fix: combo fix for internal components I

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

@@ -2,7 +2,7 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # ---------------------------------------------------------
 
-from marshmallow import fields, post_dump
+from marshmallow import fields, post_dump, INCLUDE, EXCLUDE
 
 from azure.ai.ml._schema import NestedField, StringTransformedEnum, UnionField
 from azure.ai.ml._schema.component.component import ComponentSchema
@@ -15,6 +15,7 @@
     InternalInputPortSchema,
     InternalOutputPortSchema,
     InternalParameterSchema,
+    InternalPrimitiveOutputSchema,
 )
 
 
@@ -42,6 +43,8 @@ def all_values(cls):
 
 
 class InternalBaseComponentSchema(ComponentSchema):
+    class Meta:
+        unknown = INCLUDE
     # override name as 1p components allow . in name, which is not allowed in v2 components
     name = fields.Str()
 
@@ -60,7 +63,16 @@ class InternalBaseComponentSchema(ComponentSchema):
             ]
         ),
     )
-    outputs = fields.Dict(keys=fields.Str(), values=NestedField(InternalOutputPortSchema))
+    # support primitive output for all internal components for now
+    outputs = fields.Dict(
+        keys=fields.Str(),
+        values=UnionField(
+            [
+                NestedField(InternalPrimitiveOutputSchema, unknown=EXCLUDE),
+                NestedField(InternalOutputPortSchema, unknown=EXCLUDE),
+            ]
+        ),
+    )
 
     # type field is required for registration
     type = StringTransformedEnum(

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/_schema/input_output.py

@@ -4,11 +4,22 @@
 
 from marshmallow import fields, post_dump, post_load
 
-from azure.ai.ml._schema import StringTransformedEnum, UnionField
-from azure.ai.ml._schema.component.input_output import InputPortSchema, OutputPortSchema, ParameterSchema
-from azure.ai.ml._schema.core.fields import DumpableFloatField, DumpableIntegerField
+from azure.ai.ml._schema import StringTransformedEnum, UnionField, PatchedSchemaMeta
+from azure.ai.ml._schema.component.input_output import InputPortSchema, ParameterSchema
+from azure.ai.ml._schema.core.fields import DumpableFloatField, DumpableIntegerField, DumpableEnumField
 
 
+SUPPORTED_INTERNAL_PARAM_TYPES = [
+    "integer",
+    "Integer",
+    "boolean",
+    "Boolean",
+    "string",
+    "String",
+    "float",
+    "Float",
+]
+
 class InternalInputPortSchema(InputPortSchema):
     # skip client-side validate for type enum & support list
     type = UnionField(
@@ -29,29 +40,29 @@ def resolve_list_type(self, data, original_data, **kwargs):  # pylint: disable=u
         return data
 
 
-class InternalOutputPortSchema(OutputPortSchema):
+class InternalOutputPortSchema(metaclass=PatchedSchemaMeta):
     # skip client-side validate for type enum
     type = fields.Str(
         required=True,
         data_key="type",
     )
+    description = fields.Str()
     is_link_mode = fields.Bool()
     datastore_mode = fields.Str()
 
 
+class InternalPrimitiveOutputSchema(metaclass=PatchedSchemaMeta):
+    type = DumpableEnumField(
+        allowed_values=SUPPORTED_INTERNAL_PARAM_TYPES,
+        required=True,
+    )
+    description = fields.Str()
+    is_control = fields.Bool()
+
+
 class InternalParameterSchema(ParameterSchema):
-    type = StringTransformedEnum(
-        allowed_values=[
-            "integer",
-            "Integer",
-            "boolean",
-            "Boolean",
-            "string",
-            "String",
-            "float",
-            "Float",
-        ],
-        casing_transform=lambda x: x,
+    type = DumpableEnumField(
+        allowed_values=SUPPORTED_INTERNAL_PARAM_TYPES,
         required=True,
         data_key="type",
     )

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/_schema/node.py

@@ -12,6 +12,8 @@
 
 
 class InternalBaseNodeSchema(BaseNodeSchema):
+    class Meta:
+        unknown = INCLUDE
     component = UnionField(
         [
             # for registry type assets
@@ -56,6 +58,7 @@ class ScopeSchema(InternalBaseNodeSchema):
 class HDInsightSchema(InternalBaseNodeSchema):
     type = StringTransformedEnum(allowed_values=[NodeType.HDI], casing_transform=lambda x: x)
 
+    compute_name = fields.Str()
     queue = fields.Str()
     driver_memory = fields.Str()
     driver_cores = fields.Int()

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/_util.py

@@ -17,6 +17,9 @@
     InternalComponent,
     Parallel,
     Scope,
+    DataTransfer,
+    Hemera,
+    Starlite,
 )
 from azure.ai.ml._schema import NestedField
 from azure.ai.ml.entities._component.component_factory import component_factory
@@ -57,6 +60,9 @@ def enable_internal_components_in_pipeline():
         _register_node(_type, InternalBaseNode, InternalBaseNodeSchema)
 
     # redo the registration for those with specific runsettings
+    _register_node(NodeType.DATA_TRANSFER, DataTransfer, InternalBaseNodeSchema)
+    _register_node(NodeType.HEMERA, Hemera, InternalBaseNodeSchema)
+    _register_node(NodeType.STARLITE, Starlite, InternalBaseNodeSchema)
     _register_node(NodeType.COMMAND, Command, CommandSchema)
     _register_node(NodeType.DISTRIBUTED, Distributed, DistributedSchema)
     _register_node(NodeType.SCOPE, Scope, ScopeSchema)

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/entities/_additional_includes.py

@@ -16,19 +16,34 @@
 
 class _AdditionalIncludes:
     def __init__(self, code_path: Union[None, str], yaml_path: str):
-        self._yaml_path = Path(yaml_path)
-        self._yaml_name = self._yaml_path.name
-        self._code_path = self._yaml_path.parent
-        if code_path is not None:
-            self._code_path = (self._code_path / code_path).resolve()
+        self.__yaml_path = Path(yaml_path)
+        self.__code_path = code_path
+
         self._tmp_code_path = None
-        self._additional_includes_file_path = self._yaml_path.with_suffix(f".{ADDITIONAL_INCLUDES_SUFFIX}")
         self._includes = None
         if self._additional_includes_file_path.is_file():
             with open(self._additional_includes_file_path, "r") as f:
                 lines = f.readlines()
                 self._includes = [line.strip() for line in lines if len(line.strip()) > 0]
 
+    @property
+    def _yaml_path(self) -> Path:
+        return self.__yaml_path
+
+    @property
+    def _code_path(self) -> Path:
+        if self.__code_path is not None:
+            return (self._yaml_path.parent / self.__code_path).resolve()
+        return self._yaml_path.parent
+
+    @property
+    def _yaml_name(self) -> str:
+        return self._yaml_path.name
+
+    @property
+    def _additional_includes_file_path(self) -> Path:
+        return self._yaml_path.with_suffix(f".{ADDITIONAL_INCLUDES_SUFFIX}")
+
     @property
     def code(self) -> Path:
         return self._tmp_code_path if self._tmp_code_path else self._code_path

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/entities/command.py

@@ -42,8 +42,6 @@ def compute(self) -> str:
     @compute.setter
     def compute(self, value: str):
         """Set the compute definition for the command."""
-        if value is not None and not isinstance(value, str):
-            raise ValueError(f"Failed in setting compute: only string is supported in DPv2 but got {type(value)}")
         self._compute = value
 
     @property
@@ -54,8 +52,6 @@ def environment(self) -> str:
     @environment.setter
     def environment(self, value: str):
         """Set the environment definition for the command."""
-        if value is not None and not isinstance(value, str):
-            raise ValueError(f"Failed in setting environment: only string is supported in DPv2 but got {type(value)}")
         self._environment = value
 
     @property

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/entities/component.py

@@ -5,6 +5,7 @@
 # disable redefined-builtin to use id/type as argument name
 from contextlib import contextmanager
 from typing import Dict, Union
+import os
 
 from marshmallow import INCLUDE, Schema
 
@@ -176,6 +177,21 @@ def _additional_includes(self):
     def _create_schema_for_validation(cls, context) -> Union[PathAwareSchema, Schema]:
         return InternalBaseComponentSchema(context=context)
 
+    def _validate(self, raise_error=False) -> MutableValidationResult:
+        if self._additional_includes is not None and self._additional_includes._validate().passed:
+            # update source path in case dependency file is in additional_includes
+            with self._resolve_local_code() as tmp_base_path:
+                origin_base_path, origin_source_path = self._base_path, self._source_path
+
+                try:
+                    self._base_path, self._source_path = \
+                        tmp_base_path, tmp_base_path / os.path.basename(self._source_path)
+                    return super()._validate(raise_error=raise_error)
+                finally:
+                    self._base_path, self._source_path = origin_base_path, origin_source_path
+
+        return super()._validate(raise_error=raise_error)
+
     def _customized_validate(self) -> MutableValidationResult:
         validation_result = super(InternalComponent, self)._customized_validate()
         if isinstance(self.environment, InternalEnvironment):
@@ -228,14 +244,3 @@ def _resolve_local_code(self):
 
     def __call__(self, *args, **kwargs) -> InternalBaseNode:  # pylint: disable=useless-super-delegation
         return super(InternalComponent, self).__call__(*args, **kwargs)
-
-    def _schema_validate(self) -> MutableValidationResult:
-        """Validate the resource with the schema.
-
-        return type: ValidationResult
-        """
-        result = super(InternalComponent, self)._schema_validate()
-        # skip unknown field warnings for internal components
-        # TODO: move this logic into base class
-        result._warnings = list(filter(lambda x: x.message != "Unknown field.", result._warnings))
-        return result

sdk/ml/azure-ai-ml/azure/ai/ml/_internal/entities/node.py

@@ -16,7 +16,6 @@
 from azure.ai.ml.entities._job.pipeline._io import NodeInput, NodeOutput, PipelineInput
 from azure.ai.ml.entities._util import convert_ordered_dict_to_dict
 
-from ...entities._validation import MutableValidationResult
 from .._schema.component import NodeType
 from ._input_outputs import InternalInput
 
@@ -95,17 +94,6 @@ def _to_job(self) -> Job:
     def _load_from_dict(cls, data: Dict, context: Dict, additional_message: str, **kwargs) -> "Job":
         raise RuntimeError("Internal components doesn't support load from dict")
 
-    def _schema_validate(self) -> MutableValidationResult:
-        """Validate the resource with the schema.
-
-        return type: ValidationResult
-        """
-        result = super(InternalBaseNode, self)._schema_validate()
-        # skip unknown field warnings for internal components
-        # TODO: move this logic into base class?
-        result._warnings = list(filter(lambda x: x.message != "Unknown field.", result._warnings))
-        return result
-
     @classmethod
     def _create_schema_for_validation(cls, context) -> Union[PathAwareSchema, Schema]:
         from .._schema.node import InternalBaseNodeSchema
@@ -176,6 +164,7 @@ def __init__(self, **kwargs):
         kwargs.pop("type", None)
         super(HDInsight, self).__init__(type=NodeType.HDI, **kwargs)
         self._init = True
+        self._compute_name: str = kwargs.pop("compute_name", None)
         self._queue: str = kwargs.pop("queue", None)
         self._driver_memory: str = kwargs.pop("driver_memory", None)
         self._driver_cores: int = kwargs.pop("driver_cores", None)
@@ -186,6 +175,15 @@ def __init__(self, **kwargs):
         self._hdinsight_spark_job_name: str = kwargs.pop("hdinsight_spark_job_name", None)
         self._init = False
 
+    @property
+    def compute_name(self) -> str:
+        """Name of the compute to be used."""
+        return self._compute_name
+
+    @compute_name.setter
+    def compute_name(self, value: str):
+        self._compute_name = value
+
     @property
     def queue(self) -> str:
         """The name of the YARN queue to which submitted."""
@@ -267,6 +265,7 @@ def hdinsight_spark_job_name(self, value: str):
     @classmethod
     def _picked_fields_from_dict_to_rest_object(cls) -> List[str]:
         return [
+            "compute_name",
             "queue",
             "driver_cores",
             "executor_memory",

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

@@ -38,7 +38,7 @@ class Meta:
         ],
         metadata={"description": "Provides the configuration for a distributed run."},
     )
-    # primitive output is only supported for command component
+    # primitive output is only supported for command component & pipeline component
     outputs = fields.Dict(
         keys=fields.Str(),
         values=UnionField(

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

@@ -51,16 +51,12 @@ class OutputPortSchema(metaclass=PatchedSchemaMeta):
     )
 
 
-class PrimitiveOutputSchema(metaclass=PatchedSchemaMeta):
+class PrimitiveOutputSchema(OutputPortSchema):
     type = DumpableEnumField(
         allowed_values=SUPPORTED_PARAM_TYPES,
         required=True,
     )
-    description = fields.Str()
     is_control = fields.Bool()
-    mode = DumpableEnumField(
-        allowed_values=SUPPORTED_INPUT_OUTPUT_MODES,
-    )
 
 
 class ParameterSchema(metaclass=PatchedSchemaMeta):

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

@@ -44,8 +44,10 @@ def __new__(cls, name, bases, dct):
         if meta is None:
             dct["Meta"] = PatchedMeta
         else:
-            dct["Meta"].unknown = RAISE
-            dct["Meta"].ordered = True
+            if not hasattr(meta, "unknown"):
+                dct["Meta"].unknown = RAISE
+            if not hasattr(meta, "ordered"):
+                dct["Meta"].ordered = True
 
         bases = bases + (PatchedBaseSchema,)
         klass = super().__new__(cls, name, bases, dct)

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/pipeline/pipeline_component.py

@@ -136,7 +136,7 @@ class PipelineComponentSchema(ComponentSchema):
     type = StringTransformedEnum(allowed_values=[NodeType.PIPELINE])
     jobs = PipelineJobsField()
 
-    # primitive output is only supported for command component
+    # primitive output is only supported for command component & pipeline component
     outputs = fields.Dict(
         keys=fields.Str(),
         values=UnionField(

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_load_functions.py

@@ -89,7 +89,7 @@ def load_common(
         return _load_common_raising_marshmallow_error(cls, yaml_dict, relative_origin, params_override, **kwargs)
     except ValidationError as e:
         if issubclass(cls, SchemaValidatableMixin):
-            validation_result = _ValidationResultBuilder.from_validation_error(e, relative_origin)
+            validation_result = _ValidationResultBuilder.from_validation_error(e, source_path=relative_origin)
             validation_result.try_raise(
                 # pylint: disable=protected-access
                 error_target=cls._get_validation_error_target(),
@@ -102,8 +102,7 @@ def load_common(
                 f"of type {type_str}, please specify the correct "
                 f"type in the 'type' property.",
             )
-        else:
-            raise e
+        raise e
 
 
 def _try_load_yaml_dict(source: Union[str, PathLike, IO[AnyStr]]) -> dict:

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_validate_funcs.py

@@ -30,7 +30,7 @@ def validate_common(cls, path, validate_func, params_override=None) -> Validatio
     except ValidationException as err:
         return _ValidationResultBuilder.from_single_message(err.message)
     except ValidationError as err:
-        return _ValidationResultBuilder.from_validation_error(err, path)
+        return _ValidationResultBuilder.from_validation_error(err, source_path=path)
 
 
 def validate_component(path, ml_client=None, params_override=None) -> ValidationResult: