Tag SageMaker docker image upload with current mlflow version (mlflow…

…#124)

The SageMaker deployment docker image should be tagged with the mlflow version used so one can track the correct image to use in deploy(). This PR uses the current mlflow version to tag the ECR image instead of "latest" for SageMaker docker image upload.

mlflow/sagemaker/__init__.py

@@ -13,7 +13,7 @@
 from mlflow.utils.logging_utils import eprint
 from mlflow.utils.file_utils import TempDir, _copy_project
 
-DEFAULT_IMAGE_NAME = "mlflow_sage"
+DEFAULT_IMAGE_NAME = "mlflow-pyfunc"
 
 _DOCKERFILE_TEMPLATE = """
 # Build an image that can serve pyfunc model in SageMaker
@@ -102,7 +102,7 @@ def build_image(name=DEFAULT_IMAGE_NAME, mlflow_home=None):
             eprint(x, end='')
 
 
-_full_template = "{account}.dkr.ecr.{region}.amazonaws.com/{image}:latest"
+_full_template = "{account}.dkr.ecr.{region}.amazonaws.com/{image}:{version}"
 
 
 def push_image_to_ecr(image=DEFAULT_IMAGE_NAME):
@@ -119,7 +119,8 @@ def push_image_to_ecr(image=DEFAULT_IMAGE_NAME):
     account = caller_id['Account']
     my_session = boto3.session.Session()
     region = my_session.region_name or "us-west-2"
-    fullname = _full_template.format(account=account, region=region, image=image)
+    fullname = _full_template.format(account=account, region=region, image=image, version=mlflow.version.VERSION)
+    eprint("Pushing docker image {image} to {repo}".format(image=image, repo=fullname))
     ecr_client = boto3.client('ecr')
     if not ecr_client.describe_repositories(repositoryNames=[image])['repositories']:
         ecr_client.create_repository(repositoryName=image)