[5763424][ONNX][Autocast] Fix ConstantOfShape layer output precision (#789)

## What does this PR do?

**Type of change:** Bug fix

**Overview:** Fixed the output precision of ConstantOfShape layers in
models with custom ops.

## Usage
<!-- You can potentially add a usage example below. -->

```python
$ python -m modelopt.onnx.quantization --onnx_path=$MODEL_NAME.onnx
```

## Testing
See bug 5763424.

## Before your PR is "*Ready for review*"
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`Draft` PR. -->

- **Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md)**
and your commits are signed.
- **Is this change backward compatible?**: Yes
- **Did you write any new necessary tests?**: No
- **Did you add or update any necessary documentation?**: No
- **Did you update
[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?**:
No <!--- Only for new features, API changes, critical bug fixes or bw
breaking changes. -->

## Additional Information
This issue only affects models with custom ops.


<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **Bug Fixes**
* Improved type propagation handling for ConstantOfShape operations in
ONNX autocast, ensuring correct precision type conversion across related
operations.

<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Signed-off-by: gcunhase <4861122+gcunhase@users.noreply.github.com>

Author: gcunhase

modelopt/onnx/autocast/precisionconverter.py

@@ -347,6 +347,8 @@ def _get_np_type(node, inp, opset=onnx.defs.onnx_opset_version()):
                 return node.inputs[1].dtype  # scale type
             elif node.op == "QuantizeLinear":
                 return node.inputs[2].dtype  # zero_point type
+            elif node.op == "ConstantOfShape":
+                return node.attrs["value"].dtype
             elif not inp.dtype or inp.dtype == onnx.TensorProto.UNDEFINED:
                 return None
             elif node.op not in self.custom_ops: