SAED does not work

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  • #3191
    aron
    Participant

    Training with SEAD does not work.
    I did all the steps up to step 6.
    The training with xseg also worked, but SAED does not work.
    I don’t know what I’m doing wrong. Please help me.

    Best regards
    aron

    Here are my parameters:

    Running trainer.

    [new] No saved models found. Enter a name of a new model : head20
    head20

    Model first run.

    Choose one or several GPU idxs (separated by comma).

    [CPU] : CPU
    [0] : NVIDIA GeForce GTX 950M

    [0] Which GPU indexes to choose? : 0
    0

    [0] Autobackup every N hour ( 0..24 ?:help ) :
    0
    [n] Write preview history ( y/n ?:help ) :
    n
    [0] Target iteration : 10
    10
    [n] Flip SRC faces randomly ( y/n ?:help ) :
    n
    [y] Flip DST faces randomly ( y/n ?:help ) :
    y
    [4] Batch_size ( ?:help ) : 2
    2
    [128] Resolution ( 64-640 ?:help ) : 64
    64
    [f] Face type ( h/mf/f/wf/head ?:help ) :
    f
    [liae-ud] AE architecture ( ?:help ) :
    liae-ud
    [256] AutoEncoder dimensions ( 32-1024 ?:help ) :
    256
    [64] Encoder dimensions ( 16-256 ?:help ) :
    64
    [64] Decoder dimensions ( 16-256 ?:help ) :
    64
    [22] Decoder mask dimensions ( 16-256 ?:help ) :
    22
    [n] Eyes and mouth priority ( y/n ?:help ) :
    n
    [n] Uniform yaw distribution of samples ( y/n ?:help ) :
    n
    [n] Blur out mask ( y/n ?:help ) :
    n
    [y] Place models and optimizer on GPU ( y/n ?:help ) :
    y
    [y] Use AdaBelief optimizer? ( y/n ?:help ) :
    y
    [n] Use learning rate dropout ( n/y/cpu ?:help ) :
    n
    [y] Enable random warp of samples ( y/n ?:help ) :
    y
    [0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) :
    0.0
    [0.0] GAN power ( 0.0 .. 5.0 ?:help ) :
    0.0
    [0.0] Face style power ( 0.0..100.0 ?:help ) :
    0.0
    [0.0] Background style power ( 0.0..100.0 ?:help ) :
    0.0
    [none] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) :
    none
    [n] Enable gradient clipping ( y/n ?:help ) :
    n
    [n] Enable pretraining mode ( y/n ?:help ) :
    n
    Initializing models: 100%|###############################################################| 5/5 [00:04<00:00, 1.23it/s]
    Loading samples: 100%|###############################################################| 461/461 [00:40<00:00, 11.50it/s]
    Loading samples: 100%|###############################################################| 399/399 [00:38<00:00, 10.44it/s]
    ================== Model Summary ===================
    == ==
    == Model name: head20_SAEHD ==
    == ==
    == Current iteration: 0 ==
    == ==
    ==—————- Model Options —————–==
    == ==
    == resolution: 64 ==
    == face_type: f ==
    == models_opt_on_gpu: True ==
    == archi: liae-ud ==
    == ae_dims: 256 ==
    == e_dims: 64 ==
    == d_dims: 64 ==
    == d_mask_dims: 22 ==
    == masked_training: True ==
    == eyes_mouth_prio: False ==
    == uniform_yaw: False ==
    == blur_out_mask: False ==
    == adabelief: True ==
    == lr_dropout: n ==
    == random_warp: True ==
    == random_hsv_power: 0.0 ==
    == true_face_power: 0.0 ==
    == face_style_power: 0.0 ==
    == bg_style_power: 0.0 ==
    == ct_mode: none ==
    == clipgrad: False ==
    == pretrain: False ==
    == autobackup_hour: 0 ==
    == write_preview_history: False ==
    == target_iter: 10 ==
    == random_src_flip: False ==
    == random_dst_flip: True ==
    == batch_size: 2 ==
    == gan_power: 0.0 ==
    == gan_patch_size: 8 ==
    == gan_dims: 16 ==
    == ==
    ==—————— Running On ——————==
    == ==
    == Device index: 0 ==
    == Name: NVIDIA GeForce GTX 950M ==
    == VRAM: 1.35GB ==
    == ==
    ====================================================
    Starting. Target iteration: 10. Press “Enter” to stop training and save model.

    Trying to do the first iteration. If an error occurs, reduce the model parameters.

    !!!
    Windows 10 users IMPORTANT notice. You should set this setting in order to work correctly.

    View post on imgur.com


    !!!
    You are training the model from scratch. It is strongly recommended to use a pretrained model to speed up the training and improve the quality.

    #3225
    deepfakery
    Keymaster

    Are you getting an OOM error?
    Your card doesn’t have much VRAM so you need to disable some things. Try either or both of these:

    [y] Place models and optimizer on GPU ( y/n ?:help ) :
    n
    [y] Use AdaBelief optimizer? ( y/n ?:help ) :
    n

    Might also try increasing your page file size.

    #3564
    aron
    Participant

    Thanks for your answer.
    I implemented the first two suggestions, but still got an error message.
    When I try train Quick 96, the error message also appears.
    What do you mean with the last point:”Might also try increasing your page file size.”
    Can you explain that in a bit more detail?
    Best regards
    aron

    Running trainer.

    [new] No saved models found. Enter a name of a new model :
    new

    Model first run.

    Choose one or several GPU idxs (separated by comma).

    [CPU] : CPU
    [0] : NVIDIA GeForce GTX 950M

    [0] Which GPU indexes to choose? : 0
    0

    [0] Autobackup every N hour ( 0..24 ?:help ) :
    0
    [n] Write preview history ( y/n ?:help ) :
    n
    [10] Target iteration :
    10
    [n] Flip SRC faces randomly ( y/n ?:help ) :
    n
    [y] Flip DST faces randomly ( y/n ?:help ) :
    y
    [2] Batch_size ( ?:help ) :
    2
    [64] Resolution ( 64-640 ?:help ) :
    64
    [f] Face type ( h/mf/f/wf/head ?:help ) :
    f
    [liae-ud] AE architecture ( ?:help ) :
    liae-ud
    [256] AutoEncoder dimensions ( 32-1024 ?:help ) :
    256
    [64] Encoder dimensions ( 16-256 ?:help ) :
    64
    [64] Decoder dimensions ( 16-256 ?:help ) :
    64
    [22] Decoder mask dimensions ( 16-256 ?:help ) :
    22
    [n] Eyes and mouth priority ( y/n ?:help ) :
    n
    [n] Uniform yaw distribution of samples ( y/n ?:help ) :
    n
    [n] Blur out mask ( y/n ?:help ) :
    n
    [n] Place models and optimizer on GPU ( y/n ?:help ) :
    n
    [n] Use AdaBelief optimizer? ( y/n ?:help ) :
    n
    [n] Use learning rate dropout ( n/y/cpu ?:help ) :
    n
    [y] Enable random warp of samples ( y/n ?:help ) :
    y
    [0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) :
    0.0
    [0.0] GAN power ( 0.0 .. 5.0 ?:help ) :
    0.0
    [0.0] Face style power ( 0.0..100.0 ?:help ) :
    0.0
    [0.0] Background style power ( 0.0..100.0 ?:help ) :
    0.0
    [none] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) :
    none
    [n] Enable gradient clipping ( y/n ?:help ) :
    n
    [n] Enable pretraining mode ( y/n ?:help ) :
    n
    Initializing models: 100%|###############################################################| 5/5 [00:02<00:00, 1.72it/s]
    Loading samples: 100%|###############################################################| 461/461 [00:41<00:00, 11.06it/s]
    Loading samples: 100%|###############################################################| 399/399 [00:38<00:00, 10.41it/s]
    Process Process-13:
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 80, in get_eyes_mouth_mask
    return np.clip(mask, 0, 1)
    File “<__array_function__ internals>”, line 6, in clip
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\fromnumeric.py”, line 2097, in clip
    return _wrapfunc(a, ‘clip’, a_min, a_max, out=out, **kwargs)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\fromnumeric.py”, line 58, in _wrapfunc
    return bound(*args, **kwds)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\_methods.py”, line 141, in _clip
    um.clip, a, min, max, out=out, casting=casting, **kwargs)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\_methods.py”, line 94, in _clip_dep_invoke_with_casting
    return ufunc(*args, out=out, **kwargs)
    MemoryError: Unable to allocate 16.0 MiB for an array with shape (2048, 2048, 1) and data type float32

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “multiprocessing\process.py”, line 258, in _bootstrap
    File “multiprocessing\process.py”, line 93, in run
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\joblib\SubprocessGenerator.py”, line 54, in process_func
    gen_data = next (self.generator_func)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 136, in batch_func
    raise Exception (“Exception occured in sample %s. Error: %s” % (sample.filename, traceback.format_exc() ) )
    Exception: Exception occured in sample C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\workspace\data_dst\aligned\00081_0.jpg. Error: Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 80, in get_eyes_mouth_mask
    return np.clip(mask, 0, 1)
    File “<__array_function__ internals>”, line 6, in clip
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\fromnumeric.py”, line 2097, in clip
    return _wrapfunc(a, ‘clip’, a_min, a_max, out=out, **kwargs)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\fromnumeric.py”, line 58, in _wrapfunc
    return bound(*args, **kwds)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\_methods.py”, line 141, in _clip
    um.clip, a, min, max, out=out, casting=casting, **kwargs)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\numpy\core\_methods.py”, line 94, in _clip_dep_invoke_with_casting
    return ufunc(*args, out=out, **kwargs)
    MemoryError: Unable to allocate 16.0 MiB for an array with shape (2048, 2048, 1) and data type float32

    Drücken Sie eine beliebige Taste . . .

    #3563
    aron
    Participant

    Thanks for your answer.
    I implemented the first two suggestions, but still got an error message.
    What do you mean by the last point: “Might also try increasing your page file size.”
    Can you explain that in a bit more detail?
    Best regards
    aron

    Running trainer.

    [new] No saved models found. Enter a name of a new model :
    new

    Model first run.

    Choose one or several GPU idxs (separated by comma).

    [CPU] : CPU
    [0] : NVIDIA GeForce GTX 950M

    [0] Which GPU indexes to choose? : 0
    0

    [0] Autobackup every N hour ( 0..24 ?:help ) :
    0
    [n] Write preview history ( y/n ?:help ) :
    n
    [0] Target iteration : 10
    10
    [n] Flip SRC faces randomly ( y/n ?:help ) :
    n
    [y] Flip DST faces randomly ( y/n ?:help ) :
    y
    [4] Batch_size ( ?:help ) : 2
    2
    [128] Resolution ( 64-640 ?:help ) : 64
    64
    [f] Face type ( h/mf/f/wf/head ?:help ) :
    f
    [liae-ud] AE architecture ( ?:help ) :
    liae-ud
    [256] AutoEncoder dimensions ( 32-1024 ?:help ) :
    256
    [64] Encoder dimensions ( 16-256 ?:help ) :
    64
    [64] Decoder dimensions ( 16-256 ?:help ) :
    64
    [22] Decoder mask dimensions ( 16-256 ?:help ) :
    22
    [n] Eyes and mouth priority ( y/n ?:help ) :
    n
    [n] Uniform yaw distribution of samples ( y/n ?:help ) :
    n
    [n] Blur out mask ( y/n ?:help ) :
    n
    [y] Place models and optimizer on GPU ( y/n ?:help ) : n
    [y] Use AdaBelief optimizer? ( y/n ?:help ) : n
    [n] Use learning rate dropout ( n/y/cpu ?:help ) :
    n
    [y] Enable random warp of samples ( y/n ?:help ) :
    y
    [0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) :
    0.0
    [0.0] GAN power ( 0.0 .. 5.0 ?:help ) :
    0.0
    [0.0] Face style power ( 0.0..100.0 ?:help ) :
    0.0
    [0.0] Background style power ( 0.0..100.0 ?:help ) :
    0.0
    [none] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) :
    none
    [n] Enable gradient clipping ( y/n ?:help ) :
    n
    [n] Enable pretraining mode ( y/n ?:help ) :
    n
    Initializing models: 100%|###############################################################| 5/5 [00:03<00:00, 1.64it/s]
    Loading samples: 100%|###############################################################| 461/461 [00:38<00:00, 11.91it/s]
    Loading samples: 100%|###############################################################| 399/399 [00:35<00:00, 11.09it/s]
    Process Process-13:
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 78, in get_eyes_mouth_mask
    mouth_mask = LandmarksProcessor.get_image_mouth_mask (sample_bgr.shape, sample_landmarks)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\facelib\LandmarksProcessor.py”, line 447, in get_image_mouth_mask
    hull_mask = cv2.dilate(hull_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(dilate,dilate)), iterations = 1 )
    cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp:55: error: (-4:Insufficient memory) Failed to allocate 16777216 bytes in function ‘cv::OutOfMemoryError’

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “multiprocessing\process.py”, line 258, in _bootstrap
    File “multiprocessing\process.py”, line 93, in run
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\joblib\SubprocessGenerator.py”, line 54, in process_func
    gen_data = next (self.generator_func)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 136, in batch_func
    raise Exception (“Exception occured in sample %s. Error: %s” % (sample.filename, traceback.format_exc() ) )
    Exception: Exception occured in sample C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\workspace\data_dst\aligned\00229_0.jpg. Error: Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 78, in get_eyes_mouth_mask
    mouth_mask = LandmarksProcessor.get_image_mouth_mask (sample_bgr.shape, sample_landmarks)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\facelib\LandmarksProcessor.py”, line 447, in get_image_mouth_mask
    hull_mask = cv2.dilate(hull_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(dilate,dilate)), iterations = 1 )
    cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp:55: error: (-4:Insufficient memory) Failed to allocate 16777216 bytes in function ‘cv::OutOfMemoryError’

    ================== Model Summary ===================
    == ==
    == Model name: new_SAEHD ==
    == ==
    == Current iteration: 0 ==
    == ==
    ==—————- Model Options —————–==
    == ==
    == resolution: 64 ==
    == face_type: f ==
    == models_opt_on_gpu: False ==
    == archi: liae-ud ==
    == ae_dims: 256 ==
    == e_dims: 64 ==
    == d_dims: 64 ==
    == d_mask_dims: 22 ==
    == masked_training: True ==
    == eyes_mouth_prio: False ==
    == uniform_yaw: False ==
    == blur_out_mask: False ==
    == adabelief: False ==
    == lr_dropout: n ==
    == random_warp: True ==
    == random_hsv_power: 0.0 ==
    == true_face_power: 0.0 ==
    == face_style_power: 0.0 ==
    == bg_style_power: 0.0 ==
    == ct_mode: none ==
    == clipgrad: False ==
    == pretrain: False ==
    == autobackup_hour: 0 ==
    == write_preview_history: False ==
    == target_iter: 10 ==
    == random_src_flip: False ==
    == random_dst_flip: True ==
    == batch_size: 2 ==
    == gan_power: 0.0 ==
    == gan_patch_size: 8 ==
    == gan_dims: 16 ==
    == ==
    ==—————— Running On ——————==
    == ==
    == Device index: 0 ==
    == Name: NVIDIA GeForce GTX 950M ==
    == VRAM: 1.35GB ==
    == ==
    ====================================================
    Starting. Target iteration: 10. Press “Enter” to stop training and save model.

    Trying to do the first iteration. If an error occurs, reduce the model parameters.

    !!!
    Windows 10 users IMPORTANT notice. You should set this setting in order to work correctly.

    View post on imgur.com


    !!!
    You are training the model from scratch. It is strongly recommended to use a pretrained model to speed up the training and improve the quality.

    Error: Could not allocate ndarray
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1334, in _do_call
    return fn(*args)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1319, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1407, in _call_tf_sessionrun
    run_metadata)
    tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py”, line 159, in trainerThread
    model_save()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py”, line 68, in model_save
    model.save()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\models\ModelBase.py”, line 393, in save
    self.onSave()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py”, line 759, in onSave
    model.save_weights ( self.get_strpath_storage_for_file(filename) )
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Saveable.py”, line 51, in save_weights
    w_val = nn.tf_sess.run (w).copy()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 929, in run
    run_metadata_ptr)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1152, in _run
    feed_dict_tensor, options, run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1328, in _do_run
    run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1348, in _do_call
    raise type(e)(node_def, op, message)
    tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray

    Running trainer.

    [new] No saved models found. Enter a name of a new model :
    new

    Model first run.

    Choose one or several GPU idxs (separated by comma).

    [CPU] : CPU
    [0] : NVIDIA GeForce GTX 950M

    [0] Which GPU indexes to choose? : 0
    0

    [0] Autobackup every N hour ( 0..24 ?:help ) :
    0
    [n] Write preview history ( y/n ?:help ) :
    n
    [0] Target iteration : 10
    10
    [n] Flip SRC faces randomly ( y/n ?:help ) :
    n
    [y] Flip DST faces randomly ( y/n ?:help ) :
    y
    [4] Batch_size ( ?:help ) : 2
    2
    [128] Resolution ( 64-640 ?:help ) : 64
    64
    [f] Face type ( h/mf/f/wf/head ?:help ) :
    f
    [liae-ud] AE architecture ( ?:help ) :
    liae-ud
    [256] AutoEncoder dimensions ( 32-1024 ?:help ) :
    256
    [64] Encoder dimensions ( 16-256 ?:help ) :
    64
    [64] Decoder dimensions ( 16-256 ?:help ) :
    64
    [22] Decoder mask dimensions ( 16-256 ?:help ) :
    22
    [n] Eyes and mouth priority ( y/n ?:help ) :
    n
    [n] Uniform yaw distribution of samples ( y/n ?:help ) :
    n
    [n] Blur out mask ( y/n ?:help ) :
    n
    [y] Place models and optimizer on GPU ( y/n ?:help ) : n
    [y] Use AdaBelief optimizer? ( y/n ?:help ) : n
    [n] Use learning rate dropout ( n/y/cpu ?:help ) :
    n
    [y] Enable random warp of samples ( y/n ?:help ) :
    y
    [0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) :
    0.0
    [0.0] GAN power ( 0.0 .. 5.0 ?:help ) :
    0.0
    [0.0] Face style power ( 0.0..100.0 ?:help ) :
    0.0
    [0.0] Background style power ( 0.0..100.0 ?:help ) :
    0.0
    [none] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) :
    none
    [n] Enable gradient clipping ( y/n ?:help ) :
    n
    [n] Enable pretraining mode ( y/n ?:help ) :
    n
    Initializing models: 100%|###############################################################| 5/5 [00:03<00:00, 1.64it/s]
    Loading samples: 100%|###############################################################| 461/461 [00:38<00:00, 11.91it/s]
    Loading samples: 100%|###############################################################| 399/399 [00:35<00:00, 11.09it/s]
    Process Process-13:
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 78, in get_eyes_mouth_mask
    mouth_mask = LandmarksProcessor.get_image_mouth_mask (sample_bgr.shape, sample_landmarks)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\facelib\LandmarksProcessor.py”, line 447, in get_image_mouth_mask
    hull_mask = cv2.dilate(hull_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(dilate,dilate)), iterations = 1 )
    cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp:55: error: (-4:Insufficient memory) Failed to allocate 16777216 bytes in function ‘cv::OutOfMemoryError’

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “multiprocessing\process.py”, line 258, in _bootstrap
    File “multiprocessing\process.py”, line 93, in run
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\joblib\SubprocessGenerator.py”, line 54, in process_func
    gen_data = next (self.generator_func)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 136, in batch_func
    raise Exception (“Exception occured in sample %s. Error: %s” % (sample.filename, traceback.format_exc() ) )
    Exception: Exception occured in sample C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\workspace\data_dst\aligned\00229_0.jpg. Error: Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 78, in get_eyes_mouth_mask
    mouth_mask = LandmarksProcessor.get_image_mouth_mask (sample_bgr.shape, sample_landmarks)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\facelib\LandmarksProcessor.py”, line 447, in get_image_mouth_mask
    hull_mask = cv2.dilate(hull_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(dilate,dilate)), iterations = 1 )
    cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp:55: error: (-4:Insufficient memory) Failed to allocate 16777216 bytes in function ‘cv::OutOfMemoryError’

    ================== Model Summary ===================
    == ==
    == Model name: new_SAEHD ==
    == ==
    == Current iteration: 0 ==
    == ==
    ==—————- Model Options —————–==
    == ==
    == resolution: 64 ==
    == face_type: f ==
    == models_opt_on_gpu: False ==
    == archi: liae-ud ==
    == ae_dims: 256 ==
    == e_dims: 64 ==
    == d_dims: 64 ==
    == d_mask_dims: 22 ==
    == masked_training: True ==
    == eyes_mouth_prio: False ==
    == uniform_yaw: False ==
    == blur_out_mask: False ==
    == adabelief: False ==
    == lr_dropout: n ==
    == random_warp: True ==
    == random_hsv_power: 0.0 ==
    == true_face_power: 0.0 ==
    == face_style_power: 0.0 ==
    == bg_style_power: 0.0 ==
    == ct_mode: none ==
    == clipgrad: False ==
    == pretrain: False ==
    == autobackup_hour: 0 ==
    == write_preview_history: False ==
    == target_iter: 10 ==
    == random_src_flip: False ==
    == random_dst_flip: True ==
    == batch_size: 2 ==
    == gan_power: 0.0 ==
    == gan_patch_size: 8 ==
    == gan_dims: 16 ==
    == ==
    ==—————— Running On ——————==
    == ==
    == Device index: 0 ==
    == Name: NVIDIA GeForce GTX 950M ==
    == VRAM: 1.35GB ==
    == ==
    ====================================================
    Starting. Target iteration: 10. Press “Enter” to stop training and save model.

    Trying to do the first iteration. If an error occurs, reduce the model parameters.

    !!!
    Windows 10 users IMPORTANT notice. You should set this setting in order to work correctly.

    View post on imgur.com


    !!!
    You are training the model from scratch. It is strongly recommended to use a pretrained model to speed up the training and improve the quality.

    Error: Could not allocate ndarray
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1334, in _do_call
    return fn(*args)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1319, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1407, in _call_tf_sessionrun
    run_metadata)
    tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py”, line 159, in trainerThread
    model_save()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py”, line 68, in model_save
    model.save()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\models\ModelBase.py”, line 393, in save
    self.onSave()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py”, line 759, in onSave
    model.save_weights ( self.get_strpath_storage_for_file(filename) )
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Saveable.py”, line 51, in save_weights
    w_val = nn.tf_sess.run (w).copy()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 929, in run
    run_metadata_ptr)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1152, in _run
    feed_dict_tensor, options, run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1328, in _do_run
    run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1348, in _do_call
    raise type(e)(node_def, op, message)
    tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray

    Running trainer.

    [new] No saved models found. Enter a name of a new model :
    new

    Model first run.

    Choose one or several GPU idxs (separated by comma).

    [CPU] : CPU
    [0] : NVIDIA GeForce GTX 950M

    [0] Which GPU indexes to choose? : 0
    0

    [0] Autobackup every N hour ( 0..24 ?:help ) :
    0
    [n] Write preview history ( y/n ?:help ) :
    n
    [0] Target iteration : 10
    10
    [n] Flip SRC faces randomly ( y/n ?:help ) :
    n
    [y] Flip DST faces randomly ( y/n ?:help ) :
    y
    [4] Batch_size ( ?:help ) : 2
    2
    [128] Resolution ( 64-640 ?:help ) : 64
    64
    [f] Face type ( h/mf/f/wf/head ?:help ) :
    f
    [liae-ud] AE architecture ( ?:help ) :
    liae-ud
    [256] AutoEncoder dimensions ( 32-1024 ?:help ) :
    256
    [64] Encoder dimensions ( 16-256 ?:help ) :
    64
    [64] Decoder dimensions ( 16-256 ?:help ) :
    64
    [22] Decoder mask dimensions ( 16-256 ?:help ) :
    22
    [n] Eyes and mouth priority ( y/n ?:help ) :
    n
    [n] Uniform yaw distribution of samples ( y/n ?:help ) :
    n
    [n] Blur out mask ( y/n ?:help ) :
    n
    [y] Place models and optimizer on GPU ( y/n ?:help ) : n
    [y] Use AdaBelief optimizer? ( y/n ?:help ) : n
    [n] Use learning rate dropout ( n/y/cpu ?:help ) :
    n
    [y] Enable random warp of samples ( y/n ?:help ) :
    y
    [0.0] Random hue/saturation/light intensity ( 0.0 .. 0.3 ?:help ) :
    0.0
    [0.0] GAN power ( 0.0 .. 5.0 ?:help ) :
    0.0
    [0.0] Face style power ( 0.0..100.0 ?:help ) :
    0.0
    [0.0] Background style power ( 0.0..100.0 ?:help ) :
    0.0
    [none] Color transfer for src faceset ( none/rct/lct/mkl/idt/sot ?:help ) :
    none
    [n] Enable gradient clipping ( y/n ?:help ) :
    n
    [n] Enable pretraining mode ( y/n ?:help ) :
    n
    Initializing models: 100%|###############################################################| 5/5 [00:03<00:00, 1.64it/s]
    Loading samples: 100%|###############################################################| 461/461 [00:38<00:00, 11.91it/s]
    Loading samples: 100%|###############################################################| 399/399 [00:35<00:00, 11.09it/s]
    Process Process-13:
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 78, in get_eyes_mouth_mask
    mouth_mask = LandmarksProcessor.get_image_mouth_mask (sample_bgr.shape, sample_landmarks)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\facelib\LandmarksProcessor.py”, line 447, in get_image_mouth_mask
    hull_mask = cv2.dilate(hull_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(dilate,dilate)), iterations = 1 )
    cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp:55: error: (-4:Insufficient memory) Failed to allocate 16777216 bytes in function ‘cv::OutOfMemoryError’

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “multiprocessing\process.py”, line 258, in _bootstrap
    File “multiprocessing\process.py”, line 93, in run
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\joblib\SubprocessGenerator.py”, line 54, in process_func
    gen_data = next (self.generator_func)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 136, in batch_func
    raise Exception (“Exception occured in sample %s. Error: %s” % (sample.filename, traceback.format_exc() ) )
    Exception: Exception occured in sample C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\workspace\data_dst\aligned\00229_0.jpg. Error: Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py”, line 134, in batch_func
    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 145, in process
    img = get_eyes_mouth_mask()*mask
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\samplelib\SampleProcessor.py”, line 78, in get_eyes_mouth_mask
    mouth_mask = LandmarksProcessor.get_image_mouth_mask (sample_bgr.shape, sample_landmarks)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\facelib\LandmarksProcessor.py”, line 447, in get_image_mouth_mask
    hull_mask = cv2.dilate(hull_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(dilate,dilate)), iterations = 1 )
    cv2.error: OpenCV(4.1.0) C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp:55: error: (-4:Insufficient memory) Failed to allocate 16777216 bytes in function ‘cv::OutOfMemoryError’

    ================== Model Summary ===================
    == ==
    == Model name: new_SAEHD ==
    == ==
    == Current iteration: 0 ==
    == ==
    ==—————- Model Options —————–==
    == ==
    == resolution: 64 ==
    == face_type: f ==
    == models_opt_on_gpu: False ==
    == archi: liae-ud ==
    == ae_dims: 256 ==
    == e_dims: 64 ==
    == d_dims: 64 ==
    == d_mask_dims: 22 ==
    == masked_training: True ==
    == eyes_mouth_prio: False ==
    == uniform_yaw: False ==
    == blur_out_mask: False ==
    == adabelief: False ==
    == lr_dropout: n ==
    == random_warp: True ==
    == random_hsv_power: 0.0 ==
    == true_face_power: 0.0 ==
    == face_style_power: 0.0 ==
    == bg_style_power: 0.0 ==
    == ct_mode: none ==
    == clipgrad: False ==
    == pretrain: False ==
    == autobackup_hour: 0 ==
    == write_preview_history: False ==
    == target_iter: 10 ==
    == random_src_flip: False ==
    == random_dst_flip: True ==
    == batch_size: 2 ==
    == gan_power: 0.0 ==
    == gan_patch_size: 8 ==
    == gan_dims: 16 ==
    == ==
    ==—————— Running On ——————==
    == ==
    == Device index: 0 ==
    == Name: NVIDIA GeForce GTX 950M ==
    == VRAM: 1.35GB ==
    == ==
    ====================================================
    Starting. Target iteration: 10. Press “Enter” to stop training and save model.

    Trying to do the first iteration. If an error occurs, reduce the model parameters.

    !!!
    Windows 10 users IMPORTANT notice. You should set this setting in order to work correctly.

    View post on imgur.com


    !!!
    You are training the model from scratch. It is strongly recommended to use a pretrained model to speed up the training and improve the quality.

    Error: Could not allocate ndarray
    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1334, in _do_call
    return fn(*args)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1319, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1407, in _call_tf_sessionrun
    run_metadata)
    tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py”, line 159, in trainerThread
    model_save()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\mainscripts\Trainer.py”, line 68, in model_save
    model.save()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\models\ModelBase.py”, line 393, in save
    self.onSave()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\models\Model_SAEHD\Model.py”, line 759, in onSave
    model.save_weights ( self.get_strpath_storage_for_file(filename) )
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\DeepFaceLab\core\leras\layers\Saveable.py”, line 51, in save_weights
    w_val = nn.tf_sess.run (w).copy()
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 929, in run
    run_metadata_ptr)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1152, in _run
    feed_dict_tensor, options, run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1328, in _do_run
    run_metadata)
    File “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti\_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py”, line 1348, in _do_call
    raise type(e)(node_def, op, message)
    tensorflow.python.framework.errors_impl.InternalError: Could not allocate ndarray

    #3567
    deepfakery
    Keymaster

    Hey Aron,
    I just posted a guide which might help. It has some recommendations for DeepFaceLab system optimization.

    DeepFaceLab 2.0 Guide

    You card doesn’t have much VRAM available which is going to be the major problem, even with really low settings.
    Check out this table: https://www.deepfakevfx.com/guides/model-training-settings/
    You might need to disable the -U and/or -D model options. Try these settings: LIAE/112/256/64/64/22

    Also were you able to run Quick96 at all?

    #3569
    deepfakery
    Keymaster

    I just noticed something else in the path to your DFL:
    “C:\Users\aronk\Desktop\11.20. DeepFaceLab_NVIDIA_up_to_RTX2080Ti”
    Try having it in your C: directory not the desktop, and remove the space in the folder name

    #3570
    aron
    Participant

    Hey deepfakery,

    thanks for your reply.
    I’ll deal with the guide. I moved DFL to C.
    Regarding your question: “Also were you able to run Quick96 at all?” Unfortunately, no.

    Best regards
    aron

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