:17 pm
I have no idea how I can fix this mess
Code: Select all
11/08/2019 17:10:37 MainProcess _run_1 training_data initialize DEBUG Initializing constants. training_size: 256
11/08/2019 17:10:37 MainProcess _run_1 training_data initialize DEBUG Initialized constants: {'clahe_base_contrast': 2, 'tgt_slices': slice(40, 216, None), 'warp_mapx': '[[[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]\n\n [[ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]\n [ 40. 84. 128. 172. 216.]]]', 'warp_mapy': '[[[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]\n\n [[ 40. 40. 40. 40. 40.]\n [ 84. 84. 84. 84. 84.]\n [128. 128. 128. 128. 128.]\n [172. 172. 172. 172. 172.]\n [216. 216. 216. 216. 216.]]]', '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.]]]'}
11/08/2019 17:10:37 MainProcess training_0 _base largest_face_index DEBUG 0
11/08/2019 17:10:40 MainProcess training_0 library _logger_callback INFO Analyzing Ops: 270 of 520 operations complete
11/08/2019 17:10:52 MainProcess training_0 _base compile_sample DEBUG Compiling samples: (side: 'b', samples: 14)
11/08/2019 17:10:53 MainProcess training_0 _base show_sample DEBUG Showing sample
11/08/2019 17:10:53 MainProcess training_0 _base get_predictions DEBUG Getting Predictions
11/08/2019 17:11:00 MainProcess training_0 _base get_predictions DEBUG Returning predictions: {'a_a': (14, 64, 64, 3), 'b_a': (14, 64, 64, 3), 'a_b': (14, 64, 64, 3), 'b_b': (14, 64, 64, 3)}
11/08/2019 17:11:00 MainProcess training_0 _base to_full_frame DEBUG side: 'a', number of sample arrays: 2, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
11/08/2019 17:11:00 MainProcess training_0 _base frame_overlay DEBUG full_size: 256, target_size: 176, color: (0, 0, 255)
11/08/2019 17:11:00 MainProcess training_0 _base frame_overlay DEBUG Overlayed background. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 176, 176, 3))
11/08/2019 17:11:00 MainProcess training_0 _base overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'a', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'a' shape: (14, 128, 128, 3))
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG side: 'a', width: 128
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG height: 32, total_width: 384
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG texts: ['Original (A)', 'Original > Original', 'Original > Swap'], text_sizes: [(72, 9), (116, 9), (102, 9)], text_x: [28, 134, 269], text_y: 20
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG header_box.shape: (32, 384, 3)
11/08/2019 17:11:00 MainProcess training_0 _base to_full_frame DEBUG side: 'b', number of sample arrays: 2, prediction.shapes: [(14, 64, 64, 3), (14, 64, 64, 3)])
11/08/2019 17:11:00 MainProcess training_0 _base frame_overlay DEBUG full_size: 256, target_size: 176, color: (0, 0, 255)
11/08/2019 17:11:00 MainProcess training_0 _base frame_overlay DEBUG Overlayed background. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 176, 176, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 176, 176, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 64, 64, 3), target_size: 176, scale: 2.75)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 176, 176, 3))
11/08/2019 17:11:00 MainProcess training_0 _base overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base overlay_foreground DEBUG Overlayed foreground. Shape: (14, 256, 256, 3)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 128, 128, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 128, 128, 3))
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resizing sample: (side: 'b', sample.shape: (14, 256, 256, 3), target_size: 128, scale: 0.5)
11/08/2019 17:11:00 MainProcess training_0 _base resize_sample DEBUG Resized sample: (side: 'b' shape: (14, 128, 128, 3))
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG side: 'b', width: 128
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG height: 32, total_width: 384
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG texts: ['Swap (B)', 'Swap > Swap', 'Swap > Original'], text_sizes: [(59, 9), (87, 9), (102, 9)], text_x: [34, 148, 269], text_y: 20
11/08/2019 17:11:00 MainProcess training_0 _base get_headers DEBUG header_box.shape: (32, 384, 3)
11/08/2019 17:11:00 MainProcess training_0 _base duplicate_headers DEBUG side: a header.shape: (32, 384, 3)
11/08/2019 17:11:00 MainProcess training_0 _base duplicate_headers DEBUG side: b header.shape: (32, 384, 3)
11/08/2019 17:11:00 MainProcess training_0 _base stack_images DEBUG Stack images
11/08/2019 17:11:00 MainProcess training_0 _base get_transpose_axes DEBUG Even number of images to stack
11/08/2019 17:11:00 MainProcess training_0 _base stack_images DEBUG Stacked images
11/08/2019 17:11:00 MainProcess training_0 _base show_sample DEBUG Compiled sample
11/08/2019 17:11:00 MainProcess training_0 _base save_models DEBUG Backing up and saving models
11/08/2019 17:11:00 MainProcess training_0 _base get_save_averages DEBUG Getting save averages
11/08/2019 17:11:00 MainProcess training_0 _base get_save_averages DEBUG Average losses since last save: {'a': 0.11725123971700668, 'b': 0.1210833340883255}
11/08/2019 17:11:00 MainProcess training_0 _base check_loss_drop DEBUG Loss for 'a' has dropped
11/08/2019 17:11:00 MainProcess training_0 _base check_loss_drop DEBUG Loss for 'b' has dropped
11/08/2019 17:11:00 MainProcess training_0 _base should_backup DEBUG Lowest historical save iteration loss average: {'a': 0.12577251677817486, 'b': 0.13642760413758298}
11/08/2019 17:11:00 MainProcess training_0 _base should_backup DEBUG Updating lowest save iteration average for 'a': 0.11725123971700668
11/08/2019 17:11:00 MainProcess training_0 _base should_backup DEBUG Updating lowest save iteration average for 'b': 0.1210833340883255
11/08/2019 17:11:00 MainProcess training_0 _base should_backup DEBUG Backing up: True
11/08/2019 17:11:00 MainProcess training_0 _base save_models INFO Backing up models...
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_0 backup_restore backup_model VERBOSE Backing up: 'E:\John\Documents\Deepfake\Page ASMR model\original_decoder_A.h5' to 'E:\John\Documents\Deepfake\Page ASMR model\original_decoder_A.h5.bk'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_1 backup_restore backup_model VERBOSE Backing up: 'E:\John\Documents\Deepfake\Page ASMR model\original_decoder_B.h5' to 'E:\John\Documents\Deepfake\Page ASMR model\original_decoder_B.h5.bk'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_2 backup_restore backup_model VERBOSE Backing up: 'E:\John\Documents\Deepfake\Page ASMR model\original_encoder.h5' to 'E:\John\Documents\Deepfake\Page ASMR model\original_encoder.h5.bk'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 _base save DEBUG Saving State
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 backup_restore backup_model VERBOSE Backing up: 'E:\John\Documents\Deepfake\Page ASMR model\original_state.json' to 'E:\John\Documents\Deepfake\Page ASMR model\original_state.json.bk'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_0 _base save DEBUG Saving model: 'E:\John\Documents\Deepfake\Page ASMR model\original_decoder_A.h5'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_2 _base save DEBUG Saving model: 'E:\John\Documents\Deepfake\Page ASMR model\original_encoder.h5'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 serializer save DEBUG filename: E:\John\Documents\Deepfake\Page ASMR model\original_state.json, data type: <class 'dict'>
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 serializer _check_extension DEBUG Original filename: 'E:\John\Documents\Deepfake\Page ASMR model\original_state.json', final filename: 'E:\John\Documents\Deepfake\Page ASMR model\original_state.json'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_1 _base save DEBUG Saving model: 'E:\John\Documents\Deepfake\Page ASMR model\original_decoder_B.h5'
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 serializer marshal DEBUG data type: <class 'dict'>
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 serializer marshal DEBUG returned data type: <class 'bytes'>
11/08/2019 17:11:00 MainProcess ThreadPoolExecutor-16_3 _base save DEBUG Saved State
11/08/2019 17:11:02 MainProcess training_0 _base save_models INFO [Saved models] - Average since last save: face_loss_A: 0.11725, face_loss_B: 0.12108
11/08/2019 17:12:31 MainProcess _run_1 multithreading run DEBUG Error in thread (_run_1): tuple index out of range
11/08/2019 17:12:34 MainProcess training_0 multithreading check_and_raise_error DEBUG Thread error caught: [(<class 'IndexError'>, IndexError('tuple index out of range',), <traceback object at 0x000002B387EFE808>)]
11/08/2019 17:12:34 MainProcess training_0 multithreading run DEBUG Error in thread (training_0): tuple index out of range
11/08/2019 17:12:34 MainProcess _run_0 multithreading run DEBUG Error in thread (_run_0): tuple index out of range
11/08/2019 17:12:34 MainProcess MainThread train monitor DEBUG Thread error detected
11/08/2019 17:12:34 MainProcess MainThread train monitor DEBUG Closed Monitor
11/08/2019 17:12:34 MainProcess MainThread train end_thread DEBUG Ending Training thread
11/08/2019 17:12:34 MainProcess MainThread train end_thread CRITICAL Error caught! Exiting...
11/08/2019 17:12:34 MainProcess MainThread multithreading join DEBUG Joining Threads: 'training'
11/08/2019 17:12:34 MainProcess MainThread multithreading join DEBUG Joining Thread: 'training_0'
11/08/2019 17:12:34 MainProcess MainThread multithreading join ERROR Caught exception in thread: 'training_0'
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools initialize DEBUG PlaidML already initialized
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools get_supported_devices DEBUG [<plaidml._DeviceConfig object at 0x000002B362B3A9B0>]
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools get_all_devices DEBUG Experimental Devices: [<plaidml._DeviceConfig object at 0x000002B362B3AF98>]
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools get_all_devices DEBUG [<plaidml._DeviceConfig object at 0x000002B362B3AF98>, <plaidml._DeviceConfig object at 0x000002B362B3A9B0>]
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools __init__ DEBUG Initialized: PlaidMLStats
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools supported_indices DEBUG [1]
11/08/2019 17:12:34 MainProcess MainThread plaidml_tools supported_indices DEBUG [1]
Traceback (most recent call last):
File "E:\John\Documents\faceswap\lib\cli.py", line 128, in execute_script
process.process()
File "E:\John\Documents\faceswap\scripts\train.py", line 109, in process
self.end_thread(thread, err)
File "E:\John\Documents\faceswap\scripts\train.py", line 135, in end_thread
thread.join()
File "E:\John\Documents\faceswap\lib\multithreading.py", line 117, in join
raise thread.err[1].with_traceback(thread.err[2])
File "E:\John\Documents\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "E:\John\Documents\faceswap\scripts\train.py", line 160, in training
raise err
File "E:\John\Documents\faceswap\scripts\train.py", line 150, in training
self.run_training_cycle(model, trainer)
File "E:\John\Documents\faceswap\scripts\train.py", line 232, in run_training_cycle
trainer.train_one_step(viewer, timelapse)
File "E:\John\Documents\faceswap\plugins\train\trainer\_base.py", line 211, in train_one_step
raise err
File "E:\John\Documents\faceswap\plugins\train\trainer\_base.py", line 179, in train_one_step
loss[side] = batcher.train_one_batch(do_preview)
File "E:\John\Documents\faceswap\plugins\train\trainer\_base.py", line 273, in train_one_batch
batch = self.get_next(do_preview)
File "E:\John\Documents\faceswap\plugins\train\trainer\_base.py", line 294, in get_next
batch = next(self.feed)
File "E:\John\Documents\faceswap\lib\multithreading.py", line 152, in iterator
self.check_and_raise_error()
File "E:\John\Documents\faceswap\lib\multithreading.py", line 84, in check_and_raise_error
raise error[1].with_traceback(error[2])
File "E:\John\Documents\faceswap\lib\multithreading.py", line 37, in run
self._target(*self._args, **self._kwargs)
File "E:\John\Documents\faceswap\lib\multithreading.py", line 141, in _run
for item in self.generator(*self._gen_args, **self._gen_kwargs):
File "E:\John\Documents\faceswap\lib\training_data.py", line 200, in _minibatch
yield self._process_batch(img_paths, side)
File "E:\John\Documents\faceswap\lib\training_data.py", line 222, in _process_batch
batch = self._processing.color_adjust(batch)
File "E:\John\Documents\faceswap\lib\training_data.py", line 513, in color_adjust
batch = batch_convert_color(batch, "BGR2LAB")
File "E:\John\Documents\faceswap\lib\image.py", line 256, in batch_convert_color
batch = batch.reshape((original_shape[0] * original_shape[1], *original_shape[2:]))
IndexError: tuple index out of range
============ System Information ============
encoding: cp1252
git_branch: master
git_commits: ffd3829 Added allow_growth argument for preview
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. - Ellesmere (experimental), GPU_1: Advanced Micro Devices, Inc. - Ellesmere (supported)
gpu_devices_active: GPU_0, GPU_1
gpu_driver: ['2906.10', '2906.10']
gpu_vram: GPU_0: 8192MB, GPU_1: 8192MB
os_machine: AMD64
os_platform: Windows-10-10.0.18362-SP0
os_release: 10
py_command: E:\John\Documents\faceswap\faceswap.py train -A E:/John/Documents/Deepfake/replace faces -B E:/John/Documents/Deepfake/page faces -m E:/John/Documents/Deepfake/Page ASMR model -t original -bs 66 -it 1000000 -s 100 -ss 25000 -ps 50 -L INFO -gui
py_conda_version: conda 4.7.12
py_implementation: CPython
py_version: 3.6.9
py_virtual_env: True
sys_cores: 8
sys_processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
sys_ram: Total: 16349MB, Available: 8048MB, Used: 8300MB, Free: 8048MB
=============== Pip Packages ===============
absl-py==0.8.1
astor==0.8.0
certifi==2019.9.11
cffi==1.13.2
cloudpickle==1.2.2
cycler==0.10.0
cytoolz==0.10.0
dask==2.6.0
decorator==4.4.1
enum34==1.1.6
fastcluster==1.1.25
ffmpy==0.2.2
gast==0.3.2
grpcio==1.16.1
h5py==2.9.0
imageio==2.5.0
imageio-ffmpeg==0.3.0
joblib==0.14.0
Keras==2.2.4
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
kiwisolver==1.1.0
Markdown==3.1.1
matplotlib==2.2.2
mkl-fft==1.0.15
mkl-random==1.1.0
mkl-service==2.3.0
networkx==2.4
numpy==1.16.2
nvidia-ml-py3==7.352.1
olefile==0.46
opencv-python==4.1.1.26
pathlib==1.0.1
Pillow==6.1.0
plaidml==0.6.4
plaidml-keras==0.6.4
protobuf==3.9.2
psutil==5.6.3
pycparser==2.19
pyparsing==2.4.2
pyreadline==2.1
python-dateutil==2.8.1
pytz==2019.3
PyWavelets==1.1.1
pywin32==223
PyYAML==5.1.2
scikit-image==0.15.0
scikit-learn==0.21.3
scipy==1.3.1
six==1.12.0
tensorboard==1.14.0
tensorflow==1.14.0
tensorflow-estimator==1.14.0
termcolor==1.1.0
toolz==0.10.0
toposort==1.5
tornado==6.0.3
tqdm==4.36.1
Werkzeug==0.16.0
wincertstore==0.2
wrapt==1.11.2
============== Conda Packages ==============
# packages in environment at C:\Users\John\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
_tflow_select 2.3.0 mkl
absl-py 0.8.1 py36_0
astor 0.8.0 py36_0
blas 1.0 mkl
ca-certificates 2019.9.11 hecc5488_0 conda-forge
certifi 2019.9.11 py36_0 conda-forge
cffi 1.13.2 pypi_0 pypi
cloudpickle 1.2.2 py_0
cycler 0.10.0 py36h009560c_0
cytoolz 0.10.0 py36he774522_0
dask-core 2.6.0 py_0
decorator 4.4.1 py_0
enum34 1.1.6 pypi_0 pypi
fastcluster 1.1.25 py36he350917_1000 conda-forge
ffmpeg 4.2 h6538335_0 conda-forge
ffmpy 0.2.2 pypi_0 pypi
freetype 2.9.1 ha9979f8_1
gast 0.3.2 py_0
grpcio 1.16.1 py36h351948d_1
h5py 2.9.0 py36h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
imageio 2.5.0 py36_0
imageio-ffmpeg 0.3.0 py_0 conda-forge
intel-openmp 2019.4 245
joblib 0.14.0 py_0
jpeg 9b hb83a4c4_2
keras 2.2.4 pypi_0 pypi
keras-applications 1.0.8 py_0
keras-preprocessing 1.1.0 py_1
kiwisolver 1.1.0 py36ha925a31_0
libmklml 2019.0.5 0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.9.2 h7bd577a_0
libtiff 4.1.0 h56a325e_0
markdown 3.1.1 py36_0
matplotlib 2.2.2 py36had4c4a9_2
mkl 2019.4 245
mkl-service 2.3.0 py36hb782905_0
mkl_fft 1.0.15 py36h14836fe_0
mkl_random 1.1.0 py36h675688f_0
networkx 2.4 py_0
numpy 1.16.2 py36h19fb1c0_0
numpy-base 1.16.2 py36hc3f5095_0
nvidia-ml-py3 7.352.1 pypi_0 pypi
olefile 0.46 py36_0
opencv-python 4.1.1.26 pypi_0 pypi
openssl 1.1.1d hfa6e2cd_0 conda-forge
pathlib 1.0.1 py36_1
pillow 6.1.0 py36hdc69c19_0
pip 19.3.1 py36_0
plaidml 0.6.4 pypi_0 pypi
plaidml-keras 0.6.4 pypi_0 pypi
protobuf 3.9.2 py36h33f27b4_0
psutil 5.6.3 py36he774522_0
pycparser 2.19 pypi_0 pypi
pyparsing 2.4.2 py_0
pyqt 5.9.2 py36h6538335_2
pyreadline 2.1 py36_1
python 3.6.9 h5500b2f_0
python-dateutil 2.8.1 py_0
pytz 2019.3 py_0
pywavelets 1.1.1 py36he774522_0
pywin32 223 py36hfa6e2cd_1
pyyaml 5.1.2 pypi_0 pypi
qt 5.9.7 vc14h73c81de_0
scikit-image 0.15.0 py36ha925a31_0
scikit-learn 0.21.3 py36h6288b17_0
scipy 1.3.1 py36h29ff71c_0
setuptools 41.6.0 py36_0
sip 4.19.8 py36h6538335_0
six 1.12.0 py36_0
sqlite 3.30.1 he774522_0
tensorboard 1.14.0 py36he3c9ec2_0
tensorflow 1.14.0 mkl_py36hb88db5b_0
tensorflow-base 1.14.0 mkl_py36ha978198_0
tensorflow-estimator 1.14.0 py_0
termcolor 1.1.0 py36_1
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0
toposort 1.5 py_3 conda-forge
tornado 6.0.3 py36he774522_0
tqdm 4.36.1 py_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_0
werkzeug 0.16.0 py_0
wheel 0.33.6 py36_0
wincertstore 0.2 py36h7fe50ca_0
wrapt 1.11.2 py36he774522_0
xz 5.2.4 h2fa13f4_4
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0
=============== State File =================
{
"name": "original",
"sessions": {
"1": {
"timestamp": 1573212352.3809888,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
},
"2": {
"timestamp": 1573212545.8027182,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
},
"3": {
"timestamp": 1573245738.4151528,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 17,
"config": {
"learning_rate": 5e-05
}
},
"4": {
"timestamp": 1573247961.1000285,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
},
"5": {
"timestamp": 1573248331.4945996,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 64,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
},
"6": {
"timestamp": 1573249049.5537572,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 48,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
},
"7": {
"timestamp": 1573250829.66932,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 66,
"iterations": 48,
"config": {
"learning_rate": 5e-05
}
},
"8": {
"timestamp": 1573251016.1346729,
"no_logs": false,
"pingpong": false,
"loss_names": {
"a": [
"face_loss"
],
"b": [
"face_loss"
]
},
"batchsize": 66,
"iterations": 1,
"config": {
"learning_rate": 5e-05
}
}
},
"lowest_avg_loss": {
"a": 0.11725123971700668,
"b": 0.1210833340883255
},
"iterations": 71,
"inputs": {
"face_in:0": [
64,
64,
3
]
},
"training_size": 256,
"config": {
"coverage": 68.75,
"mask_type": null,
"mask_blur": false,
"icnr_init": false,
"conv_aware_init": false,
"subpixel_upscaling": false,
"reflect_padding": false,
"penalized_mask_loss": true,
"loss_function": "mae",
"learning_rate": 5e-05,
"lowmem": false
}
}
================= 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
radius: 3.0
passes: 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
[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: 50
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
font: default
font_size: 9
--------- train.ini ---------
[global]
coverage: 68.75
mask_type: none
mask_blur: False
icnr_init: False
conv_aware_init: False
subpixel_upscaling: False
reflect_padding: False
penalized_mask_loss: True
loss_function: mae
learning_rate: 5e-05
[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