Unexpected behavior in tf.data.Dataset.from_generator when there is a naming collision
Hi @kralka ,

I have replicated the issue with `TF2.15v` and `tf-nightly` as well. On Colab the code executes indefinitely due to naming collision of generator and finally runtime will crash without any logs. Attaching [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/07facdb64fa42d474b68cbe875040fd7/67566.ipynb) for reference. @SuryanarayanaY thank you for your response. One can get a crash (as opposed to indefinite execution without errors) in an official docker (`docker pull tensorflow/tensorflow:latest-gpu`). I will provide concrete steps if needed. Hi @SuryanarayanaY is there some plan to resolve this issue? Do you know what causes it? In case resolving would require too large changes do you think it is worth putting a note in the documentation since it is rather hard to figure out what causes this behavior?

Personally I would be interested in the cause of this since some magic needs to be happening here :-) Sorry my fault. This is not a TensorFlow issue.

```python
my_list = [1, 2, 3]

def gen():
  yield from my_list

my_list = [5, 6, 7]

assert list(gen()) == [5, 6, 7]
``` 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/67566">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/67566">No</a>

### Issue type

Documentation Bug

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

Yes

### Source

source

### TensorFlow version

2.15.0

### Custom code

Yes

### OS platform and distribution

colab

### Mobile device

_No response_

### Python version

3.10.12

### Bazel version

_No response_

### GCC/compiler version

11.4.0

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

When creating a `tf.data.Dataset` object using `from_generator` a naming collision with an iterable used in the `generator` parameter causes a crash.

On Ubuntu I got the following error (not in colab):
date: F external/local_tsl/tsl/platform/default/env.cc:74] Check failed: ret == 0 (11 vs. 0)Thread tf_data_private_threadpool creation via pthread_create() failed.

### Standalone code to reproduce the issue

```shell
import sys
print(f"Python version: {sys.version}")

import tensorflow as tf
print(f"{tf.__version__ = }")

# This runs as expected:

ds_no_name_collision = list(range(100))

def gen():
  print("gen called")
  for x in ds_no_name_collision:
    print(f"{x = }")
    yield x

# Notice there is no name collision:
ds_without_name_collision = tf.data.Dataset.from_generator(gen, output_signature=tf.TensorSpec(shape=(), dtype=tf.int32))

print("All good so far")

for x in ds_without_name_collision.take(10):
  print(x)



# This fails:

ds_name_collision = list(range(100))

def gen():
  print("gen called")
  for x in ds_name_collision:
    print(f"{x = }")
    yield x

# Notice the name collision:
ds_name_collision = tf.data.Dataset.from_generator(gen, output_signature=tf.TensorSpec(shape=(), dtype=tf.int32))

print("All good so far")

for x in ds_name_collision.take(10):
  print(x)
```


### Relevant log output

```shell
Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]
tf.__version__ = '2.15.0'
All good so far
gen called
x = 0
x = 1
tf.Tensor(0, shape=(), dtype=int32)
tf.Tensor(1, shape=(), dtype=int32)
x = 2
x = 3
x = 4
tf.Tensor(2, shape=(), dtype=int32)
x = 5
tf.Tensor(3, shape=(), dtype=int32)
tf.Tensor(4, shape=(), dtype=int32)
tf.Tensor(5, shape=(), dtype=int32)
x = 6
x = 7
x = 8
x = 9
tf.Tensor(6, shape=(), dtype=int32)
tf.Tensor(7, shape=(), dtype=int32)
tf.Tensor(8, shape=(), dtype=int32)
tf.Tensor(9, shape=(), dtype=int32)
All good so far
gen called
gen called
gen called
gen called
gen called
gen called
gen called
[log truncated]
```
