[ML] fix(next-pylint): Resolve arguments-differ and name-too-long (…

…Azure#31234)

* fix(next-pylint): Resolve `arguments-differ`

    Endpoint._from_rest_object:

        * Wasn't marked as @classmethod
        * Had a first argument of `self` instead of `cls`

    Made name of second parameter consistent across
    {Endpoint,BatchEndpoint,OnlineEndpoint}._from_rest_object

* refactor: validate_pipeline_input_key_contains_allowed_characters -> validate_pipeline_input_key_characters

* refactor: try_get_non_arbitrary_attr_for_potential_attr_dict -> try_get_non_arbitrary_attr

* refactor: parse_pipeline_input_names_from_data_binding -> PipelineExpression.parse_pipeline_inputs_from_data_binding

* refactor: get_choice_{,and_single_value_}schema_of_type -> choice_{,and_single_value_}schema_of_type

* fix: Add `pylint: disable=name-too-long`

    Added in situations where the isn't an obvious rename

* refactor: read_remote_feature_set_spec_metadata_contents -> read_remote_feature_set_spec_metadata

* refactor: Remove dead code

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/entities/runsettings/ai_super_computer_configuration.py

@@ -19,7 +19,7 @@ def items(self):
         return result
 
 
-class AISuperComputerStorageReferenceConfiguration(PascalCaseProperty):
+class AISuperComputerStorageReferenceConfiguration(PascalCaseProperty):  # pylint: disable=name-too-long
     _KEY_MAPPING = {
         "container_name": "ContainerName",
         "relative_path": "RelativePath",

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_deployment/batch/batch_pipeline_component_deployment_configurations_schema.py

@@ -22,7 +22,7 @@
 
 module_logger = logging.getLogger(__name__)
 
-
+# pylint: disable-next=name-too-long
 class BatchPipelineComponentDeploymentConfiguarationsSchema(metaclass=PatchedSchemaMeta):
     component_id = fields.Str()
     job = UnionField(

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_feature_set/featureset_spec_properties_schema.py

@@ -13,6 +13,7 @@
 from .source_metadata_schema import SourceMetadataSchema
 
 
+# pylint: disable-next=name-too-long
 class FeatureTransformationCodePropertiesSchema(metaclass=PatchedSchemaMeta):
     path = fields.Str(data_key="Path")
     transformer_class = fields.Str(data_key="TransformerClass")

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_utils/data_binding_expression.py

@@ -58,7 +58,7 @@ def _add_data_binding_to_field(field, attrs_to_skip, schema_stack):
     return field
 
 
-def support_data_binding_expression_for_fields(
+def support_data_binding_expression_for_fields(  # pylint: disable=name-too-long
     schema: Union[PathAwareSchema, Schema], attrs_to_skip=None, schema_stack=None
 ):
     """Update fields inside schema to support data binding string.

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/automl/image_vertical/image_model_distribution_settings.py

@@ -33,26 +33,26 @@
 from azure.ai.ml._utils.utils import camel_to_snake
 
 
-def get_choice_schema_of_type(cls, **kwargs):
+def choice_schema_of_type(cls, **kwargs):
     class CustomChoiceSchema(ChoiceSchema):
         values = fields.List(cls(**kwargs))
 
     return CustomChoiceSchema()
 
 
-def get_choice_and_single_value_schema_of_type(cls, **kwargs):
+def choice_and_single_value_schema_of_type(cls, **kwargs):
     # Reshuffling the order of fields for allowing choice of booleans.
     # The reason is, while dumping [Bool, Choice[Bool]] is parsing even dict as True.
     # Since all unionFields are parsed sequentially, to avoid this, we are giving the "type" field at the end.
-    return UnionField([NestedField(get_choice_schema_of_type(cls, **kwargs)), cls(**kwargs)])
+    return UnionField([NestedField(choice_schema_of_type(cls, **kwargs)), cls(**kwargs)])
 
 
 FLOAT_SEARCH_SPACE_DISTRIBUTION_FIELD = UnionField(
     [
         fields.Float(),
         DumpableIntegerField(strict=True),
-        NestedField(get_choice_schema_of_type(DumpableIntegerField, strict=True)),
-        NestedField(get_choice_schema_of_type(fields.Float)),
+        NestedField(choice_schema_of_type(DumpableIntegerField, strict=True)),
+        NestedField(choice_schema_of_type(fields.Float)),
         NestedField(UniformSchema()),
         NestedField(QUniformSchema()),
         NestedField(NormalSchema()),
@@ -64,15 +64,15 @@ def get_choice_and_single_value_schema_of_type(cls, **kwargs):
 INT_SEARCH_SPACE_DISTRIBUTION_FIELD = UnionField(
     [
         DumpableIntegerField(strict=True),
-        NestedField(get_choice_schema_of_type(DumpableIntegerField, strict=True)),
+        NestedField(choice_schema_of_type(DumpableIntegerField, strict=True)),
         NestedField(RandintSchema()),
         NestedField(IntegerQUniformSchema()),
         NestedField(IntegerQNormalSchema()),
     ]
 )
 
-STRING_SEARCH_SPACE_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(DumpableStringField)
-BOOL_SEARCH_SPACE_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(fields.Bool)
+STRING_SEARCH_SPACE_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(DumpableStringField)
+BOOL_SEARCH_SPACE_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(fields.Bool)
 
 model_size_enum_args = {"allowed_values": [o.value for o in ModelSize], "casing_transform": camel_to_snake}
 learning_rate_scheduler_enum_args = {
@@ -86,14 +86,12 @@ def get_choice_and_single_value_schema_of_type(cls, **kwargs):
 }
 
 
-MODEL_SIZE_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(
-    StringTransformedEnum, **model_size_enum_args
-)
-LEARNING_RATE_SCHEDULER_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(
+MODEL_SIZE_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(StringTransformedEnum, **model_size_enum_args)
+LEARNING_RATE_SCHEDULER_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(
     StringTransformedEnum, **learning_rate_scheduler_enum_args
 )
-OPTIMIZER_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(StringTransformedEnum, **optimizer_enum_args)
-VALIDATION_METRIC_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(
+OPTIMIZER_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(StringTransformedEnum, **optimizer_enum_args)
+VALIDATION_METRIC_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(
     StringTransformedEnum, **validation_metric_enum_args
 )
 
@@ -128,6 +126,7 @@ class ImageModelDistributionSettingsSchema(metaclass=PatchedSchemaMeta):
     weight_decay = FLOAT_SEARCH_SPACE_DISTRIBUTION_FIELD
 
 
+# pylint: disable-next=name-too-long
 class ImageModelDistributionSettingsClassificationSchema(ImageModelDistributionSettingsSchema):
     model_name = STRING_SEARCH_SPACE_DISTRIBUTION_FIELD
     training_crop_size = INT_SEARCH_SPACE_DISTRIBUTION_FIELD
@@ -163,6 +162,7 @@ def make(self, data, **kwargs):
         return ImageClassificationSearchSpace(**data)
 
 
+# pylint: disable-next=name-too-long
 class ImageModelDistributionSettingsDetectionCommonSchema(ImageModelDistributionSettingsSchema):
     box_detections_per_image = INT_SEARCH_SPACE_DISTRIBUTION_FIELD
     box_score_threshold = FLOAT_SEARCH_SPACE_DISTRIBUTION_FIELD
@@ -206,9 +206,11 @@ def make(self, data, **kwargs):
         return ImageObjectDetectionSearchSpace(**data)
 
 
+# pylint: disable-next=name-too-long
 class ImageModelDistributionSettingsObjectDetectionSchema(ImageModelDistributionSettingsDetectionCommonSchema):
     model_name = STRING_SEARCH_SPACE_DISTRIBUTION_FIELD
 
 
+# pylint: disable-next=name-too-long
 class ImageModelDistributionSettingsInstanceSegmentationSchema(ImageModelDistributionSettingsObjectDetectionSchema):
     model_name = STRING_SEARCH_SPACE_DISTRIBUTION_FIELD

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/automl/nlp_vertical/nlp_parameter_subspace.py

@@ -26,23 +26,23 @@
 from azure.ai.ml._utils.utils import camel_to_snake
 
 
-def get_choice_schema_of_type(cls, **kwargs):
+def choice_schema_of_type(cls, **kwargs):
     class CustomChoiceSchema(ChoiceSchema):
         values = fields.List(cls(**kwargs))
 
     return CustomChoiceSchema()
 
 
-def get_choice_and_single_value_schema_of_type(cls, **kwargs):
-    return UnionField([cls(**kwargs), NestedField(get_choice_schema_of_type(cls, **kwargs))])
+def choice_and_single_value_schema_of_type(cls, **kwargs):
+    return UnionField([cls(**kwargs), NestedField(choice_schema_of_type(cls, **kwargs))])
 
 
 FLOAT_SEARCH_SPACE_DISTRIBUTION_FIELD = UnionField(
     [
         fields.Float(),
         DumpableIntegerField(strict=True),
-        NestedField(get_choice_schema_of_type(DumpableIntegerField, strict=True)),
-        NestedField(get_choice_schema_of_type(fields.Float)),
+        NestedField(choice_schema_of_type(DumpableIntegerField, strict=True)),
+        NestedField(choice_schema_of_type(fields.Float)),
         NestedField(UniformSchema()),
         NestedField(QUniformSchema()),
         NestedField(NormalSchema()),
@@ -54,19 +54,19 @@ def get_choice_and_single_value_schema_of_type(cls, **kwargs):
 INT_SEARCH_SPACE_DISTRIBUTION_FIELD = UnionField(
     [
         DumpableIntegerField(strict=True),
-        NestedField(get_choice_schema_of_type(DumpableIntegerField, strict=True)),
+        NestedField(choice_schema_of_type(DumpableIntegerField, strict=True)),
         NestedField(RandintSchema()),
     ]
 )
 
-STRING_SEARCH_SPACE_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(DumpableStringField)
-BOOL_SEARCH_SPACE_DISTRIBUTION_FIELD = get_choice_and_single_value_schema_of_type(fields.Bool)
+STRING_SEARCH_SPACE_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(DumpableStringField)
+BOOL_SEARCH_SPACE_DISTRIBUTION_FIELD = choice_and_single_value_schema_of_type(fields.Bool)
 
 
 class NlpParameterSubspaceSchema(metaclass=PatchedSchemaMeta):
     gradient_accumulation_steps = INT_SEARCH_SPACE_DISTRIBUTION_FIELD
     learning_rate = FLOAT_SEARCH_SPACE_DISTRIBUTION_FIELD
-    learning_rate_scheduler = get_choice_and_single_value_schema_of_type(
+    learning_rate_scheduler = choice_and_single_value_schema_of_type(
         StringTransformedEnum,
         allowed_values=[obj.value for obj in NlpLearningRateScheduler],
         casing_transform=camel_to_snake,

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/component/data_transfer_component.py

@@ -157,6 +157,7 @@ def make(self, data, **kwargs):
         )
 
 
+# pylint: disable-next=name-too-long
 class AnonymousDataTransferImportComponentSchema(AnonymousAssetSchema, DataTransferImportComponentSchema):
     """Anonymous data transfer import component schema.
 
@@ -179,6 +180,7 @@ def make(self, data, **kwargs):
         )
 
 
+# pylint: disable-next=name-too-long
 class AnonymousDataTransferExportComponentSchema(AnonymousAssetSchema, DataTransferExportComponentSchema):
     """Anonymous data transfer export component schema.
 

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/core/fields.py

@@ -39,7 +39,7 @@
     RESOURCE_ID_FORMAT,
     AzureMLResourceType,
 )
-from ...entities._job.pipeline._attr_dict import try_get_non_arbitrary_attr_for_potential_attr_dict
+from ...entities._job.pipeline._attr_dict import try_get_non_arbitrary_attr
 from ...exceptions import ValidationException
 from ..core.schema import PathAwareSchema
 
@@ -572,7 +572,7 @@ def _simplified_error_base_on_type(self, e, value, attr) -> Exception:
          * First Matched Error message if value has type and type matches atleast one field
         :rtype: Exception
         """
-        value_type = try_get_non_arbitrary_attr_for_potential_attr_dict(value, self.type_field_name)
+        value_type = try_get_non_arbitrary_attr(value, self.type_field_name)
         if value_type is None:
             # if value has no type field, raise original error
             return e
@@ -596,7 +596,7 @@ def _simplified_error_base_on_type(self, e, value, attr) -> Exception:
 
     def _serialize(self, value, attr, obj, **kwargs):
         union_fields = self._union_fields[:]
-        value_type = try_get_non_arbitrary_attr_for_potential_attr_dict(value, self.type_field_name)
+        value_type = try_get_non_arbitrary_attr(value, self.type_field_name)
         if value_type is not None and value_type in self.allowed_types:
             target_fields = self._type_sensitive_fields_dict[value_type]
             if len(target_fields) == 1:

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/monitoring/thresholds.py

@@ -76,6 +76,7 @@ def make(self, data, **kwargs):
         return PredictionDriftMetricThreshold(**data)
 
 
+# pylint: disable-next=name-too-long
 class FeatureAttributionDriftMetricThresholdSchema(MetricThresholdSchema):
     @post_load
     def make(self, data, **kwargs):

sdk/ml/azure-ai-ml/azure/ai/ml/_utils/_feature_store_utils.py

@@ -29,12 +29,12 @@
     from azure.ai.ml.operations._feature_store_entity_operations import FeatureStoreEntityOperations
 
 
-def read_feature_set_metadata_contents(*, path: str) -> Dict:
+def read_feature_set_metadata(*, path: str) -> Dict:
     metadata_path = str(Path(path, "FeatureSetSpec.yaml"))
     return load_yaml(metadata_path)
 
 
-def read_remote_feature_set_spec_metadata_contents(
+def read_remote_feature_set_spec_metadata(
     *,
     base_uri: str,
     datastore_operations: DatastoreOperations,

sdk/ml/azure-ai-ml/azure/ai/ml/_utils/utils.py

@@ -407,12 +407,6 @@ def dict_eq(dict1: Dict[str, Any], dict2: Dict[str, Any]) -> bool:
     return dict1 == dict2
 
 
-def get_http_response_and_deserialized_from_pipeline_response(
-    pipeline_response: Any, deserialized: Any
-) -> Tuple[Any, Any]:
-    return pipeline_response.http_response, deserialized
-
-
 def xor(a: Any, b: Any) -> bool:
     return bool(a) != bool(b)
 
@@ -765,7 +759,7 @@ def is_on_disk_cache_enabled():
     return os.getenv(AZUREML_DISABLE_ON_DISK_CACHE_ENV_VAR) not in ["True", "true", True]
 
 
-def is_concurrent_component_registration_enabled():
+def is_concurrent_component_registration_enabled():  # pylint: disable=name-too-long
     return os.getenv(AZUREML_DISABLE_CONCURRENT_COMPONENT_REGISTRATION) not in ["True", "true", True]
 
 

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_component/pipeline_component.py

@@ -27,7 +27,7 @@
 from azure.ai.ml.entities._job.automl.automl_job import AutoMLJob
 from azure.ai.ml.entities._job.pipeline._attr_dict import (
     has_attr_safe,
-    try_get_non_arbitrary_attr_for_potential_attr_dict,
+    try_get_non_arbitrary_attr,
 )
 from azure.ai.ml.entities._job.pipeline._pipeline_expression import PipelineExpression
 from azure.ai.ml.entities._validation import MutableValidationResult
@@ -210,7 +210,7 @@ def _get_input_binding_dict(self, node: BaseNode) -> Tuple[dict, dict]:
                     component_binding_input = component_binding_input.path
                 if is_data_binding_expression(component_binding_input, ["parent"]):
                     # data binding may have more than one PipelineInput now
-                    for pipeline_input_name in PipelineExpression.parse_pipeline_input_names_from_data_binding(
+                    for pipeline_input_name in PipelineExpression.parse_pipeline_inputs_from_data_binding(
                         component_binding_input
                     ):
                         if pipeline_input_name not in self.inputs:
@@ -370,11 +370,7 @@ def _check_ignored_keys(cls, obj):
             "settings": lambda val: val is not None and any(v is not None for v in val._to_dict().values()),
         }
         # Avoid new attr added by use `try_get_non...` instead of `hasattr` or `getattr` directly.
-        return [
-            k
-            for k, has_set in examine_mapping.items()
-            if has_set(try_get_non_arbitrary_attr_for_potential_attr_dict(obj, k))
-        ]
+        return [k for k, has_set in examine_mapping.items() if has_set(try_get_non_arbitrary_attr(obj, k))]
 
     def _get_telemetry_values(self, *args, **kwargs):
         telemetry_values = super()._get_telemetry_values()

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_endpoint/batch_endpoint.py

@@ -89,19 +89,19 @@ def _to_rest_batch_endpoint(self, location: str) -> BatchEndpointData:
         return BatchEndpointData(location=location, tags=self.tags, properties=batch_endpoint)
 
     @classmethod
-    def _from_rest_object(cls, endpoint: BatchEndpointData):  # pylint: disable=arguments-renamed
+    def _from_rest_object(cls, obj: BatchEndpointData) -> "BatchEndpoint":
         return BatchEndpoint(
-            id=endpoint.id,
-            name=endpoint.name,
-            tags=endpoint.tags,
-            properties=endpoint.properties.properties,
-            auth_mode=camel_to_snake(endpoint.properties.auth_mode),
-            description=endpoint.properties.description,
-            location=endpoint.location,
-            defaults=endpoint.properties.defaults,
-            provisioning_state=endpoint.properties.provisioning_state,
-            scoring_uri=endpoint.properties.scoring_uri,
-            openapi_uri=endpoint.properties.swagger_uri,
+            id=obj.id,
+            name=obj.name,
+            tags=obj.tags,
+            properties=obj.properties.properties,
+            auth_mode=camel_to_snake(obj.properties.auth_mode),
+            description=obj.properties.description,
+            location=obj.location,
+            defaults=obj.properties.defaults,
+            provisioning_state=obj.properties.provisioning_state,
+            scoring_uri=obj.properties.scoring_uri,
+            openapi_uri=obj.properties.swagger_uri,
         )
 
     def dump(

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_endpoint/endpoint.py

@@ -114,8 +114,9 @@ def provisioning_state(self) -> Optional[str]:
     def dump(self, dest: Optional[Union[str, PathLike, IO[AnyStr]]] = None, **kwargs) -> None:
         pass
 
+    @classmethod
     @abstractmethod
-    def _from_rest_object(self, obj: Any) -> Any:
+    def _from_rest_object(cls, obj: Any) -> Any:
         pass
 
     def _merge_with(self, other: "Endpoint") -> None: