two version of R2R are here HEAD master

1 files changed, 170 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_job/parameterized_command.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_job/parameterized_command.py
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+# ---------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# ---------------------------------------------------------
+
+# pylint: disable=protected-access
+
+import logging
+import os
+from typing import Dict, Optional, Union
+
+from marshmallow import INCLUDE
+
+from azure.ai.ml._restclient.v2023_04_01_preview.models import SweepJob
+from azure.ai.ml._schema.core.fields import ExperimentalField
+from azure.ai.ml.entities._assets import Environment
+
+from ..._schema import NestedField, UnionField
+from ..._schema.job.distribution import (
+    MPIDistributionSchema,
+    PyTorchDistributionSchema,
+    RayDistributionSchema,
+    TensorFlowDistributionSchema,
+)
+from .distribution import (
+    DistributionConfiguration,
+    MpiDistribution,
+    PyTorchDistribution,
+    RayDistribution,
+    TensorFlowDistribution,
+)
+from .job_resource_configuration import JobResourceConfiguration
+from .queue_settings import QueueSettings
+
+module_logger = logging.getLogger(__name__)
+
+# no reference found. leave it for future use.
+INPUT_BINDING_PREFIX = "AZURE_ML_INPUT_"
+OLD_INPUT_BINDING_PREFIX = "AZURE_ML_INPUT"
+
+
+class ParameterizedCommand:
+    """Command component version that contains the command and supporting parameters for a Command component
+    or job.
+
+    This class should not be instantiated directly. Instead, use the child class
+    ~azure.ai.ml.entities.CommandComponent.
+
+    :param command: The command to be executed. Defaults to "".
+    :type command: str
+    :param resources: The compute resource configuration for the command.
+    :type resources: Optional[Union[dict, ~azure.ai.ml.entities.JobResourceConfiguration]]
+    :param code: The source code to run the job. Can be a local path or "http:", "https:", or "azureml:" url pointing
+        to a remote location.
+    :type code: Optional[str]
+    :param environment_variables: A dictionary of environment variable names and values.
+        These environment variables are set on the process where user script is being executed.
+    :type environment_variables: Optional[dict[str, str]]
+    :param distribution: The distribution configuration for distributed jobs.
+    :type distribution: Optional[Union[dict, ~azure.ai.ml.PyTorchDistribution, ~azure.ai.ml.MpiDistribution,
+        ~azure.ai.ml.TensorFlowDistribution, ~azure.ai.ml.RayDistribution]]
+    :param environment: The environment that the job will run in.
+    :type environment: Optional[Union[str, ~azure.ai.ml.entities.Environment]]
+    :param queue_settings: The queue settings for the job.
+    :type queue_settings: Optional[~azure.ai.ml.entities.QueueSettings]
+    :keyword kwargs: A dictionary of additional configuration parameters.
+    :paramtype kwargs: dict
+    """
+
+    def __init__(
+        self,
+        command: Optional[str] = "",
+        resources: Optional[Union[dict, JobResourceConfiguration]] = None,
+        code: Optional[Union[str, os.PathLike]] = None,
+        environment_variables: Optional[Dict] = None,
+        distribution: Optional[
+            Union[
+                Dict,
+                MpiDistribution,
+                TensorFlowDistribution,
+                PyTorchDistribution,
+                RayDistribution,
+                DistributionConfiguration,
+            ]
+        ] = None,
+        environment: Optional[Union[Environment, str]] = None,
+        queue_settings: Optional[QueueSettings] = None,
+        **kwargs: Dict,
+    ) -> None:
+        super().__init__(**kwargs)
+        self.command = command
+        self.code = code
+        self.environment_variables = dict(environment_variables) if environment_variables else {}
+        self.environment = environment
+        self.distribution = distribution
+        self.resources = resources  # type: ignore[assignment]
+        self.queue_settings = queue_settings
+
+    @property
+    def distribution(
+        self,
+    ) -> Optional[
+        Union[
+            dict,
+            MpiDistribution,
+            TensorFlowDistribution,
+            PyTorchDistribution,
+            RayDistribution,
+            DistributionConfiguration,
+        ]
+    ]:
+        """The configuration for the distributed command component or job.
+
+        :return: The distribution configuration.
+        :rtype: Union[~azure.ai.ml.PyTorchDistribution, ~azure.ai.ml.MpiDistribution,
+            ~azure.ai.ml.TensorFlowDistribution, ~azure.ai.ml.RayDistribution]
+        """
+        return self._distribution
+
+    @distribution.setter
+    def distribution(self, value: Union[dict, PyTorchDistribution, MpiDistribution]) -> None:
+        """Sets the configuration for the distributed command component or job.
+
+        :param value: The distribution configuration for distributed jobs.
+        :type value: Union[dict, ~azure.ai.ml.PyTorchDistribution, ~azure.ai.ml.MpiDistribution,
+            ~azure.ai.ml.TensorFlowDistribution, ~azure.ai.ml.RayDistribution]
+        """
+        if isinstance(value, dict):
+            dist_schema = UnionField(
+                [
+                    NestedField(PyTorchDistributionSchema, unknown=INCLUDE),
+                    NestedField(TensorFlowDistributionSchema, unknown=INCLUDE),
+                    NestedField(MPIDistributionSchema, unknown=INCLUDE),
+                    ExperimentalField(NestedField(RayDistributionSchema, unknown=INCLUDE)),
+                ]
+            )
+            value = dist_schema._deserialize(value=value, attr=None, data=None)
+        self._distribution = value
+
+    @property
+    def resources(self) -> JobResourceConfiguration:
+        """The compute resource configuration for the command component or job.
+
+        :return: The compute resource configuration for the command component or job.
+        :rtype: ~azure.ai.ml.entities.JobResourceConfiguration
+        """
+        return self._resources
+
+    @resources.setter
+    def resources(self, value: Union[dict, JobResourceConfiguration]) -> None:
+        """Sets the compute resource configuration for the command component or job.
+
+        :param value: The compute resource configuration for the command component or job.
+        :type value: Union[dict, ~azure.ai.ml.entities.JobResourceConfiguration]
+        """
+        if isinstance(value, dict):
+            value = JobResourceConfiguration(**value)
+        self._resources = value
+
+    @classmethod
+    def _load_from_sweep_job(cls, sweep_job: SweepJob) -> "ParameterizedCommand":
+        parameterized_command = cls(
+            command=sweep_job.trial.command,
+            code=sweep_job.trial.code_id,
+            environment_variables=sweep_job.trial.environment_variables,
+            environment=sweep_job.trial.environment_id,
+            distribution=DistributionConfiguration._from_rest_object(sweep_job.trial.distribution),
+            resources=JobResourceConfiguration._from_rest_object(sweep_job.trial.resources),
+            queue_settings=QueueSettings._from_rest_object(sweep_job.queue_settings),
+        )
+        return parameterized_command