Division by 0 in `DenseCountSparseOutput`
### Impact
An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`:
```python
import tensorflow as tf
values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])
tf.raw_ops.DenseCountSparseOutput(
values=values, weights=weights,
minlength=-1, maxlength=58, binary_output=True)
```
This is because the implementation
https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127 computes a divisor value from user data but does not check that the result is 0 before doing the division:
```cc
int num_batch_elements = 1;
for (int i = 0; i < num_batch_dimensions; ++i) {
num_batch_elements *= data.shape().dim_size(i);
}
int num_value_elements = data.shape().num_elements() / num_batch_elements;
```
Since `data` is given by the `values` argument, `num_batch_elements` is 0.
### Patches
We have patched the issue in GitHub commit da5ff2daf618591f64b2b62d9d9803951b945e9f
https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.
### For more information
Please consult our security guide
https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.