[BUG] Mutation warning being printed at every layer of EfficientNet when running LRP analyzer

### Describe the bug
Running any LRP analyzer, I get tensorflow warnings in the format of something like:
`2023-11-22 10:49:33.032371: W tensorflow/c/c_api.cc:305] Operation '{name:'mul_1355/x' id:43796 op device:{requested: '', assigned: ''} def:{{{node mul_1355/x}} = Const[_has_manual_control_dependencies=true, dtype=DT_FLOAT, value=Tensor]()}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.`

Being printed at what looks to be every single layer in the EfficientNet model I'm using. It also runs very slowly, taking about 15 minutes (longer if I use the sequential presets) to analyze the model. Is this runtime normal due to the size of the network? Can I safely ignore these warnings or is something actually wrong?

### Steps to reproduce the bug
NOTE: I had to implement juliowissing-iis's fix [here](https://github.com/albermax/innvestigate/issues/323) for this code block to run without errors.

```python
import tensorflow as tf
import tensorflow.keras.utils as ku
import numpy as np
import innvestigate as inn
from tensorflow.keras.applications import EfficientNetB5
import time

tf.compat.v1.disable_eager_execution()

# create EfficientNet B5 model with imagenet weights
model = EfficientNetB5(weights='imagenet')

# Read in data
img = ku.load_img('img.jpg',target_size = (456,456))
# Conver1 to numpy array
img_arr = ku.img_to_array(img)
# Add in extra 1st dim
img_CNN = np.array([img_arr])

# Remove last softmax layer (required for INNvestigate)
model_wo_softmax = inn.model_wo_softmax(model)

# Create LRP epsilon analyzer
analyzer = inn.create_analyzer("lrp.epsilon", model_wo_softmax,**{'epsilon':1})

# Analyze input image
t0=time.time()
a = analyzer.analyze(img_CNN)
t1=time.time()

total_time = t1-t0
print(f'Anaylzer took {total_time} seconds')

```

### Expected behavior
Minimal mutation warnings and a code that doesn't take 15 minutes to run.

### Platform information
- OS: Mac OSX 13.6.1 (this behavior also occurs on CentOS 7)
- Python version: 3.10.13
- iNNvestigate version: 2.1.2
- TensorFlow version: 2.14.0