2021-04-13 15:58:15.397351: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2)
Epoch 1/5
2021-04-13 15:58:21.108870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-13 15:58:21.309964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
109/109 - 10s - loss: 14.1373 - activation_1_loss: 0.1491 - activation_loss: 6.3234 - activation_1_msse: 0.1233 - activation_msse: 0.2453
Epoch 2/5
109/109 - 4s - loss: 10.7089 - activation_1_loss: 0.1276 - activation_loss: 4.7167 - activation_1_msse: 0.1048 - activation_msse: 0.2671
Epoch 3/5
109/109 - 4s - loss: 9.3554 - activation_1_loss: 0.1185 - activation_loss: 4.0850 - activation_1_msse: 0.0970 - activation_msse: 0.2107
Epoch 4/5
109/109 - 4s - loss: 8.6628 - activation_1_loss: 0.1127 - activation_loss: 3.7677 - activation_1_msse: 0.0921 - activation_msse: 0.2026
Epoch 5/5
109/109 - 4s - loss: 8.3032 - activation_1_loss: 0.1092 - activation_loss: 3.6058 - activation_1_msse: 0.0891 - activation_msse: 0.1976
WARNING:tensorflow:Layer gru will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.
WARNING:tensorflow:Layer gru_1 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.
WARNING:tensorflow:Layer gru_2 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.
WARNING:tensorflow:Layer gru_3 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.
WARNING:tensorflow:Layer gru_4 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.
Traceback (most recent call last):
File "E:\repositories\nnom\examples\rnn-denoise\main.py", line 307, in
main()
File "E:\repositories\nnom\examples\rnn-denoise\main.py", line 292, in main
filtered_sig = voice_denoise(sig, rate, model, timestamp_size, numcep=y_train.shape[-1], plot=True) # use plot=True argument to see the gains/vad
File "E:\repositories\nnom\examples\rnn-denoise\main.py", line 84, in voice_denoise
prediction = model.predict(feat, batch_size=timestamp_size)
File "C:\Program Files\Python39\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1742, in predict
raise ValueError('Expect x to be a non-empty array or dataset.')
ValueError: Expect x to be a non-empty array or dataset.
2021-04-13 15:58:15.397351: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2) Epoch 1/5 2021-04-13 15:58:21.108870: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll 2021-04-13 15:58:21.309964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll 109/109 - 10s - loss: 14.1373 - activation_1_loss: 0.1491 - activation_loss: 6.3234 - activation_1_msse: 0.1233 - activation_msse: 0.2453 Epoch 2/5 109/109 - 4s - loss: 10.7089 - activation_1_loss: 0.1276 - activation_loss: 4.7167 - activation_1_msse: 0.1048 - activation_msse: 0.2671 Epoch 3/5 109/109 - 4s - loss: 9.3554 - activation_1_loss: 0.1185 - activation_loss: 4.0850 - activation_1_msse: 0.0970 - activation_msse: 0.2107 Epoch 4/5 109/109 - 4s - loss: 8.6628 - activation_1_loss: 0.1127 - activation_loss: 3.7677 - activation_1_msse: 0.0921 - activation_msse: 0.2026 Epoch 5/5 109/109 - 4s - loss: 8.3032 - activation_1_loss: 0.1092 - activation_loss: 3.6058 - activation_1_msse: 0.0891 - activation_msse: 0.1976 WARNING:tensorflow:Layer gru will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU. WARNING:tensorflow:Layer gru_1 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU. WARNING:tensorflow:Layer gru_2 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU. WARNING:tensorflow:Layer gru_3 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU. WARNING:tensorflow:Layer gru_4 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU. Traceback (most recent call last): File "E:\repositories\nnom\examples\rnn-denoise\main.py", line 307, in
main()
File "E:\repositories\nnom\examples\rnn-denoise\main.py", line 292, in main
filtered_sig = voice_denoise(sig, rate, model, timestamp_size, numcep=y_train.shape[-1], plot=True) # use plot=True argument to see the gains/vad
File "E:\repositories\nnom\examples\rnn-denoise\main.py", line 84, in voice_denoise
prediction = model.predict(feat, batch_size=timestamp_size)
File "C:\Program Files\Python39\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1742, in predict
raise ValueError('Expect x to be a non-empty array or dataset.')
ValueError: Expect x to be a non-empty array or dataset.