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Critical Error on Training Initialisation "Failed to convert object of type <class 'plaidml.tile.Value'> to Tensor"

Posted: Tue Mar 24, 2020 5:54 am
by locomanos
Hello all,

I have encountered very strange issue when initialising training. After console displays line "opening device" it says:

"CRITICAL Error caught! Exiting...
ERROR Caught exception in thread: '_training_0'
ERROR Got Exception on main handler:"

I have tried using different training algorithms, and mask even no mask with low batch sizes... no change.

Please find below the log

Code: Select all

03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.dlight', title: 'details', datatype: '<class 'str'>', default: 'good', info: 'Defines detail fidelity. Lower setting can appear 'rugged' while 'good' might take onger time to train.\nAffects VRAM usage.', rounding: 'None', min_max: None, choices: ['fast', 'good'], gui_radio: True, fixed: True, group: None)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.dlight', title: 'output_size', datatype: '<class 'int'>', default: '256', info: 'Output image resolution (in pixels).\nBe aware that larger resolution will increase VRAM requirements.\nNB: Must be either 128, 256, or 384.', rounding: '128', min_max: (128, 384), choices: [], gui_radio: False, fixed: True, group: None)
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Added defaults: model.dlight
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Adding defaults: (filename: original_defaults.py, module_path: plugins.train.model, plugin_type: model
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Importing defaults module: plugins.train.model.original_defaults
03/24/2020 00:49:42 MainProcess     _training_0     config          add_section               DEBUG    Add section: (title: 'model.original', info: 'Original Faceswap Model.\nNB: Unless specifically stated, values changed here will only take effect when creating a new model.')
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.original', title: 'lowmem', datatype: '<class 'bool'>', default: 'False', info: 'Lower memory mode. Set to 'True' if having issues with VRAM useage.\nNB: Models with a changed lowmem mode are not compatible with each other.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Added defaults: model.original
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Adding defaults: (filename: realface_defaults.py, module_path: plugins.train.model, plugin_type: model
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Importing defaults module: plugins.train.model.realface_defaults
03/24/2020 00:49:42 MainProcess     _training_0     config          add_section               DEBUG    Add section: (title: 'model.realface', info: 'An extra detailed variant of Original model.\nIncorporates ideas from Bryanlyon and inspiration from the Villain model.\nRequires about 6GB-8GB of VRAM (batchsize 8-16).\n\nNB: Unless specifically stated, values changed here will only take effect when creating a new model.')
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.realface', title: 'input_size', datatype: '<class 'int'>', default: '64', info: 'Resolution (in pixels) of the input image to train on.\nBE AWARE Larger resolution will dramatically increase VRAM requirements.\nHigher resolutions may increase prediction accuracy, but does not effect the resulting output size.\nMust be between 64 and 128 and be divisible by 16.', rounding: '16', min_max: (64, 128), choices: [], gui_radio: False, fixed: True, group: size)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.realface', title: 'output_size', datatype: '<class 'int'>', default: '128', info: 'Output image resolution (in pixels).\nBe aware that larger resolution will increase VRAM requirements.\nNB: Must be between 64 and 256 and be divisible by 16.', rounding: '16', min_max: (64, 256), choices: [], gui_radio: False, fixed: True, group: size)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.realface', title: 'dense_nodes', datatype: '<class 'int'>', default: '1536', info: 'Number of nodes for decoder. Might affect your model's ability to learn in general.\nNote that: Lower values will affect the ability to predict details.', rounding: '64', min_max: (768, 2048), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.realface', title: 'complexity_encoder', datatype: '<class 'int'>', default: '128', info: 'Encoder Convolution Layer Complexity. sensible ranges: 128 to 150.', rounding: '4', min_max: (96, 160), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.realface', title: 'complexity_decoder', datatype: '<class 'int'>', default: '512', info: 'Decoder Complexity.', rounding: '4', min_max: (512, 544), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Added defaults: model.realface
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Adding defaults: (filename: unbalanced_defaults.py, module_path: plugins.train.model, plugin_type: model
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Importing defaults module: plugins.train.model.unbalanced_defaults
03/24/2020 00:49:42 MainProcess     _training_0     config          add_section               DEBUG    Add section: (title: 'model.unbalanced', info: 'An unbalanced model with adjustable input size options.\nThis is an unbalanced model so b>a swaps may not work well\n\nNB: Unless specifically stated, values changed here will only take effect when creating a new model.')
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'input_size', datatype: '<class 'int'>', default: '128', info: 'Resolution (in pixels) of the image to train on.\nBE AWARE Larger resolution will dramatically increaseVRAM requirements.\nMake sure your resolution is divisible by 64 (e.g. 64, 128, 256 etc.).\nNB: Your faceset must be at least 1.6x larger than your required input size.\n(e.g. 160 is the maximum input size for a 256x256 faceset).', rounding: '64', min_max: (64, 512), choices: [], gui_radio: False, fixed: True, group: size)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'lowmem', datatype: '<class 'bool'>', default: 'False', info: 'Lower memory mode. Set to 'True' if having issues with VRAM useage.\nNB: Models with a changed lowmem mode are not compatible with each other.\nNB: lowmem will override cutom nodes and complexity settings.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'clipnorm', datatype: '<class 'bool'>', default: 'True', info: 'Controls gradient clipping of the optimizer. Can prevent model corruption at the expense of VRAM.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'nodes', datatype: '<class 'int'>', default: '1024', info: 'Number of nodes for decoder. Don't change this unless you know what you are doing!', rounding: '64', min_max: (512, 4096), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'complexity_encoder', datatype: '<class 'int'>', default: '128', info: 'Encoder Convolution Layer Complexity. sensible ranges: 128 to 160.', rounding: '16', min_max: (64, 1024), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'complexity_decoder_a', datatype: '<class 'int'>', default: '384', info: 'Decoder A Complexity.', rounding: '16', min_max: (64, 1024), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.unbalanced', title: 'complexity_decoder_b', datatype: '<class 'int'>', default: '512', info: 'Decoder B Complexity.', rounding: '16', min_max: (64, 1024), choices: [], gui_radio: False, fixed: True, group: network)
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Added defaults: model.unbalanced
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Adding defaults: (filename: villain_defaults.py, module_path: plugins.train.model, plugin_type: model
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Importing defaults module: plugins.train.model.villain_defaults
03/24/2020 00:49:42 MainProcess     _training_0     config          add_section               DEBUG    Add section: (title: 'model.villain', info: 'A Higher resolution version of the Original Model by VillainGuy.\nExtremely VRAM heavy. Full model requires 9GB+ for batchsize 16\n\nNB: Unless specifically stated, values changed here will only take effect when creating a new model.')
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'model.villain', title: 'lowmem', datatype: '<class 'bool'>', default: 'False', info: 'Lower memory mode. Set to 'True' if having issues with VRAM useage.\nNB: Models with a changed lowmem mode are not compatible with each other.', rounding: 'None', min_max: None, choices: [], gui_radio: False, fixed: True, group: settings)
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Added defaults: model.villain
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Adding defaults: (filename: original_defaults.py, module_path: plugins.train.trainer, plugin_type: trainer
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Importing defaults module: plugins.train.trainer.original_defaults
03/24/2020 00:49:42 MainProcess     _training_0     config          add_section               DEBUG    Add section: (title: 'trainer.original', info: 'Original Trainer Options.\nWARNING: The defaults for augmentation will be fine for 99.9% of use cases. Only change them if you absolutely know what you are doing!')
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'preview_images', datatype: '<class 'int'>', default: '14', info: 'Number of sample faces to display for each side in the preview when training.', rounding: '2', min_max: (2, 16), choices: None, gui_radio: False, fixed: True, group: evaluation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'zoom_amount', datatype: '<class 'int'>', default: '5', info: 'Percentage amount to randomly zoom each training image in and out.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'rotation_range', datatype: '<class 'int'>', default: '10', info: 'Percentage amount to randomly rotate each training image.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'shift_range', datatype: '<class 'int'>', default: '5', info: 'Percentage amount to randomly shift each training image horizontally and vertically.', rounding: '1', min_max: (0, 25), choices: None, gui_radio: False, fixed: True, group: image augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'flip_chance', datatype: '<class 'int'>', default: '50', info: 'Percentage chance to randomly flip each training image horizontally.\nNB: This is ignored if the 'no-flip' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: image augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'color_lightness', datatype: '<class 'int'>', default: '30', info: 'Percentage amount to randomly alter the lightness of each training image.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: True, group: color augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'color_ab', datatype: '<class 'int'>', default: '8', info: 'Percentage amount to randomly alter the 'a' and 'b' colors of the L*a*b* color space of each training image.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (0, 50), choices: None, gui_radio: False, fixed: True, group: color augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'color_clahe_chance', datatype: '<class 'int'>', default: '50', info: 'Percentage chance to perform Contrast Limited Adaptive Histogram Equalization on each training image.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (0, 75), choices: None, gui_radio: False, fixed: False, group: color augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     config          add_item                  DEBUG    Add item: (section: 'trainer.original', title: 'color_clahe_max_size', datatype: '<class 'int'>', default: '4', info: 'The grid size dictates how much Contrast Limited Adaptive Histogram Equalization is performed on any training image selected for clahe. Contrast will be applied randomly with a gridsize of 0 up to the maximum. This value is a multiplier calculated from the training image size.\nNB: This is ignored if the 'no-augment-color' option is enabled', rounding: '1', min_max: (1, 8), choices: None, gui_radio: False, fixed: True, group: color augmentation)
03/24/2020 00:49:42 MainProcess     _training_0     _config         load_module               DEBUG    Added defaults: trainer.original
03/24/2020 00:49:42 MainProcess     _training_0     config          handle_config             DEBUG    Handling config
03/24/2020 00:49:42 MainProcess     _training_0     config          check_exists              DEBUG    Config file exists: 'C:\Users\Jim\faceswap\config\train.ini'
03/24/2020 00:49:42 MainProcess     _training_0     config          load_config               VERBOSE  Loading config: 'C:\Users\Jim\faceswap\config\train.ini'
03/24/2020 00:49:42 MainProcess     _training_0     config          validate_config           DEBUG    Validating config
03/24/2020 00:49:42 MainProcess     _training_0     config          check_config_change       DEBUG    Default config has not changed
03/24/2020 00:49:42 MainProcess     _training_0     config          check_config_choices      DEBUG    Checking config choices
03/24/2020 00:49:42 MainProcess     _training_0     config          check_config_choices      DEBUG    Checked config choices
03/24/2020 00:49:42 MainProcess     _training_0     config          validate_config           DEBUG    Validated config
03/24/2020 00:49:42 MainProcess     _training_0     config          handle_config             DEBUG    Handled config
03/24/2020 00:49:42 MainProcess     _training_0     config          __init__                  DEBUG    Initialized: Config
03/24/2020 00:49:42 MainProcess     _training_0     config          get                       DEBUG    Getting config item: (section: 'global', option: 'learning_rate')
03/24/2020 00:49:42 MainProcess     _training_0     config          get                       DEBUG    Returning item: (type: <class 'float'>, value: 5e-05)
03/24/2020 00:49:42 MainProcess     _training_0     config          changeable_items          DEBUG    Alterable for existing models: {'learning_rate': 5e-05}
03/24/2020 00:49:42 MainProcess     _training_0     _base           __init__                  DEBUG    Initializing State: (model_dir: 'C:\Users\Jim\Documents\DF\Models\Nat Cherie X S Johansson', model_name: 'lightweight', config_changeable_items: '{'learning_rate': 5e-05}', no_logs: False, pingpong: False, training_image_size: '256'
03/24/2020 00:49:42 MainProcess     _training_0     serializer      get_serializer            DEBUG    <lib.serializer._JSONSerializer object at 0x000001C7CC30F808>
03/24/2020 00:49:42 MainProcess     _training_0     _base           load                      DEBUG    Loading State
03/24/2020 00:49:42 MainProcess     _training_0     _base           load                      INFO     No existing state file found. Generating.
03/24/2020 00:49:42 MainProcess     _training_0     _base           new_session_id            DEBUG    1
03/24/2020 00:49:42 MainProcess     _training_0     _base           create_new_session        DEBUG    Creating new session. id: 1
03/24/2020 00:49:42 MainProcess     _training_0     _base           __init__                  DEBUG    Initialized State:
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       __init__                  DEBUG    Initializing NNBlocks: (use_subpixel: False, use_icnr_init: True, use_convaware_init: True, use_reflect_padding: False, first_run: True)
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       __init__                  INFO     Using Convolutional Aware Initialization. Model generation will take a few minutes...
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       __init__                  DEBUG    Initialized NNBlocks
03/24/2020 00:49:42 MainProcess     _training_0     _base           name                      DEBUG    model name: 'lightweight'
03/24/2020 00:49:42 MainProcess     _training_0     _base           load_state_info           DEBUG    Loading Input Shape from State file
03/24/2020 00:49:42 MainProcess     _training_0     _base           load_state_info           DEBUG    No input shapes saved. Using model config
03/24/2020 00:49:42 MainProcess     _training_0     _base           calculate_coverage_ratio  DEBUG    Requested coverage_ratio: 0.75
03/24/2020 00:49:42 MainProcess     _training_0     _base           calculate_coverage_ratio  DEBUG    Final coverage_ratio: 0.75
03/24/2020 00:49:42 MainProcess     _training_0     _base           __init__                  DEBUG    training_opts: {'alignments': {'a': 'C:\\Users\\Jim\\Documents\\DF\\Nat Cherie\\Nat Cherie Faceset\\Natalie_Cherie_Alignments.fsa', 'b': 'C:\\Users\\Jim\\Documents\\DF\\S Johansson\\S Johanson Faceset\\Scarlett_Johansson_Alignments.fsa'}, 'preview_scaling': 0.5, 'warp_to_landmarks': False, 'augment_color': True, 'no_flip': False, 'pingpong': False, 'snapshot_interval': 25000, 'training_size': 256, 'no_logs': False, 'coverage_ratio': 0.75, 'mask_type': 'vgg-obstructed', 'mask_blur_kernel': 3, 'mask_threshold': 4, 'learn_mask': False, 'penalized_mask_loss': True}
03/24/2020 00:49:42 MainProcess     _training_0     _base           multiple_models_in_folder DEBUG    model_files: [], retval: False
03/24/2020 00:49:42 MainProcess     _training_0     original        add_networks              DEBUG    Adding networks
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       upscale                   DEBUG    inp: input_1 Placeholder FLOAT32(<tile.Value SymbolicDim UINT64()>, 8, 8, 256), filters: 512, kernel_size: 3, use_instance_norm: False, kwargs: {})
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       get_name                  DEBUG    Generating block name: upscale_(<tile.Value SymbolicDim UINT64()>, 8, 8, 256)_0
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       set_default_initializer   DEBUG    Set default kernel_initializer to: <lib.model.initializers.ConvolutionAware object at 0x000001C7CC4A7C08>
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       switch_kernel_initializer DEBUG    Switched kernel_initializer from <lib.model.initializers.ConvolutionAware object at 0x000001C7CC4A7C08> to <lib.model.initializers.ICNR object at 0x000001C7CC255D48>
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       conv2d                    DEBUG    inp: input_1 Placeholder FLOAT32(<tile.Value SymbolicDim UINT64()>, 8, 8, 256), filters: 2048, kernel_size: 3, strides: (1, 1), padding: same, kwargs: {'name': 'upscale_(<tile.Value SymbolicDim UINT64()>, 8, 8, 256)_0_conv2d', 'kernel_initializer': <lib.model.initializers.ICNR object at 0x000001C7CC255D48>})
03/24/2020 00:49:42 MainProcess     _training_0     nn_blocks       set_default_initializer   DEBUG    Using model specified initializer: <lib.model.initializers.ICNR object at 0x000001C7CC255D48>
03/24/2020 00:49:42 MainProcess     _training_0     initializers    __call__                  INFO     Calculating Convolution Aware Initializer for shape: [3, 3, 256, 512]
03/24/2020 00:49:43 MainProcess     _training_0     library         _logger_callback          INFO     Opening device "opencl_amd_gfx900.0"
03/24/2020 00:49:43 MainProcess     _training_0     multithreading  run                       DEBUG    Error in thread (_training_0): Failed to convert object of type <class 'plaidml.tile.Value'> to Tensor. Contents: upscale_(<tile.Value SymbolicDim UINT64()>, 8, 8, 256)_0_conv2d/conv_aware Tensor FLOAT32(3, 3, 256, 512). Consider casting elements to a supported type.
03/24/2020 00:49:43 MainProcess     MainThread      train           _monitor                  DEBUG    Thread error detected
03/24/2020 00:49:43 MainProcess     MainThread      train           _monitor                  DEBUG    Closed Monitor
03/24/2020 00:49:43 MainProcess     MainThread      train           _end_thread               DEBUG    Ending Training thread
03/24/2020 00:49:43 MainProcess     MainThread      train           _end_thread               CRITICAL Error caught! Exiting...
03/24/2020 00:49:43 MainProcess     MainThread      multithreading  join                      DEBUG    Joining Threads: '_training'
03/24/2020 00:49:43 MainProcess     MainThread      multithreading  join                      DEBUG    Joining Thread: '_training_0'
03/24/2020 00:49:43 MainProcess     MainThread      multithreading  join                      ERROR    Caught exception in thread: '_training_0'
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   initialize                DEBUG    PlaidML already initialized
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   get_supported_devices     DEBUG    [<plaidml._DeviceConfig object at 0x000001C7CC5D3408>]
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   get_all_devices           DEBUG    Experimental Devices: [<plaidml._DeviceConfig object at 0x000001C7CC5002C8>]
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   get_all_devices           DEBUG    [<plaidml._DeviceConfig object at 0x000001C7CC5002C8>, <plaidml._DeviceConfig object at 0x000001C7CC5D3408>]
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   __init__                  DEBUG    Initialized: PlaidMLStats
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   supported_indices         DEBUG    [1]
03/24/2020 00:49:43 MainProcess     MainThread      plaidml_tools   supported_indices         DEBUG    [1]
Traceback (most recent call last):
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\tensor_util.py", line 541, in make_tensor_proto
    str_values = [compat.as_bytes(x) for x in proto_values]
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\tensor_util.py", line 541, in <listcomp>
    str_values = [compat.as_bytes(x) for x in proto_values]
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\util\compat.py", line 71, in as_bytes
    (bytes_or_text,))
TypeError: Expected binary or unicode string, got <tile.Value upscale_(<tile.Value SymbolicDim UINT64()>, 8, 8, 256)_0_conv2d/conv_aware Tensor FLOAT32(3, 3, 256, 512)>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\Jim\faceswap\lib\cli.py", line 128, in execute_script
    process.process()
  File "C:\Users\Jim\faceswap\scripts\train.py", line 159, in process
    self._end_thread(thread, err)
  File "C:\Users\Jim\faceswap\scripts\train.py", line 199, in _end_thread
    thread.join()
  File "C:\Users\Jim\faceswap\lib\multithreading.py", line 121, in join
    raise thread.err[1].with_traceback(thread.err[2])
  File "C:\Users\Jim\faceswap\lib\multithreading.py", line 37, in run
    self._target(*self._args, **self._kwargs)
  File "C:\Users\Jim\faceswap\scripts\train.py", line 224, in _training
    raise err
  File "C:\Users\Jim\faceswap\scripts\train.py", line 212, in _training
    model = self._load_model()
  File "C:\Users\Jim\faceswap\scripts\train.py", line 253, in _load_model
    predict=False)
  File "C:\Users\Jim\faceswap\plugins\train\model\lightweight.py", line 20, in __init__
    super().__init__(*args, **kwargs)
  File "C:\Users\Jim\faceswap\plugins\train\model\original.py", line 25, in __init__
    super().__init__(*args, **kwargs)
  File "C:\Users\Jim\faceswap\plugins\train\model\_base.py", line 126, in __init__
    self.build()
  File "C:\Users\Jim\faceswap\plugins\train\model\_base.py", line 244, in build
    self.add_networks()
  File "C:\Users\Jim\faceswap\plugins\train\model\original.py", line 31, in add_networks
    self.add_network("decoder", "a", self.decoder(), is_output=True)
  File "C:\Users\Jim\faceswap\plugins\train\model\lightweight.py", line 40, in decoder
    var_x = self.blocks.upscale(var_x, 512)
  File "C:\Users\Jim\faceswap\lib\model\nn_blocks.py", line 137, in upscale
    **kwargs)
  File "C:\Users\Jim\faceswap\lib\model\nn_blocks.py", line 90, in conv2d
    **kwargs)(inp)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 431, in __call__
    self.build(unpack_singleton(input_shapes))
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\keras\layers\convolutional.py", line 141, in build
    constraint=self.kernel_constraint)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\keras\engine\base_layer.py", line 249, in add_weight
    weight = K.variable(initializer(shape),
  File "C:\Users\Jim\faceswap\lib\model\initializers.py", line 67, in __call__
    var_x = tf.transpose(var_x, perm=[2, 0, 1, 3])
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\ops\array_ops.py", line 1859, in transpose
    ret = transpose_fn(a, perm, name=name)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\ops\gen_array_ops.py", line 11452, in transpose
    "Transpose", x=x, perm=perm, name=name)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 531, in _apply_op_helper
    raise err
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 528, in _apply_op_helper
    preferred_dtype=default_dtype)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1297, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\constant_op.py", line 286, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\constant_op.py", line 227, in constant
    allow_broadcast=True)
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\constant_op.py", line 265, in _constant_impl
    allow_broadcast=allow_broadcast))
  File "C:\Users\Jim\MiniConda3\envs\faceswap\lib\site-packages\tensorflow_core\python\framework\tensor_util.py", line 545, in make_tensor_proto
    "supported type." % (type(values), values))
TypeError: Failed to convert object of type <class 'plaidml.tile.Value'> to Tensor. Contents: upscale_(<tile.Value SymbolicDim UINT64()>, 8, 8, 256)_0_conv2d/conv_aware Tensor FLOAT32(3, 3, 256, 512). Consider casting elements to a supported type.

============ System Information ============
encoding:            cp1252
git_branch:          master
git_commits:         924d537 Core updates (#982)
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. - gfx900 (experimental), GPU_1: Advanced Micro Devices, Inc. - gfx900 (supported)
gpu_devices_active:  GPU_0, GPU_1
gpu_driver:          ['3004.8 (PAL,HSAIL)', '3004.8 (PAL,HSAIL)']
gpu_vram:            GPU_0: 8176MB, GPU_1: 8176MB
os_machine:          AMD64
os_platform:         Windows-10-10.0.18362-SP0
os_release:          10
py_command:          C:\Users\Jim\faceswap\faceswap.py train -A C:/Users/Jim/Documents/DF/A/A Faceset -ala C:/Users/Jim/Documents/DF/A/A Faceset/A_Alignments.fsa -B C:/Users/Jim/Documents/DF/B/B Faceset -alb C:/Users/Jim/Documents/DF/B/B Faceset/B_Alignments.fsa -m C:/Users/Jim/Documents/DF/Models/AB -t lightweight -bs 10 -it 1000000 -s 100 -ss 25000 -ps 50 -L INFO -gui
py_conda_version:    conda 4.8.3
py_implementation:   CPython
py_version:          3.7.6
py_virtual_env:      True
sys_cores:           8
sys_processor:       Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
sys_ram:             Total: 16344MB, Available: 3214MB, Used: 13130MB, Free: 3214MB

=============== Pip Packages ===============
absl-py==0.9.0
asn1crypto==1.3.0
astor==0.8.0
blinker==1.4
cachetools==3.1.1
certifi==2019.11.28
cffi==1.14.0
chardet==3.0.4
click==7.1.1
cloudpickle==1.3.0
cryptography==2.8
cycler==0.10.0
cytoolz==0.10.1
dask==2.12.0
decorator==4.4.2
enum34==1.1.10
fastcluster==1.1.26
ffmpy==0.2.2
gast==0.2.2
google-auth==1.11.2
google-auth-oauthlib==0.4.1
google-pasta==0.1.8
grpcio==1.27.2
h5py==2.9.0
idna==2.9
imageio==2.6.1
imageio-ffmpeg==0.4.1
joblib==0.14.1
Keras==2.2.4
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
kiwisolver==1.1.0
Markdown==3.1.1
matplotlib==3.1.3
mkl-fft==1.0.15
mkl-random==1.1.0
mkl-service==2.3.0
networkx==2.4
numpy==1.17.4
nvidia-ml-py3==7.352.1
oauthlib==3.1.0
olefile==0.46
opencv-python==4.1.2.30
opt-einsum==3.1.0
pathlib==1.0.1
Pillow==6.2.1
plaidml==0.6.4
plaidml-keras==0.6.4
protobuf==3.11.4
psutil==5.7.0
pyasn1==0.4.8
pyasn1-modules==0.2.7
pycparser==2.20
PyJWT==1.7.1
pyOpenSSL==19.1.0
pyparsing==2.4.6
pyreadline==2.1
PySocks==1.7.1
python-dateutil==2.8.1
pytz==2019.3
PyWavelets==1.1.1
pywin32==227
PyYAML==5.3
requests==2.23.0
requests-oauthlib==1.3.0
rsa==4.0
scikit-image==0.16.2
scikit-learn==0.22.1
scipy==1.4.1
six==1.14.0
tensorboard==2.1.0
tensorflow==1.15.0
tensorflow-estimator==1.15.1
termcolor==1.1.0
toolz==0.10.0
toposort==1.5
tornado==6.0.4
tqdm==4.43.0
urllib3==1.25.8
Werkzeug==0.16.1
win-inet-pton==1.1.0
wincertstore==0.2
wrapt==1.12.1

============== Conda Packages ==============
# packages in environment at C:\Users\Jim\MiniConda3\envs\faceswap:
#
# Name                    Version                   Build  Channel
_tflow_select             2.2.0                     eigen  
absl-py                   0.9.0                    py37_0  
asn1crypto                1.3.0                    py37_0  
astor                     0.8.0                    py37_0  
blas                      1.0                         mkl  
blinker                   1.4                      py37_0  
ca-certificates           2020.1.1                      0  
cachetools                3.1.1                      py_0  
certifi                   2019.11.28               py37_0  
cffi                      1.14.0           py37h7a1dbc1_0  
chardet                   3.0.4                 py37_1003  
click                     7.1.1                      py_0  
cloudpickle               1.3.0                      py_0  
cryptography              2.8              py37h7a1dbc1_0  
cycler                    0.10.0                   py37_0  
cytoolz                   0.10.1           py37he774522_0  
dask-core                 2.12.0                     py_0  
decorator                 4.4.2                      py_0  
enum34                    1.1.10                   pypi_0    pypi
fastcluster               1.1.26           py37he350917_0    conda-forge
ffmpeg                    4.2                  h6538335_0    conda-forge
ffmpy                     0.2.2                    pypi_0    pypi
freetype                  2.9.1                ha9979f8_1  
gast                      0.2.2                    py37_0  
git                       2.23.0               h6bb4b03_0  
google-auth               1.11.2                     py_0  
google-auth-oauthlib      0.4.1                      py_2  
google-pasta              0.1.8                      py_0  
grpcio                    1.27.2           py37h351948d_0  
h5py                      2.9.0            py37h5e291fa_0  
hdf5                      1.10.4               h7ebc959_0  
icc_rt                    2019.0.0             h0cc432a_1  
icu                       58.2                 ha66f8fd_1  
idna                      2.9                        py_1  
imageio                   2.6.1                    py37_0  
imageio-ffmpeg            0.4.1                      py_0    conda-forge
intel-openmp              2020.0                      166  
joblib                    0.14.1                     py_0  
jpeg                      9b                   hb83a4c4_2  
keras                     2.2.4                         0  
keras-applications        1.0.8                      py_0  
keras-base                2.2.4                    py37_0  
keras-preprocessing       1.1.0                      py_1  
kiwisolver                1.1.0            py37ha925a31_0  
libpng                    1.6.37               h2a8f88b_0  
libprotobuf               3.11.4               h7bd577a_0  
libtiff                   4.1.0                h56a325e_0  
markdown                  3.1.1                    py37_0  
matplotlib                3.1.1            py37hc8f65d3_0  
matplotlib-base           3.1.3            py37h64f37c6_0  
mkl                       2020.0                      166  
mkl-service               2.3.0            py37hb782905_0  
mkl_fft                   1.0.15           py37h14836fe_0  
mkl_random                1.1.0            py37h675688f_0  
networkx                  2.4                        py_0  
numpy                     1.17.4           py37h4320e6b_0  
numpy-base                1.17.4           py37hc3f5095_0  
nvidia-ml-py3             7.352.1                  pypi_0    pypi
oauthlib                  3.1.0                      py_0  
olefile                   0.46                     py37_0  
opencv-python             4.1.2.30                 pypi_0    pypi
openssl                   1.1.1e               he774522_0  
opt_einsum                3.1.0                      py_0  
pathlib                   1.0.1                    py37_1  
pillow                    6.2.1            py37hdc69c19_0  
pip                       20.0.2                   py37_1  
plaidml                   0.6.4                    pypi_0    pypi
plaidml-keras             0.6.4                    pypi_0    pypi
protobuf                  3.11.4           py37h33f27b4_0  
psutil                    5.7.0            py37he774522_0  
pyasn1                    0.4.8                      py_0  
pyasn1-modules            0.2.7                      py_0  
pycparser                 2.20                       py_0  
pyjwt                     1.7.1                    py37_0  
pyopenssl                 19.1.0                   py37_0  
pyparsing                 2.4.6                      py_0  
pyqt                      5.9.2            py37h6538335_2  
pyreadline                2.1                      py37_1  
pysocks                   1.7.1                    py37_0  
python                    3.7.6                h60c2a47_2  
python-dateutil           2.8.1                      py_0  
python_abi                3.7                     1_cp37m    conda-forge
pytz                      2019.3                     py_0  
pywavelets                1.1.1            py37he774522_0  
pywin32                   227              py37he774522_1  
pyyaml                    5.3              py37he774522_0  
qt                        5.9.7            vc14h73c81de_0  
requests                  2.23.0                   py37_0  
requests-oauthlib         1.3.0                      py_0  
rsa                       4.0                        py_0  
scikit-image              0.16.2           py37h47e9c7a_0  
scikit-learn              0.22.1           py37h6288b17_0  
scipy                     1.4.1            py37h9439919_0  
setuptools                46.0.0                   py37_0  
sip                       4.19.8           py37h6538335_0  
six                       1.14.0                   py37_0  
sqlite                    3.31.1               he774522_0  
tensorboard               2.1.0                     py3_0  
tensorflow                1.15.0          eigen_py37h9f89a44_0  
tensorflow-base           1.15.0          eigen_py37h07d2309_0  
tensorflow-estimator      1.15.1             pyh2649769_0  
termcolor                 1.1.0                    py37_1  
tk                        8.6.8                hfa6e2cd_0  
toolz                     0.10.0                     py_0  
toposort                  1.5                        py_3    conda-forge
tornado                   6.0.4            py37he774522_1  
tqdm                      4.43.0                     py_0  
urllib3                   1.25.8                   py37_0  
vc                        14.1                 h0510ff6_4  
vs2015_runtime            14.16.27012          hf0eaf9b_1  
werkzeug                  0.16.1                     py_0  
wheel                     0.34.2                   py37_0  
win_inet_pton             1.1.0                    py37_0  
wincertstore              0.2                      py37_0  
wrapt                     1.12.1           py37he774522_1  
xz                        5.2.4                h2fa13f4_4  
yaml                      0.1.7                hc54c509_2  
zlib                      1.2.11               h62dcd97_3  
zstd                      1.3.7                h508b16e_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

[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:                 75.0
mask_type:                vgg-obstructed
mask_blur_kernel:         3
mask_threshold:           4
learn_mask:               False
icnr_init:                True
conv_aware_init:          True
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
Thank you for your help in advance

Re: Critical Error on Training Initialisation "Failed to convert object of type <class 'plaidml.tile.Value'> to Tensor"

Posted: Tue Mar 24, 2020 10:31 am
by torzdf