Open hadaev8 opened 4 years ago
Can you confirm that the code is running on GPU and not CPU?
Should be gpu, but actually i'm not sure
Tacotron gst is known to hang on CPU #439. Although another user has reported errors on Google colab #476. Unfortunately, just like the CPU issue, we most likely will not be able to fix it if it is a Google colab issue.
Same issue. It is running on local single GPU(1660 Ti) in mine and it is definitely using a GPU(nvidia_smi shows it's being used). I'm training a tacatron_float for text-to-speech conversion model on the LJSpeech dataset. I have tried reducing batch size but it doesn't seem to fix the issue.
Were you able to resolve the issue?I am also facing the same issue. I am using 6 GB Nvidia Geforce GTX 1060 with Cuda 10.0 and nvidia drivers 430.64. My batch size is 32. I had to reduce it from 48 due to cuda out of memory error. GPU utilisation in Nvidia-smi shows 1988/6078 MiB utilised. Volatile GPU util is very less (1%-4%)
Use tf.GraphKeys.GLOBAL_VARIABLES
instead.
*** WARNING: Can't compute number of objects per step, since train model does not define get_num_objects_per_step method.
2020-08-04 14:37:19.226539: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
I am also facing the same issue. Any solution for the same? I am using tacotron_gst.py config file and pre-trained weights shared here (https://nvidia.github.io/OpenSeq2Seq/html/speech-synthesis.html). Other config is shared below- GPU- V100 Cuda - 10.0 Python - 3.6.10 Tensorflow - 1.15.0
It stuck on
Code https://colab.research.google.com/drive/10DxRZTqmIPE6983fGEZ2UDjRrcvM99pK