Inconsistent Outputs from tf.nn.astrous_conv2d multiplied with tf.cos on XLA compiled model 
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Issue type
Bug

Have you reproduced the bug with TensorFlow Nightly?
Yes

Source
source

TensorFlow version
2.15.0

Custom code
Yes

OS platform and distribution
Ubuntu 22.04.3 LTS

Mobile device
No response

Python version
3.10

Bazel version
No response

GCC/compiler version
No response

CUDA/cuDNN version
cuda : 12.2 / cudnn 8.9.04

GPU model and memory
Tesla V100S-PCIE-32GB

Current behavior?
I've identified a critical issue in TensorFlow 2.15.0 where the combination of tf.nn.conv2d and tf.cos in an XLA compiled model produces significantly different outputs compared to the eager execution mode. This inconsistency is particularly concerning given that the data type used is float32, which is a standard in many applications. This issue only occurs with certain input data with gpu device

To reproduce this, please download first [pickle file](https://github.com/GwiHwan-Go/repo/raw/main/conv_cos_bug_inputs.pickle) and replace YOUR_PICKLE_FILE_PATH with your pickle file path.