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I've spent several hours today trying to make my app work and even upgraded just to avoid space problems, unfortunately I keep getting the following error (my app uses Tensorflow 2.3.0 and a saved model .h5 in it):

2021-02-02 03:21:16.621430: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dler ror: libcudart.so.10.1: cannot open shared object file: No such file or directory 2021-02-02 03:21:16.621488: 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. 2021-02-02 03:21:27.532069: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory 2021-02-02 03:21:27.532135: W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303) 2021-02-02 03:21:27.532165: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (blu e-liveconsole3): /proc/driver/nvidia/version does not exist 2021-02-02 03:21:27.532518: 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 AVX512F FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2021-02-02 03:21:27.558443: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 2500080000 Hz 2021-02-02 03:21:27.562421: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x46263d0 initialized for platform Host (this does not gua rantee that XLA will be used). Devices: 2021-02-02 03:21:27.562462: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2021-02-02 03:21:27.571226: F tensorflow/core/platform/env.cc:351] Check failed: -1 != path_length (-1 vs. -1) Aborted

I'm using my own Virtualenv. Is there a way to fix my app without downgrading to other Tensorflow version? After reading several posts, they seem to suggest that it is not possible (apparently Pythonanywhere does not support GPU with CUDA cores), but I wanted to be sure

Code that requires GPU won't work on PythonAnywhere and we don't expect that to change in the near future.