use unique_name_from_base for Chainer integ tests

Author: laurenyu

tests/integ/test_chainer_train.py

@@ -1,4 +1,4 @@
-# Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# Copyright 2017-2019 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 +21,7 @@
 from sagemaker.chainer.defaults import CHAINER_VERSION
 from sagemaker.chainer.estimator import Chainer
 from sagemaker.chainer.model import ChainerModel
-from sagemaker.utils import sagemaker_timestamp
+from sagemaker.utils import unique_name_from_base
 import tests.integ
 from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
 from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
@@ -62,14 +62,15 @@ def test_training_with_additional_hyperparameters(sagemaker_session, chainer_ful
         test_input = chainer.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
                                                            key_prefix='integ-test-data/chainer_mnist/test')
 
-        chainer.fit({'train': train_input, 'test': test_input})
+        job_name = unique_name_from_base('test-chainer-training')
+        chainer.fit({'train': train_input, 'test': test_input}, job_name=job_name)
         return chainer.latest_training_job.name
 
 
 @pytest.mark.canary_quick
 @pytest.mark.regional_testing
 def test_attach_deploy(chainer_training_job, sagemaker_session):
-    endpoint_name = 'test-chainer-attach-deploy-{}'.format(sagemaker_timestamp())
+    endpoint_name = unique_name_from_base('test-chainer-attach-deploy')
 
     with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
         estimator = Chainer.attach(chainer_training_job, sagemaker_session=sagemaker_session)
@@ -78,7 +79,7 @@ def test_attach_deploy(chainer_training_job, sagemaker_session):
 
 
 def test_deploy_model(chainer_training_job, sagemaker_session):
-    endpoint_name = 'test-chainer-deploy-model-{}'.format(sagemaker_timestamp())
+    endpoint_name = unique_name_from_base('test-chainer-deploy-model')
     with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
         desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=chainer_training_job)
         model_data = desc['ModelArtifacts']['S3ModelArtifacts']
@@ -89,15 +90,14 @@ def test_deploy_model(chainer_training_job, sagemaker_session):
 
 
 def test_async_fit(sagemaker_session):
-    endpoint_name = 'test-chainer-attach-deploy-{}'.format(sagemaker_timestamp())
-
     with timeout(minutes=5):
         training_job_name = _run_mnist_training_job(sagemaker_session, "ml.c4.xlarge", 1,
                                                     chainer_full_version=CHAINER_VERSION, wait=False)
 
         print("Waiting to re-attach to the training job: %s" % training_job_name)
         time.sleep(20)
 
+    endpoint_name = unique_name_from_base('test-chainer-async-fit')
     with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
         print("Re-attaching now to: %s" % training_job_name)
         estimator = Chainer.attach(training_job_name=training_job_name, sagemaker_session=sagemaker_session)
@@ -115,7 +115,7 @@ def test_failed_training_job(sagemaker_session, chainer_full_version):
                           sagemaker_session=sagemaker_session)
 
         with pytest.raises(ValueError) as e:
-            chainer.fit()
+            chainer.fit(job_name=unique_name_from_base('test-chainer-training'))
         assert 'ExecuteUserScriptError' in str(e.value)
 
 
@@ -138,7 +138,8 @@ def _run_mnist_training_job(sagemaker_session, instance_type, instance_count,
         test_input = chainer.sagemaker_session.upload_data(path=os.path.join(data_path, 'test'),
                                                            key_prefix='integ-test-data/chainer_mnist/test')
 
-        chainer.fit({'train': train_input, 'test': test_input}, wait=wait)
+        job_name = unique_name_from_base('test-chainer-training')
+        chainer.fit({'train': train_input, 'test': test_input}, wait=wait, job_name=job_name)
         return chainer.latest_training_job.name