Jupyter Notebook kernel keep crashing(Could not load library cudnn_cnn_infer64_8.dll. Error code 193)

Question

I am running a tensorflow code but the kernel of jupyter notebook keeps crashing, i searched the error i was getting in logs which said "Could not load library cudnn_cnn_infer64_8.dll. Error code 193". I tried the solutions from differenct users of using compatible CUDA and cuDnn. Tried various combinations but the error still remains same. Versions of CUDA and cuDnn I tried are: Cuda v11.7 cudnn 8.4.0.27 Cuda v11.6 cudnn 8.4.0.27 Cuda v11.6 cudnn 8.3.1.22

I have also given the paths of Cuda and cudnn correctly in the environment variable.

Here is the logs...

C:\Users\Sachal Raja>jupyter-notebook
[I 17:18:55.635 NotebookApp] Serving notebooks from local directory: C:\Users\Sachal Raja
[I 17:18:55.635 NotebookApp] Jupyter Notebook 6.4.11 is running at:
[I 17:18:55.635 NotebookApp] http://localhost:8888/?token=ea2a961618582e46f95937ee7beee00c8cd163dfc3230502
[I 17:18:55.635 NotebookApp]  or http://127.0.0.1:8888/?token=ea2a961618582e46f95937ee7beee00c8cd163dfc3230502
[I 17:18:55.635 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 17:18:55.870 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///C:/Users/Sachal%20Raja/AppData/Roaming/jupyter/runtime/nbserver-13152-open.html
    Or copy and paste one of these URLs:
        http://localhost:8888/?token=ea2a961618582e46f95937ee7beee00c8cd163dfc3230502
     or http://127.0.0.1:8888/?token=ea2a961618582e46f95937ee7beee00c8cd163dfc3230502
[W 17:19:15.744 NotebookApp] 404 GET /nbextensions/widgets/notebook/js/extension.js?v=20220521171854 (::1) 64.830000ms referer=http://localhost:8888/notebooks/Desktop/ctc_asr.ipynb
[I 17:19:17.391 NotebookApp] Kernel started: 49107dc3-9e85-4e51-b176-37b4c2881f4f, name: python3
2022-05-21 17:19:44.730767: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-05-21 17:19:51.600339: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /device:GPU:0 with 2149 MB memory:  -> device: 0, name: NVIDIA GeForce GTX 1650, pci bus id: 0000:01:00.0, compute capability: 7.5
2022-05-21 17:19:51.662909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 2149 MB memory:  -> device: 0, name: NVIDIA GeForce GTX 1650, pci bus id: 0000:01:00.0, compute capability: 7.5
2022-05-21 17:20:30.323369: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8400
Could not load library cudnn_cnn_infer64_8.dll. Error code 193
[I 17:20:32.374 NotebookApp] KernelRestarter: restarting kernel (1/5), keep random ports
WARNING:root:kernel 49107dc3-9e85-4e51-b176-37b4c2881f4f restarted

Code snippet where error arises: Code snippet

Answer 1

The purpose of Entity Framework Core is to build a code model for a known database. Thus, it is a very poor fit for your application.

Instead, just use regular ADO.NET methods with a library such as MySqlConnector. You can use the DbConnection.GetSchema method to get a list of all schemas and tables (that your MySQL user account has permission to view).

using var connection = new MySqlConnection("Server=...;User=...");
connection.Open();

var databases = connection.GetSchema("DATABASES");
var tables = connection.GetSchema("TABLES");

// process the two DataTables retrieved above...