### 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 driver logs)
GPU Environment: Multi-GPU system
Python Version: 3.x
Current Behavior
Error Description
The application crashes with a core dump when executing tf.map_fnwith parallel_iterationsparameter in eager execution mode. The failure sequence involves:
GPU memory allocation failure (despite small request size)
Stream synchronization issues
Invalid CUDA handle errors during memory copy
Fatal GPU->CPU memcpy failure
Error Log Sequence
2025-11-21 10:41:37.494986: I tensorflow/stream_executor/cuda/cuda_driver.cc:733] failed to allocate 2.2K (2304 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
WARNING:tensorflow:Setting parallel_iterations > 1 has no effect when executing eagerly. Consider calling map_fn with tf.function to execute fn in parallel.
2025-11-21 10:41:38.458887: I tensorflow/stream_executor/stream.cc:1035] [stream=0xae19b10,impl=0x3b680520] did not wait for [stream=0xbf17eea0,impl=0x3b6804f0]
2025-11-21 10:41:38.458941: E tensorflow/stream_executor/cuda/cuda_driver.cc:1157] failed to enqueue async memcpy from device to host: CUDA_ERROR_INVALID_HANDLE: invalid resource handle; host dst: 0xbfb6e980; GPU src: 0x7fec61c00200; size: 1=0x1
2025-11-21 10:41:38.458967: E tensorflow/stream_executor/stream.cc:320] Error recording event in stream: Error recording CUDA event: CUDA_ERROR_INVALID_HANDLE: invalid resource handle; not marking stream as bad, as the Event object may be at fault. Monitor for further errors.
2025-11-21 10:41:38.459028: F tensorflow/core/common_runtime/gpu/gpu_util.cc:303] GPU->CPU Memcpy failed
Aborted (core dumped)

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
input_data = tf.constant([1, 2, 3, 4, 5])


def square(x):
    return x * x


result = tf.map_fn(fn=square, elems=input_data, dtype=tf.int32,
    parallel_iterations=10, back_prop=True, swap_memory=False, infer_shape=
    True, name='map_fn_example', fn_output_signature=tf.int32)
print(result)
```

### Relevant log output

```shell

```