Node: 'model/conv1d/Conv1D' DNN library is not found.

Hello i hope everyone is good. I am trying to run a python code using tensor-flow. I have GPU RTX2080 and have installed tensorflow=2.12.0 using the instructions given on "https://www.tensorflow.org/install/pip". when i run the code i get the following error.

Epoch 1/10
2023-06-19 17:03:27.840554: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:417] Loaded runtime CuDNN library: 8.0.5 but source was compiled with: 8.6.0. CuDNN library needs to have matching major version and equal or higher minor version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
2023-06-19 17:03:27.841329: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at conv_ops.cc:1068 : UNIMPLEMENTED: DNN library is not found.
2023-06-19 17:03:27.841375: I tensorflow/core/common_runtime/executor.cc:1197] [/job:localhost/replica:0/task:0/device:GPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): UNIMPLEMENTED: DNN library is not found.
[[{{node model/conv1d/Conv1D}}]]
Traceback (most recent call last):
File "/home/csu/USMAN/Transformer-for-wind_speed-dev/TS_Reg_Trans/main.py", line 91, in
history=model.fit(X_train,y_train,validation_split=0.1,epochs=args.e,batch_size=args.b_s,callbacks=[early_stop,checkpoint])
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/tensorflow/python/eager/execute.py", line 52, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.UnimplementedError: Graph execution error:

Detected at node 'model/conv1d/Conv1D' defined at (most recent call last):
File "/home/csu/USMAN/Transformer-for-wind_speed-dev/TS_Reg_Trans/main.py", line 91, in
history=model.fit(X_train,y_train,validation_split=0.1,epochs=args.e,batch_size=args.b_s,callbacks=[early_stop,checkpoint])
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/training.py", line 1685, in fit
tmp_logs = self.train_function(iterator)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/training.py", line 1284, in train_function
return step_function(self, iterator)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/training.py", line 1268, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/training.py", line 1249, in run_step
outputs = model.train_step(data)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/training.py", line 1050, in train_step
y_pred = self(x, training=True)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/training.py", line 558, in call
return super().call(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/base_layer.py", line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/functional.py", line 512, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/functional.py", line 669, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/engine/base_layer.py", line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/layers/convolutional/base_conv.py", line 290, in call
outputs = self.convolution_op(inputs, self.kernel)
File "/home/csu/anaconda3/envs/simple/lib/python3.9/site-packages/keras/layers/convolutional/base_conv.py", line 262, in convolution_op
return tf.nn.convolution(
Node: 'model/conv1d/Conv1D'
DNN library is not found.
[[{{node model/conv1d/Conv1D}}]] [Op:__inference_train_function_20730]
I have set the paths using the instructions given on "https://www.tensorflow.org/install/pip" still it fails to load the cudnn properly Any solution???

Start with the reported failure at TS_Reg_Trans/main.py line 91 and review the TensorFlow pip installation instructions alongside the logged CUDA/cuDNN versions. Reproduce the Conv1D training run and verify the environment configuration; done means the training run completes without the DNN library error or the compatibility requirements are documented.