Add search for training job and fix slow tests

src/smexperiments/api_types.py

@@ -272,6 +272,85 @@ def __init__(self, code=None, message=None, metric_index=None, **kwargs):
         super(BatchPutMetricsError, self).__init__(code=code, message=message, metric_index=metric_index, **kwargs)
 
 
+class TrainingJobSearchResult(_base_types.ApiObject):
+    """Summary model of an Training Job search result.
+
+    Attributes:
+        training_job_name (str): The name of the training job.
+        training_job_arn (str): The Amazon Resource Name (ARN) of the training job.
+        tuning_job_arn (str): The Amazon Resource Name (ARN) of the associated.
+        hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
+        labeling_job_arn (str): The Amazon Resource Name (ARN) of the labeling job.
+        autoML_job_arn (str): The Amazon Resource Name (ARN) of the job.
+        model_artifacts (dict): Information about the Amazon S3 location that is configured for storing model artifacts.
+        training_job_status (str): The status of the training job
+        hyper_parameters (dict): Algorithm-specific parameters.
+        algorithm_specification (dict): Information about the algorithm used for training, and algorithm metadata.
+        input_data_config (dict): An array of Channel objects that describes each data input channel.
+        output_data_config (dict): The S3 path where model artifacts that you configured when creating the job are
+        stored. Amazon SageMaker creates subfolders for model artifacts.
+        resource_config (dict): Resources, including ML compute instances and ML storage volumes, that are configured
+        for model training.
+        debug_hook_config (dict): Configuration information for the debug hook parameters, collection configuration,
+        and storage paths.
+        debug_rule_config (dict): Information about the debug rule configuration.
+    """
+
+    training_job_name = None
+    training_job_arn = None
+    tuning_job_arn = None
+    labeling_job_arn = None
+    autoML_job_arn = None
+    model_artifacts = None
+    training_job_status = None
+    hyper_parameters = None
+    algorithm_specification = None
+    input_data_config = None
+    output_data_config = None
+    resource_config = None
+    debug_hook_config = None
+    experiment_config = None
+    debug_rule_config = None
+
+    def __init__(
+        self,
+        training_job_arn=None,
+        training_job_name=None,
+        tuning_job_arn=None,
+        labeling_job_arn=None,
+        autoML_job_arn=None,
+        model_artifacts=None,
+        training_job_status=None,
+        hyper_parameters=None,
+        algorithm_specification=None,
+        input_data_config=None,
+        output_data_config=None,
+        resource_config=None,
+        debug_hook_config=None,
+        experiment_config=None,
+        debug_rule_config=None,
+        **kwargs
+    ):
+        super(TrainingJobSearchResult, self).__init__(
+            training_job_arn=training_job_arn,
+            training_job_name=training_job_name,
+            tuning_job_arn=tuning_job_arn,
+            labeling_job_arn=labeling_job_arn,
+            autoML_job_arn=autoML_job_arn,
+            model_artifacts=model_artifacts,
+            training_job_status=training_job_status,
+            hyper_parameters=hyper_parameters,
+            algorithm_specification=algorithm_specification,
+            input_data_config=input_data_config,
+            output_data_config=output_data_config,
+            resource_config=resource_config,
+            debug_hook_config=debug_hook_config,
+            experiment_config=experiment_config,
+            debug_rule_config=debug_rule_config,
+            **kwargs
+        )
+
+
 class ExperimentSearchResult(_base_types.ApiObject):
     """Summary model of an Experiment search result.
 
@@ -369,12 +448,6 @@ class TrialComponentSearchResult(_base_types.ApiObject):
     display_name = None
     source = None
     status = None
-    start_time = None
-    end_time = None
-    creation_time = None
-    created_by = None
-    last_modified_time = None
-    last_modified_by = None
     parameters = None
     input_artifacts = None
     output_artifacts = None
@@ -392,35 +465,27 @@ def __init__(
         display_name=None,
         source=None,
         status=None,
-        creation_time=None,
-        created_by=None,
-        last_modified_time=None,
-        last_modified_by=None,
         parameters=None,
         input_artifacts=None,
         output_artifacts=None,
         metrics=None,
         source_detail=None,
         tags=None,
         parents=None,
+        **kwargs
     ):
         super(TrialComponentSearchResult, self).__init__(
             trial_component_arn=trial_component_arn,
             trial_component_name=trial_component_name,
             display_name=display_name,
             source=source,
             status=status,
-            start_time=start_time,
-            end_time=end_time,
-            creation_time=creation_time,
-            created_by=created_by,
-            last_modified_by=last_modified_by,
-            last_modified_time=last_modified_time,
             parameters=parameters,
             input_artifacts=input_artifacts,
             output_artifacts=output_artifacts,
             metrics=metrics,
             source_detail=source_detail,
             tags=tags,
             parents=parents,
+            **kwargs
         )

src/smexperiments/training_job.py

@@ -0,0 +1,49 @@
+# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+
+"""Contains the SageMaker Training Job class."""
+from smexperiments import _base_types, api_types
+
+
+class TrainingJob(_base_types.Record):
+    @classmethod
+    def search(
+        cls, search_expression=None, sort_by=None, sort_order=None, max_results=None, sagemaker_boto_client=None,
+    ):
+        """
+        Search Training Job. Returns SearchResults in the account matching the search criteria.
+
+        Args:
+            search_expression: (dict, optional): A Boolean conditional statement. Resource objects
+                must satisfy this condition to be included in search results. You must provide at
+                least one subexpression, filter, or nested filter.
+            sort_by (str, optional): The name of the resource property used to sort the SearchResults.
+                The default is LastModifiedTime
+            sort_order (str, optional): How SearchResults are ordered. Valid values are Ascending or
+                Descending . The default is Descending .
+            max_results (int, optional): The maximum number of results to return in a SearchResponse.
+            sagemaker_boto_client (SageMaker.Client, optional): Boto3 client for SageMaker. If not
+                supplied, a default boto3 client will be used.
+
+        Returns:
+            collections.Iterator[SearchResult] : An iterator over search results matching the search criteria.
+        """
+        return super(TrainingJob, cls)._search(
+            search_resource="TrainingJob",
+            search_item_factory=api_types.TrainingJobSearchResult.from_boto,
+            search_expression=None if search_expression is None else search_expression.to_boto(),
+            sort_by=sort_by,
+            sort_order=sort_order,
+            max_results=max_results,
+            sagemaker_boto_client=sagemaker_boto_client,
+        )

tests/conftest.py

@@ -264,11 +264,7 @@ def training_job_name(sagemaker_boto_client, training_role_arn, docker_image, tr
                 "DataSource": {"S3DataSource": {"S3Uri": training_s3_uri, "S3DataType": "S3Prefix"}},
             }
         ],
-        AlgorithmSpecification={
-            "TrainingImage": docker_image,
-            "TrainingInputMode": "File",
-            "EnableSageMakerMetricsTimeSeries": True,
-        },
+        AlgorithmSpecification={"TrainingImage": docker_image, "TrainingInputMode": "File",},
         RoleArn=training_role_arn,
         ResourceConfig={"InstanceType": "ml.m5.large", "InstanceCount": 1, "VolumeSizeInGB": 10},
         StoppingCondition={"MaxRuntimeInSeconds": 900},

tests/integ/test_track_from_processing_job.py

@@ -20,12 +20,11 @@
 
 @pytest.mark.slow
 def test_track_from_processing_job(sagemaker_boto_client, processing_job_name):
-
     get_job = lambda: sagemaker_boto_client.describe_processing_job(ProcessingJobName=processing_job_name)
     processing_job = get_job()
 
     source_arn = processing_job["ProcessingJobArn"]
-    # wait_for_job(processing_job_name, get_job, "ProcessingJobStatus")
+    wait_for_job(processing_job_name, get_job, "ProcessingJobStatus")
 
     print(processing_job)
     if "ProcessingStartTime" in processing_job:

tests/integ/test_track_from_training_job.py

@@ -1,4 +1,4 @@
-# Copyright 019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"). You
 # may not use this file except in compliance with the License. A copy of
@@ -21,7 +21,6 @@
 
 @pytest.mark.slow
 def test_track_from_training_job(sagemaker_boto_client, training_job_name):
-    training_job_name = "smexperiments-integ-eca5c064-3a64-433e-a30a-2963338d71d8"
     get_job = lambda: sagemaker_boto_client.describe_training_job(TrainingJobName=training_job_name)
     tj = get_job()
     source_arn = tj["TrainingJobArn"]

tests/integ/test_training_job.py

@@ -0,0 +1,46 @@
+# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+import pytest
+
+from smexperiments.training_job import TrainingJob
+from smexperiments.search_expression import SearchExpression, Filter, Operator
+from tests.helpers import retry
+
+
+@pytest.mark.slow
+def test_search(sagemaker_boto_client, training_job_name, docker_image):
+    def validate():
+        training_job_searched = []
+        search_filter = Filter(name="TrainingJobName", operator=Operator.EQUALS, value=training_job_name)
+        search_expression = SearchExpression(filters=[search_filter])
+        for s in TrainingJob.search(
+            search_expression=search_expression, max_results=10, sagemaker_boto_client=sagemaker_boto_client,
+        ):
+            training_job_searched.append(s)
+
+        assert len(training_job_searched) == 1
+        assert training_job_searched[0].training_job_name == training_job_name
+        assert training_job_searched[0].input_data_config[0]["ChannelName"] == "train"
+        assert training_job_searched[0].algorithm_specification == {
+            "TrainingImage": docker_image,
+            "TrainingInputMode": "File",
+        }
+        assert training_job_searched[0].resource_config == {
+            "InstanceType": "ml.m5.large",
+            "InstanceCount": 1,
+            "VolumeSizeInGB": 10,
+        }
+        assert training_job_searched[0].stopping_condition == {"MaxRuntimeInSeconds": 900}
+        assert training_job_searched  # sanity test
+
+    retry(validate)

tests/unit/test_training_job.py

@@ -0,0 +1,55 @@
+# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+import pytest
+import unittest.mock
+
+from smexperiments import training_job, api_types
+
+
+@pytest.fixture
+def sagemaker_boto_client():
+    return unittest.mock.Mock()
+
+
+def test_search(sagemaker_boto_client):
+    sagemaker_boto_client.search.return_value = {
+        "Results": [
+            {
+                "TrainingJob": {
+                    "TrainingJobName": "training-1",
+                    "TrainingJobArn": "arn::training-1",
+                    "HyperParameters": {"learning_rate": "0.1"},
+                }
+            },
+            {
+                "TrainingJob": {
+                    "TrainingJobName": "training-2",
+                    "TrainingJobArn": "arn::training-2",
+                    "HyperParameters": {"learning_rate": "0.2"},
+                }
+            },
+        ]
+    }
+    expected = [
+        api_types.TrainingJobSearchResult(
+            training_job_name="training-1",
+            training_job_arn="arn::training-1",
+            hyper_parameters={"learning_rate": "0.1"},
+        ),
+        api_types.TrainingJobSearchResult(
+            training_job_name="training-2",
+            training_job_arn="arn::training-2",
+            hyper_parameters={"learning_rate": "0.2"},
+        ),
+    ]
+    assert expected == list(training_job.TrainingJob.search(sagemaker_boto_client=sagemaker_boto_client))