### Issue type

Bug

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

No

### Source

source

### TensorFlow version

tf2.10

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Version
TensorFlow Version: 2.x (based on log structure)
CUDA Version: Unknown (from CUDA driver logs)
GPU Environment: Multi-GPU system
Python Version: 3.x
Current Behavior
Error Description
The application crashes with a core dump when performing FFT operations with extremely large fft_lengthvalues (36028797018963968). The failure sequence involves:
GPU memory allocation failure due to excessive memory request
cuFFT batched plan initialization failure
Fatal error in CUDA FFT component
Error Log Sequence
2025-11-21 10:27:15.599582: I tensorflow/stream_executor/cuda/cuda_driver.cc:733] failed to allocate 6.31M (6617856 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-11-21 10:27:15.630055: E tensorflow/stream_executor/cuda/cuda_fft.cc:225] failed to make cuFFT batched plan:5
2025-11-21 10:27:15.630112: E tensorflow/stream_executor/cuda/cuda_fft.cc:430] Initialize Params: rank: 2 elem_count: 2 input_embed: 2 input_stride: 1 input_distance: 4 output_embed: 2 output_stride: 1 output_distance: 4 batch_count: 1
2025-11-21 10:27:15.630128: F tensorflow/stream_executor/cuda/cuda_fft.cc:439] failed to initialize batched cufft plan with customized allocator: Failed to make cuFFT batched plan.
Aborted (core dumped)

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
input_data = tf.constant([[1.0 + 1.0j, 2.0 + 2.0j], [3.0 + 3.0j, 4.0 + 4.0j
    ]], dtype=tf.complex64)
fft_length = tf.constant([36028797018963968, 36028797018963968], dtype=tf.int32
    )
axes = tf.constant([0, 1], dtype=tf.int32)
result = tf.signal.fft2d(input_data)
```

### Relevant log output

```shell

```