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### Running command:
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###   chmod a+r DeepPINCS -R && D:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD build --keep-empty-dirs --no-resave-data DeepPINCS
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* checking for file 'DeepPINCS/DESCRIPTION' ... OK
* preparing 'DeepPINCS':
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ... ERROR
--- re-building 'DeepPINCS.Rmd' using rmarkdown
2022-03-17 16:43:14.319416: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2022-03-17 16:43:14.321060: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-03-17 16:44:05.845469: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2022-03-17 16:44:05.846510: W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303)
2022-03-17 16:44:05.850466: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: riesling1
2022-03-17 16:44:05.851070: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: riesling1
2022-03-17 16:44:05.852595: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-03-17 16:44:05.883461: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x60786b40 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2022-03-17 16:44:05.883779: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
Epoch 1/20

1/6 [====>.........................] - ETA: 0s - loss: 0.7027 - accuracy: 0.4375
6/6 [==============================] - ETA: 0s - loss: 0.6912 - accuracy: 0.5286
6/6 [==============================] - 0s 47ms/step - loss: 0.6912 - accuracy: 0.5286 - val_loss: 0.6856 - val_accuracy: 0.5333
Epoch 2/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6829 - accuracy: 0.6094
6/6 [==============================] - 0s 16ms/step - loss: 0.6811 - accuracy: 0.5829 - val_loss: 0.6783 - val_accuracy: 0.6000
Epoch 3/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6839 - accuracy: 0.5938
6/6 [==============================] - 0s 13ms/step - loss: 0.6738 - accuracy: 0.6229 - val_loss: 0.6713 - val_accuracy: 0.6267
Epoch 4/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6572 - accuracy: 0.6875
6/6 [==============================] - 0s 13ms/step - loss: 0.6651 - accuracy: 0.6143 - val_loss: 0.6640 - val_accuracy: 0.6133
Epoch 5/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6543 - accuracy: 0.6250
6/6 [==============================] - 0s 13ms/step - loss: 0.6571 - accuracy: 0.6057 - val_loss: 0.6559 - val_accuracy: 0.6267
Epoch 6/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6484 - accuracy: 0.6406
6/6 [==============================] - 0s 13ms/step - loss: 0.6489 - accuracy: 0.6200 - val_loss: 0.6479 - val_accuracy: 0.6600
Epoch 7/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6436 - accuracy: 0.5938
6/6 [==============================] - 0s 13ms/step - loss: 0.6400 - accuracy: 0.6657 - val_loss: 0.6400 - val_accuracy: 0.6800
Epoch 8/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6231 - accuracy: 0.7188
6/6 [==============================] - 0s 13ms/step - loss: 0.6313 - accuracy: 0.6914 - val_loss: 0.6305 - val_accuracy: 0.6867
Epoch 9/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6288 - accuracy: 0.6562
6/6 [==============================] - 0s 13ms/step - loss: 0.6201 - accuracy: 0.6943 - val_loss: 0.6207 - val_accuracy: 0.6933
Epoch 10/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6157 - accuracy: 0.6875
6/6 [==============================] - 0s 13ms/step - loss: 0.6094 - accuracy: 0.6971 - val_loss: 0.6097 - val_accuracy: 0.7133
Epoch 11/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5846 - accuracy: 0.7031
6/6 [==============================] - 0s 13ms/step - loss: 0.5959 - accuracy: 0.7171 - val_loss: 0.6011 - val_accuracy: 0.7000
Epoch 12/20

1/6 [====>.........................] - ETA: 0s - loss: 0.6180 - accuracy: 0.6562
6/6 [==============================] - 0s 13ms/step - loss: 0.5858 - accuracy: 0.7200 - val_loss: 0.5867 - val_accuracy: 0.7267
Epoch 13/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5927 - accuracy: 0.7188
6/6 [==============================] - 0s 13ms/step - loss: 0.5729 - accuracy: 0.7286 - val_loss: 0.5776 - val_accuracy: 0.7267
Epoch 14/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5463 - accuracy: 0.7656
6/6 [==============================] - 0s 13ms/step - loss: 0.5552 - accuracy: 0.7457 - val_loss: 0.5618 - val_accuracy: 0.7467
Epoch 15/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5441 - accuracy: 0.7656
6/6 [==============================] - 0s 13ms/step - loss: 0.5417 - accuracy: 0.7743 - val_loss: 0.5482 - val_accuracy: 0.7467
Epoch 16/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5161 - accuracy: 0.7812
6/6 [==============================] - ETA: 0s - loss: 0.5239 - accuracy: 0.7886
6/6 [==============================] - 0s 13ms/step - loss: 0.5239 - accuracy: 0.7886 - val_loss: 0.5461 - val_accuracy: 0.7267
Epoch 17/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5033 - accuracy: 0.8281
6/6 [==============================] - ETA: 0s - loss: 0.5120 - accuracy: 0.7914
6/6 [==============================] - 0s 16ms/step - loss: 0.5120 - accuracy: 0.7914 - val_loss: 0.5264 - val_accuracy: 0.7600
Epoch 18/20

1/6 [====>.........................] - ETA: 0s - loss: 0.5423 - accuracy: 0.7031
6/6 [==============================] - ETA: 0s - loss: 0.4928 - accuracy: 0.8200
6/6 [==============================] - 0s 16ms/step - loss: 0.4928 - accuracy: 0.8200 - val_loss: 0.5212 - val_accuracy: 0.7533
Epoch 19/20

1/6 [====>.........................] - ETA: 0s - loss: 0.4671 - accuracy: 0.8594
5/6 [========================>.....] - ETA: 0s - loss: 0.4816 - accuracy: 0.8188
6/6 [==============================] - 0s 16ms/step - loss: 0.4749 - accuracy: 0.8286 - val_loss: 0.5046 - val_accuracy: 0.7600
Epoch 20/20

1/6 [====>.........................] - ETA: 0s - loss: 0.4780 - accuracy: 0.8594
6/6 [==============================] - ETA: 0s - loss: 0.4565 - accuracy: 0.8543
6/6 [==============================] - 0s 16ms/step - loss: 0.4565 - accuracy: 0.8543 - val_loss: 0.5059 - val_accuracy: 0.7467
Quitting from lines 82-108 (DeepPINCS.Rmd) 
Error: processing vignette 'DeepPINCS.Rmd' failed with diagnostics:
NotImplementedError: Layer MultiLinear has arguments in `__init__` and therefore must override `get_config`.

Detailed traceback:
  File "C:\Python38\lib\site-packages\tensorflow\python\keras\engine\functional.py", line 598, in get_config
    return copy.deepcopy(get_network_config(self))
  File "C:\Python38\lib\site-packages\tensorflow\python\keras\engine\functional.py", line 1278, in get_network_config
    layer_config = serialize_layer_fn(layer)
  File "C:\Python38\lib\site-packages\tensorflow\python\keras\utils\generic_utils.py", line 250, in serialize_keras_object
    raise e
  File "C:\Python38\lib\site-packages\tensorflow\python\keras\utils\generic_utils.py", line 245, in serialize_keras_object
    config = instance.get_config()
  File "C:\Python38\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 676, in get_config
    raise NotImplementedError('Layer %s has arguments in `__init__` and '

--- failed re-building 'DeepPINCS.Rmd'

SUMMARY: processing the following file failed:
  'DeepPINCS.Rmd'

Error: Vignette re-building failed.
Execution halted