[ML] Pylint fixes for Sweep and Command jobs (Azure#26324)

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_sweep/search_space/normal.py

@@ -49,6 +49,6 @@ def make(self, data, **kwargs):
     def predump(self, data, **kwargs):
         from azure.ai.ml.sweep import QLogNormal, QNormal
 
-        if not (isinstance(data, QNormal) or isinstance(data, QLogNormal)):
+        if not isinstance(data, (QNormal, QLogNormal)):
             raise ValidationError("Cannot dump non-QNormal or non-QLogNormal object into QNormalSchema")
         return data

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_sweep/search_space/uniform.py

@@ -22,7 +22,7 @@ class UniformSchema(metaclass=PatchedSchemaMeta):
     def predump(self, data, **kwargs):
         from azure.ai.ml.sweep import LogUniform, Uniform
 
-        if not (isinstance(data, Uniform) or isinstance(data, LogUniform)):
+        if not isinstance(data, (Uniform, LogUniform)):
             raise ValidationError("Cannot dump non-Uniform or non-LogUniform object into UniformSchema")
         if data.type.lower() not in SearchSpace.UNIFORM_LOGUNIFORM:
             raise ValidationError(BASE_ERROR_MESSAGE + str(SearchSpace.UNIFORM_LOGUNIFORM))
@@ -51,6 +51,6 @@ def make(self, data, **kwargs):
     def predump(self, data, **kwargs):
         from azure.ai.ml.sweep import QLogUniform, QUniform
 
-        if not (isinstance(data, QUniform) or isinstance(data, QLogUniform)):
+        if not isinstance(data, (QUniform, QLogUniform)):
             raise ValidationError("Cannot dump non-QUniform or non-QLogUniform object into UniformSchema")
         return data

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/job/parameterized_command.py

@@ -17,6 +17,7 @@
 class ParameterizedCommandSchema(PathAwareSchema):
     command = fields.Str(
         metadata={
+            # pylint: disable=line-too-long
             "description": "The command run and the parameters passed. This string may contain place holders of inputs in {}. "
         },
         required=True,

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

@@ -130,7 +130,7 @@ def __init__(
         validate_attribute_type(attrs_to_check=locals(), attr_type_map=self._attr_type_map())
 
         # resolve normal dict to dict[str, JobService]
-        services = self._resolve_job_services(services)
+        services = _resolve_job_services(services)
         kwargs.pop("type", None)
         self._parameters = kwargs.pop("parameters", {})
         BaseNode.__init__(
@@ -221,7 +221,7 @@ def services(self) -> Dict:
 
     @services.setter
     def services(self, value: Dict):
-        self._services = self._resolve_job_services(value)
+        self._services = _resolve_job_services(value)
 
     @property
     def component(self) -> Union[str, CommandComponent]:
@@ -550,37 +550,6 @@ def _create_schema_for_validation(cls, context) -> Union[PathAwareSchema, Schema
 
         return CommandSchema(context=context)
 
-    def _resolve_job_services(self, services: dict) -> dict:
-        """Resolve normal dict to dict[str, JobService]"""
-        # pylint disable=no-self-use
-        if services is None:
-            return None
-        if not isinstance(services, dict):
-            msg = f"Services must be a dict, got {type(services)} instead."
-            raise ValidationException(
-                message=msg,
-                no_personal_data_message=msg,
-                target=ErrorTarget.COMMAND_JOB,
-                error_category=ErrorCategory.USER_ERROR,
-            )
-
-        result = {}
-        for name, service in services.items():
-            if isinstance(service, dict):
-                service = load_from_dict(JobServiceSchema, service, context={BASE_PATH_CONTEXT_KEY: "."})
-            elif not isinstance(service, JobService):
-                msg = (
-                    f"Service value for key {name!r} must be a dict or JobService object, got {type(service)} instead."
-                )
-                raise ValidationException(
-                    message=msg,
-                    no_personal_data_message=msg,
-                    target=ErrorTarget.COMMAND_JOB,
-                    error_category=ErrorCategory.USER_ERROR,
-                )
-            result[name] = service
-        return result
-
     def __call__(self, *args, **kwargs) -> "Command":
         """Call Command as a function will return a new instance each time."""
         if isinstance(self._component, Component):
@@ -618,3 +587,33 @@ def __call__(self, *args, **kwargs) -> "Command":
             target=ErrorTarget.COMMAND_JOB,
             error_type=ValidationErrorType.INVALID_VALUE,
         )
+
+
+def _resolve_job_services(services: dict) -> dict:
+    """Resolve normal dict to dict[str, JobService]"""
+    if services is None:
+        return None
+
+    if not isinstance(services, dict):
+        msg = f"Services must be a dict, got {type(services)} instead."
+        raise ValidationException(
+            message=msg,
+            no_personal_data_message=msg,
+            target=ErrorTarget.COMMAND_JOB,
+            error_category=ErrorCategory.USER_ERROR,
+        )
+
+    result = {}
+    for name, service in services.items():
+        if isinstance(service, dict):
+            service = load_from_dict(JobServiceSchema, service, context={BASE_PATH_CONTEXT_KEY: "."})
+        elif not isinstance(service, JobService):
+            msg = f"Service value for key {name!r} must be a dict or JobService object, got {type(service)} instead."
+            raise ValidationException(
+                message=msg,
+                no_personal_data_message=msg,
+                target=ErrorTarget.COMMAND_JOB,
+                error_category=ErrorCategory.USER_ERROR,
+            )
+        result[name] = service
+    return result

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/job_limits.py

@@ -37,6 +37,7 @@ class CommandJobLimits(JobLimits):
     """
 
     def __init__(self, *, timeout: int = None):
+        super().__init__()
         self.type = JobType.COMMAND
         self.timeout = timeout
 
@@ -76,6 +77,7 @@ def __init__(
         timeout: int = None,
         trial_timeout: int = None,
     ):
+        super().__init__()
         self.type = JobType.SWEEP
         self.max_concurrent_trials = max_concurrent_trials
         self.max_total_trials = max_total_trials

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/parameterized_command.py

@@ -49,7 +49,7 @@ def __init__(
         code: str = None,
         environment_variables: Dict = None,
         distribution: Union[dict, MpiDistribution, TensorFlowDistribution, PyTorchDistribution] = None,
-        environment: Union["Environment", str] = None,
+        environment: Union[Environment, str] = None,
         **kwargs,
     ):
         super().__init__(**kwargs)

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/sweep/early_termination_policy.py

@@ -32,13 +32,13 @@ def _from_rest_object(cls, obj: RestEarlyTerminationPolicy) -> "EarlyTermination
 
         policy = None
         if obj.policy_type == EarlyTerminationPolicyType.BANDIT:
-            policy = BanditPolicy._from_rest_object(obj)
+            policy = BanditPolicy._from_rest_object(obj)  # pylint: disable=protected-access
 
         if obj.policy_type == EarlyTerminationPolicyType.MEDIAN_STOPPING:
-            policy = MedianStoppingPolicy._from_rest_object(obj)
+            policy = MedianStoppingPolicy._from_rest_object(obj)  # pylint: disable=protected-access
 
         if obj.policy_type == EarlyTerminationPolicyType.TRUNCATION_SELECTION:
-            policy = TruncationSelectionPolicy._from_rest_object(obj)
+            policy = TruncationSelectionPolicy._from_rest_object(obj)  # pylint: disable=protected-access
 
         return policy
 

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/sweep/parameterized_sweep.py

@@ -1,7 +1,7 @@
 # ---------------------------------------------------------
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # ---------------------------------------------------------
-from typing import Callable, Dict, Optional, Union
+from typing import Dict, Optional, Type, Union
 
 from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException
 
@@ -27,16 +27,18 @@
 )
 from .search_space import SweepDistribution
 
-SAMPLING_ALGORITHM_TO_REST_CONSTRUCTOR: Dict[SamplingAlgorithmType, Callable[[], RestSamplingAlgorithm]] = {
-    SamplingAlgorithmType.RANDOM: lambda: RestRandomSamplingAlgorithm(),
-    SamplingAlgorithmType.GRID: lambda: RestGridSamplingAlgorithm(),
-    SamplingAlgorithmType.BAYESIAN: lambda: RestBayesianSamplingAlgorithm(),
+# pylint: disable=unnecessary-lambda
+SAMPLING_ALGORITHM_TO_REST_CONSTRUCTOR: Dict[SamplingAlgorithmType, Type[RestSamplingAlgorithm]] = {
+    SamplingAlgorithmType.RANDOM: RestRandomSamplingAlgorithm,
+    SamplingAlgorithmType.GRID: RestGridSamplingAlgorithm,
+    SamplingAlgorithmType.BAYESIAN: RestBayesianSamplingAlgorithm,
 }
 
-SAMPLING_ALGORITHM_CONSTRUCTOR: Dict[SamplingAlgorithmType, Callable[[], SamplingAlgorithm]] = {
-    SamplingAlgorithmType.RANDOM: lambda: RandomSamplingAlgorithm(),
-    SamplingAlgorithmType.GRID: lambda: GridSamplingAlgorithm(),
-    SamplingAlgorithmType.BAYESIAN: lambda: BayesianSamplingAlgorithm(),
+# pylint: disable=unnecessary-lambda
+SAMPLING_ALGORITHM_CONSTRUCTOR: Dict[SamplingAlgorithmType, Type[SamplingAlgorithm]] = {
+    SamplingAlgorithmType.RANDOM: RandomSamplingAlgorithm,
+    SamplingAlgorithmType.GRID: GridSamplingAlgorithm,
+    SamplingAlgorithmType.BAYESIAN: BayesianSamplingAlgorithm,
 }
 
 
@@ -158,11 +160,13 @@ def sampling_algorithm(self, value: Optional[Union[SamplingAlgorithm, str]] = No
     def _get_rest_sampling_algorithm(self) -> RestSamplingAlgorithm:
         # TODO: self.sampling_algorithm will always return SamplingAlgorithm
         if isinstance(self.sampling_algorithm, SamplingAlgorithm):
-            return self.sampling_algorithm._to_rest_object()
-        elif isinstance(self.sampling_algorithm, str):
-            return SAMPLING_ALGORITHM_CONSTRUCTOR[
+            return self.sampling_algorithm._to_rest_object()  # pylint: disable=protected-access
+
+        if isinstance(self.sampling_algorithm, str):
+            return SAMPLING_ALGORITHM_CONSTRUCTOR[  # pylint: disable=protected-access
                 SamplingAlgorithmType(self.sampling_algorithm.lower().capitalize())
             ]()._to_rest_object()
+
         msg = f"Received unsupported value {self._sampling_algorithm} as the sampling algorithm"
         raise ValidationException(
             message=msg,
@@ -208,6 +212,3 @@ def early_termination(self, value: Union[EarlyTerminationPolicy, str]):
                 error_category=ErrorCategory.USER_ERROR,
                 error_type=ValidationErrorType.INVALID_VALUE,
             )
-
-    def _override_missing_properties_from_trial(self):
-        return

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/sweep/sampling_algorithm.py

@@ -24,13 +24,13 @@ def _from_rest_object(cls, obj: RestSamplingAlgorithm) -> "SamplingAlgorithm":
 
         sampling_algorithm = None
         if obj.sampling_algorithm_type == SamplingAlgorithmType.RANDOM:
-            sampling_algorithm = RandomSamplingAlgorithm._from_rest_object(obj)
+            sampling_algorithm = RandomSamplingAlgorithm._from_rest_object(obj)  # pylint: disable=protected-access
 
         if obj.sampling_algorithm_type == SamplingAlgorithmType.GRID:
-            sampling_algorithm = GridSamplingAlgorithm._from_rest_object(obj)
+            sampling_algorithm = GridSamplingAlgorithm._from_rest_object(obj)  # pylint: disable=protected-access
 
         if obj.sampling_algorithm_type == SamplingAlgorithmType.BAYESIAN:
-            sampling_algorithm = BayesianSamplingAlgorithm._from_rest_object(obj)
+            sampling_algorithm = BayesianSamplingAlgorithm._from_rest_object(obj)  # pylint: disable=protected-access
 
         return sampling_algorithm
 
@@ -42,6 +42,7 @@ def __init__(
         rule=None,
         seed=None,
     ) -> None:
+        super().__init__()
         self.type = SamplingAlgorithmType.RANDOM.lower()
         self.rule = rule
         self.seed = seed
@@ -62,6 +63,7 @@ def _from_rest_object(cls, obj: RestRandomSamplingAlgorithm) -> "RandomSamplingA
 
 class GridSamplingAlgorithm(SamplingAlgorithm):
     def __init__(self) -> None:
+        super().__init__()
         self.type = SamplingAlgorithmType.GRID.lower()
 
     # pylint: disable=no-self-use
@@ -76,6 +78,7 @@ def _from_rest_object(cls, obj: RestGridSamplingAlgorithm) -> "GridSamplingAlgor
 
 class BayesianSamplingAlgorithm(SamplingAlgorithm):
     def __init__(self):
+        super().__init__()
         self.type = SamplingAlgorithmType.BAYESIAN.lower()
 
     # pylint: disable=no-self-use

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/sweep/search_space.py

@@ -14,11 +14,11 @@
 
 
 class SweepDistribution(ABC, RestTranslatableMixin):
-    def __init__(self, *, type: str = None):
+    def __init__(self, *, type: str = None):  # pylint: disable=redefined-builtin
         self.type = type
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "SweepDistribution":
+    def _from_rest_object(cls, obj: List) -> "SweepDistribution":
 
         mapping = {
             SearchSpace.CHOICE: Choice,
@@ -33,17 +33,17 @@ def _from_rest_object(cls, rest: List) -> "SweepDistribution":
             SearchSpace.QLOGUNIFORM: QLogUniform,
         }
 
-        ss_class = mapping.get(rest[0], None)
+        ss_class = mapping.get(obj[0], None)
         if ss_class:
-            return ss_class._from_rest_object(rest)
-        else:
-            msg = f"Unknown search space type: {rest[0]}"
-            raise JobException(
-                message=msg,
-                no_personal_data_message=msg,
-                target=ErrorTarget.SWEEP_JOB,
-                error_category=ErrorCategory.SYSTEM_ERROR,
-            )
+            return ss_class._from_rest_object(obj)
+
+        msg = f"Unknown search space type: {obj[0]}"
+        raise JobException(
+            message=msg,
+            no_personal_data_message=msg,
+            target=ErrorTarget.SWEEP_JOB,
+            error_category=ErrorCategory.SYSTEM_ERROR,
+        )
 
     def __eq__(self, other: object) -> bool:
         if not isinstance(other, SweepDistribution):
@@ -73,8 +73,8 @@ def _to_rest_object(self) -> List:
         return [self.type, [items]]
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "Choice":
-        rest_values = rest[1][0]
+    def _from_rest_object(cls, obj: List) -> "Choice":
+        rest_values = obj[1][0]
         from_rest_values = []
         for rest_value in rest_values:
             if isinstance(rest_value, dict):
@@ -84,7 +84,7 @@ def _from_rest_object(cls, rest: List) -> "Choice":
                         # first assume that any dictionary value is a valid distribution (i.e. normal, uniform, etc)
                         # and try to deserialize it into a the correct SDK distribution object
                         from_rest_dict[k] = SweepDistribution._from_rest_object(v)
-                    except Exception:
+                    except Exception:  # pylint: disable=broad-except
                         # if an exception is raised, assume that the value was not a valid distribution and use the
                         # value as it is for deserialization
                         from_rest_dict[k] = v
@@ -105,8 +105,8 @@ def _to_rest_object(self) -> List:
         return [self.type, [self.mu, self.sigma]]
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "Normal":
-        return cls(mu=rest[1][0], sigma=rest[1][1])
+    def _from_rest_object(cls, obj: List) -> "Normal":
+        return cls(mu=obj[1][0], sigma=obj[1][1])
 
 
 class LogNormal(Normal):
@@ -125,8 +125,8 @@ def _to_rest_object(self) -> List:
         return [self.type, [self.mu, self.sigma, self.q]]
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "QNormal":
-        return cls(mu=rest[1][0], sigma=rest[1][1], q=rest[1][2])
+    def _from_rest_object(cls, obj: List) -> "QNormal":
+        return cls(mu=obj[1][0], sigma=obj[1][1], q=obj[1][2])
 
 
 class QLogNormal(QNormal):
@@ -145,8 +145,8 @@ def _to_rest_object(self) -> List:
         return [self.type, [self.upper]]
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "Randint":
-        return cls(upper=rest[1][0])
+    def _from_rest_object(cls, obj: List) -> "Randint":
+        return cls(upper=obj[1][0])
 
 
 class Uniform(SweepDistribution):
@@ -160,8 +160,8 @@ def _to_rest_object(self) -> List:
         return [self.type, [self.min_value, self.max_value]]
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "Uniform":
-        return cls(min_value=rest[1][0], max_value=rest[1][1])
+    def _from_rest_object(cls, obj: List) -> "Uniform":
+        return cls(min_value=obj[1][0], max_value=obj[1][1])
 
 
 class LogUniform(Uniform):
@@ -186,8 +186,8 @@ def _to_rest_object(self) -> List:
         return [self.type, [self.min_value, self.max_value, self.q]]
 
     @classmethod
-    def _from_rest_object(cls, rest: List) -> "QUniform":
-        return cls(min_value=rest[1][0], max_value=rest[1][1], q=rest[1][2])
+    def _from_rest_object(cls, obj: List) -> "QUniform":
+        return cls(min_value=obj[1][0], max_value=obj[1][1], q=obj[1][2])
 
 
 class QLogUniform(QUniform):