move DataSchemaValidatorMixin into standalone utils (#720)

# What does this PR do?

- there's no value in keeping data schema validation logic in a
DataSchemaValidatorMixin
- move into data schema validation logic into standalone utils

## Test Plan
```
pytest -v -s -m llm_as_judge_scoring_together_inference scoring/test_scoring.py --judge-model meta-llama/Llama-3.2-3B-Instruct
pytest -v -s -m basic_scoring_together_inference scoring/test_scoring.py
pytest -v -s -m braintrust_scoring_together_inference scoring/test_scoring.py

pytest -v -s -m meta_reference_eval_together_inference eval/test_eval.py
pytest -v -s -m meta_reference_eval_together_inference_huggingface_datasetio eval/test_eval.py
```



## Sources

Please link relevant resources if necessary.


## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.

llama_stack/providers/inline/eval/meta_reference/eval.py

@@ -18,8 +18,8 @@ from llama_stack.providers.datatypes import EvalTasksProtocolPrivate
 
 from llama_stack.providers.utils.common.data_schema_validator import (
     ColumnName,
-    DataSchemaValidatorMixin,
     get_valid_schemas,
+    validate_dataset_schema,
 )
 from llama_stack.providers.utils.kvstore import kvstore_impl
 
@@ -31,7 +31,10 @@ from .config import MetaReferenceEvalConfig
 EVAL_TASKS_PREFIX = "eval_tasks:"
 
 
-class MetaReferenceEvalImpl(Eval, EvalTasksProtocolPrivate, DataSchemaValidatorMixin):
+class MetaReferenceEvalImpl(
+    Eval,
+    EvalTasksProtocolPrivate,
+):
     def __init__(
         self,
         config: MetaReferenceEvalConfig,
@@ -85,7 +88,7 @@ class MetaReferenceEvalImpl(Eval, EvalTasksProtocolPrivate, DataSchemaValidatorM
         candidate = task_config.eval_candidate
         scoring_functions = task_def.scoring_functions
         dataset_def = await self.datasets_api.get_dataset(dataset_id=dataset_id)
-        self.validate_dataset_schema(
+        validate_dataset_schema(
             dataset_def.dataset_schema, get_valid_schemas(Api.eval.value)
         )
         all_rows = await self.datasetio_api.get_rows_paginated(