aws / aws/sagemaker-python-sdk

ModelPackage.get_all() fails with ParamValidationError for versioned packages in a model package group

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Description

**PySDK Version**
- [ ] PySDK V2 (2.x)
- [x] PySDK V3 (3.x)

**Describe the bug**
`ModelPackage.get_all()` fails with `ParamValidationError: Missing required parameter in input: "ModelPackageName"` when listing versioned model packages within a model package group. The `ResourceIterator` calls `refresh()` on each `ModelPackage` object it constructs from the list summary. The `refresh()` method uses `self.model_package_name` to call `DescribeModelPackage`, but for versioned model packages the `ListModelPackages` API does not return `ModelPackageName`; it only returns `ModelPackageArn`. Since `model_package_name` remains `Unassigned`, it gets serialized to `None` and dropped from the request, causing the missing parameter error.

**To reproduce**
Prerequisites: An existing model package group with at least one versioned model package.

```python
from sagemaker.core.resources import ModelPackage

# This will fail on the first iteration when refresh() is called
for pkg in ModelPackage.get_all(
model_package_group_name="",
sort_by="CreationTime",
sort_order="Descending",
):
print(pkg.model_package_arn)
```

**Expected behavior**
ModelPackage.get_all() should successfully iterate over all model packages in the group. The refresh() method should
fall back to using model_package_arn when model_package_name is not available, since DescribeModelPackage accepts either a name or an ARN for the ModelPackageName parameter.

**Screenshots or logs**
```
ParamValidationError: Parameter validation failed: Missing required parameter in input: "ModelPackageName"

File "sagemaker/core/utils/utils.py", line 469, in __next__
resource_object.refresh()
File "sagemaker/core/resources.py", line 25130, in refresh
response = client.describe_model_package(**operation_input_args)
```

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: 3.5
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: N/A
- **Framework version**: N/A
- **Python version**: 3.12
- **CPU or GPU**: CPU
- **Custom Docker image (Y/N)**: N

**Additional context**
N/A

Contributor guide

Open the contributing guide

Research direction

Start in sagemaker/core/resources.py at ModelPackage.refresh() and inspect the ResourceIterator path in sagemaker/core/utils/utils.py. Reproduce the failure with a versioned model package group, then verify that ModelPackage.get_all() can iterate successfully when only an ARN is returned and that the request satisfies DescribeModelPackage validation.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, python
Domain
api, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
55/100

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