FPE in conv.h
Hi @SiriusHsh 

As this [comment](https://github.com/tensorflow/tensorflow/issues/60620#issuecomment-1553442519) suggests, please consult https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md#vulnerabilities-in-tensorflow and follow rules for responsible disclosure.

Thanks. Hi @SiriusHsh,

This has been fixed in this commit: https://github.com/tensorflow/tensorflow/commit/b40420ef4c2064b7eb5e26f9d1a1c6abdc3db0f4

You may test the changes with the tf-nightly package or by building from the master/nightly branch. If you are satisfied with the resolution please feel free to close this issue. 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/60622">Yes</a>
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<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

Yes

### Source

source

### Tensorflow Version

tf 2.14.0

### Custom Code

No

### OS Platform and Distribution

Ubuntu 18.04.6

### Mobile device

_No response_

### Python version

Python 3.8.3

### Bazel version

bazel 5.3.0

### GCC/Compiler version

gcc 7.5.0

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

The `groups` variable and `filters_per_group` variable may be equal to 0, leading to a division by zero error.

```c
inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
                 const float* input_data, const RuntimeShape& filter_shape,
                 const float* filter_data, const RuntimeShape& bias_shape,
                 const float* bias_data, const RuntimeShape& output_shape,
                 float* output_data, const RuntimeShape& im2col_shape,
                 float* im2col_data) {
    ...
  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
    ...
  const int input_depth = input_shape.Dims(3);
const int output_depth = MatchingDim(filter_shape, 0, output_shape, 3);
    ...
  const int groups = input_depth / filter_input_depth;
  TFLITE_DCHECK_EQ(input_depth % filter_input_depth, 0);
  const int filters_per_group = output_depth / groups; // FPE
	...
  for (int batch = 0; batch < batches; ++batch) {
    for (int out_y = 0; out_y < output_height; ++out_y) {
      const int in_y_origin = (out_y * stride_height) - pad_height;
      for (int out_x = 0; out_x < output_width; ++out_x) {
        const int in_x_origin = (out_x * stride_width) - pad_width;
        for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
          auto group = out_channel / filters_per_group;  // FPE

```

[conv_divide_by_zero.zip](https://github.com/tensorflow/tensorflow/files/11503617/conv_divide_by_zero.zip)


### Standalone code to reproduce the issue

```shell
When I use the benchmark tool for PoC validation, it causes the TensorFlow Lite inference process to be subjected to a DOS（coredump).


❯ ./benchmark_model --graph=./conv_divide_by_zero1.tflite
INFO: STARTING!
INFO: Log parameter values verbosely: [0]
INFO: Graph: [./conv_divide_by_zero1.tflite]
INFO: Loaded model ./conv_divide_by_zero1.tflite
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
INFO: The input model file size (MB): 0.000708
INFO: Initialized session in 0.68ms.
INFO: Running benchmark for at least 1 iterations and at least 0.5 seconds but terminate if exceeding 150 seconds.
[1]    6968 floating point exception (core dumped)  ./benchmark_model --graph=./conv_divide_by_zero1.tflite
```
```


### Relevant log output

_No response_</details>