When performing inference, the error 'DNN library not found.' occurs intermittently.
Hi **@kimbyungeun** ,

- Sorry for the delay, Check your environment variables related to CUDA and cuDNN. Set LD_LIBRARY_PATH to include the directories containing the CUDA and cuDNN libraries. 
- Run a script to check if tensorflow can detect your GPU and if it's using the correct CUDA/cuDNN versions.
```
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
```
- Clearing the tensorflow cache can resolve intermittent issues. You can do this by deleting the '~/.keras' directory.
- If the issue persists, consider reinstalling TensorFlow and its dependencies from scratch. Use a virtual environment to isolate the installation.

Thank you!

 Hi @Venkat6871 

I am planning to proceed with the following two tasks:

* Set the LD_LIBRARY_PATH environment variable in a Docker container.
* Downgrade CUDA version from 11.3.0 to 11.2.2.
   * https://github.com/googlecolab/colabtools/issues/2600#issuecomment-1061312120

Additionally, I have a question:
* Between CUDA 11.3.1 and CUDA 11.2.2, which direction would be better? Please recommend.

Thank you! Hi @kimbyungeun ,
- As per [documentation](https://www.tensorflow.org/install/source#gpu). For TF 2.11 compatible version is CUDA 11.2.2. So i can say this compatible version for smooth installation.

Thank you! Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/65033">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/65033">No</a>
 The base image has been changed from `nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04` to `nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04`, and so far the same error has not occurred. It is considered to be resolved.

https://hub.docker.com/layers/nvidia/cuda/11.3.1-cudnn8-devel-ubuntu20.04/images/sha256-278b6f43436029c8fa7b4905970457156774178b99509aa753b08547fb721cd9?context=explore

https://hub.docker.com/layers/nvidia/cuda/11.2.2-cudnn8-devel-ubuntu20.04/images/sha256-7d4850083e83853f757014e9fb852934907317a4830013591ec71480181232e7?context=explore

@Venkat6871 👍 
### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

No

### Source

binary

### TensorFlow version

TF 2.11

### Custom code

Yes

### OS platform and distribution

Ubuntu 20.04 LTS 5.15.0-46-generic

### Mobile device

_No response_

### Python version

3.8.10

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

11.3.0 / 8.2.0.53

### GPU model and memory

NVIDIA A16

### Current behavior?

When attempting inference, the error 'DNN library is not found.' occurs, leading to inference failure. This error does not occur every time but happens randomly, and sometimes it does not occur at all.


### Standalone code to reproduce the issue

```shell
os.environ["CUDA_VISIBLE_DEVICES"] = self.gpu_no
self.model = tf.keras.models.load_model(self.model_file_path)

size = tf_model.get_model_image_size(self.model_type)
img = tf.keras.preprocessing.image.load_img(image_file, target_size=(size, size))
img_array = tf.keras.preprocessing.image.img_to_array(img)
img_array = tf.expand_dims(img_array, 0)  

predictions = self.model.predict(img_array)
```


### Relevant log output

```shell
Exception: Graph execution error:
 Detected at node 'efficientnetb6/efficientnetb6_backbone/efficientnetb6_m1/stem_conv/Conv2D' defined at (most recent call last):
   File "/home/user/inference.py", line 170, in predict_multi_step
    predictions = self.model.predict(img_array)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/training.py", line 561, in __call__
    return super().__call__(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 511, in call
    return self._run_internal_graph(inputs, training=training, mask=mask)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 668, in _run_internal_graph
    outputs = node.layer(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/training.py", line 561, in __call__
    return super().__call__(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 511, in call
    return self._run_internal_graph(inputs, training=training, mask=mask)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 668, in _run_internal_graph
    outputs = node.layer(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/training.py", line 561, in __call__
    return super().__call__(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 511, in call
    return self._run_internal_graph(inputs, training=training, mask=mask)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 668, in _run_internal_graph
    outputs = node.layer(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/layers/convolutional/base_conv.py", line 283, in call
    outputs = self.convolution_op(inputs, self.kernel)
   File "/usr/local/lib/python3.8/dist-packages/keras/layers/convolutional/base_conv.py", line 255, in convolution_op
    return tf.nn.convolution(
 Node: 'efficientnetb6/efficientnetb6_backbone/efficientnetb6_m1/stem_conv/Conv2D'
 Detected at node 'efficientnetb6/efficientnetb6_backbone/efficientnetb6_m1/stem_conv/Conv2D' defined at (most recent call last):
   File "/home/user/inference.py", line 170, in predict_multi_step
    predictions = self.model.predict(img_array)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/training.py", line 561, in __call__
    return super().__call__(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 511, in call
    return self._run_internal_graph(inputs, training=training, mask=mask)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 668, in _run_internal_graph
    outputs = node.layer(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/training.py", line 561, in __call__
    return super().__call__(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 511, in call
    return self._run_internal_graph(inputs, training=training, mask=mask)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 668, in _run_internal_graph
    outputs = node.layer(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/training.py", line 561, in __call__
    return super().__call__(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 511, in call
    return self._run_internal_graph(inputs, training=training, mask=mask)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/functional.py", line 668, in _run_internal_graph
    outputs = node.layer(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/engine/base_layer.py", line 1132, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
    return fn(*args, **kwargs)
   File "/usr/local/lib/python3.8/dist-packages/keras/layers/convolutional/base_conv.py", line 283, in call
    outputs = self.convolution_op(inputs, self.kernel)
   File "/usr/local/lib/python3.8/dist-packages/keras/layers/convolutional/base_conv.py", line 255, in convolution_op
    return tf.nn.convolution(
 Node: 'efficientnetb6/efficientnetb6_backbone/efficientnetb6_m1/stem_conv/Conv2D'
 2 root error(s) found.
  (0) UNIMPLEMENTED: DNN library is not found.
  [[{{node efficientnetb6/efficientnetb6_backbone/efficientnetb6_m1/stem_conv/Conv2D}}]]
  [[Func/efficientnetb6/efficientnetb6_head/conditional_multi_head_v6/while/body/_1/efficientnetb6/efficientnetb6_head/conditional_multi_head_v6/while/StatefulPartitionedCall/StatefulPartitionedCall/output_control_node/_983/_177]]
  (1) UNIMPLEMENTED: DNN library is not found.
  [[{{node efficientnetb6/efficientnetb6_backbone/efficientnetb6_m1/stem_conv/Conv2D}}]]
 0 successful operations.
```
