infra: add single-instance, multi-process Horovod test for local GPU (#390)

Author: laurenyu

test/integration/local/test_horovod.py

@@ -23,25 +23,38 @@
 RESOURCE_PATH = os.path.join(os.path.dirname(__file__), '..', '..', 'resources')
 
 
+@pytest.mark.skip_cpu
+@pytest.mark.skip_generic
+def test_distributed_training_horovod_gpu(
+    sagemaker_local_session, image_uri, tmpdir, framework_version
+):
+    _test_distributed_training_horovod(
+        1, 2, sagemaker_local_session, image_uri, tmpdir, framework_version, 'local_gpu'
+    )
+
+
 @pytest.mark.skip_gpu
 @pytest.mark.skip_generic
-@pytest.mark.parametrize('instances, processes', [
-    [1, 2],
-    (2, 1),
-    (2, 2),
-    (5, 2)])
-def test_distributed_training_horovod_basic(instances,
-                                            processes,
-                                            sagemaker_local_session,
-                                            image_uri,
-                                            tmpdir,
-                                            framework_version):
+@pytest.mark.parametrize(
+    'instances, processes', [(1, 2), (2, 1), (2, 2), (5, 2)]
+)
+def test_distributed_training_horovod_cpu(
+    instances, processes, sagemaker_local_session, image_uri, tmpdir, framework_version
+):
+    _test_distributed_training_horovod(
+        instances, processes, sagemaker_local_session, image_uri, tmpdir, framework_version, 'local'
+    )
+
+
+def _test_distributed_training_horovod(
+    instances, processes, session, image_uri, tmpdir, framework_version, instance_type
+):
     output_path = 'file://%s' % tmpdir
     estimator = TensorFlow(
         entry_point=os.path.join(RESOURCE_PATH, 'hvdbasic', 'train_hvd_basic.py'),
         role='SageMakerRole',
-        train_instance_type='local',
-        sagemaker_session=sagemaker_local_session,
+        train_instance_type=instance_type,
+        sagemaker_session=session,
         train_instance_count=instances,
         image_name=image_uri,
         output_path=output_path,