TFlite Convert Fails to check for bias type int32 
Hi @Naveen-Dodda , Thanks for creating the issue.
This issue was discussed with the TFLite team, we are looking into the issue.
It makes more sense to throw an error during conversion itself than throwing error during Interpreter to avoid more confusion.
@haozha111 , to give more context this works fine with the float conversion but fails with the below configuration.

```
converter.target_spec.supported_ops = [
    tf.lite.OpsSet.EXPERIMENTAL_TFLITE_BUILTINS_ACTIVATIONS_INT16_WEIGHTS_INT8
]
``` Is there a specific reason why INT16_WEIGHTS_INT8 cannot operate with INT32 dtype bias ?

TFlite converter allows bias type int32; but interpreter fails to allocate tensors. 

1) [Colab to reproduce issue]https://gist.github.com/Naveen-Dodda/2427001bc4b8fb1e05f0a4d84d201e4e): Demonstrate how the model is built and converted to tflite.

### 3. Failure after conversion
 The conversion works fine but Interpreter fails to allocate tensors. I am wondering if this issue can be fixed.

RuntimeError                              Traceback (most recent call last)
<ipython-input-8-514827761d7e> in <cell line: 5>()
      3 signatures = quantizer.get_signature_list()
      4 print(signatures)
----> 5 quantizer.allocate_tensors()

/usr/local/lib/python3.9/dist-packages/tensorflow/lite/python/interpreter.py in allocate_tensors(self)
    505   def allocate_tensors(self):
    506     self._ensure_safe()
--> 507     return self._interpreter.AllocateTensors()
    508 
    509   def _safe_to_run(self):

RuntimeError: tensorflow/lite/kernels/depthwise_conv.cc:149 bias->type != kTfLiteInt64 (INT32 != INT64)Node number 1 (DEPTHWISE_CONV_2D) failed to prepare.Failed to apply the default TensorFlow Lite delegate indexed at 0

### 5. (optional) Any other info / logs

https://github.com/tensorflow/tensorflow/blob/v2.12.0/tensorflow/lite/python/lite.py#L479

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/kernels/depthwise_conv.cc#L149

