Merge branch 'master' into master

Author: TEChopra1000

doc/requirements.txt

@@ -1,2 +1,3 @@
 sphinx==3.1.1
 sphinx-rtd-theme==0.5.0
+docutils==0.15.2

src/sagemaker/clarify.py

@@ -123,6 +123,7 @@ def __init__(
         content_type=None,
         content_template=None,
         custom_attributes=None,
+        accelerator_type=None,
     ):
         """Initializes a configuration of a model and the endpoint to be created for it.
 
@@ -151,6 +152,9 @@ def __init__(
                 Section 3.3.6. Field Value Components (
                 https://tools.ietf.org/html/rfc7230#section-3.2.6) of the Hypertext Transfer
                 Protocol (HTTP/1.1).
+            accelerator_type (str): The Elastic Inference accelerator type to deploy to the model
+                endpoint instance for making inferences to the model, see
+                https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html.
         """
         self.predictor_config = {
             "model_name": model_name,
@@ -178,9 +182,8 @@ def __init__(
                     f" Please include a placeholder $features."
                 )
             self.predictor_config["content_template"] = content_template
-
-        if custom_attributes is not None:
-            self.predictor_config["custom_attributes"] = custom_attributes
+        _set(custom_attributes, "custom_attributes", self.predictor_config)
+        _set(accelerator_type, "accelerator_type", self.predictor_config)
 
     def get_predictor_config(self):
         """Returns part of the predictor dictionary of the analysis config."""

tests/conftest.py

@@ -190,7 +190,7 @@ def pytorch_inference_py_version(pytorch_inference_version, request):
         return "py3"
 
 
-def _huggingface_pytorch_version(huggingface_vesion):
+def _huggingface_base_fm_version(huggingface_vesion, base_fw):
     config = image_uris.config_for_framework("huggingface")
     training_config = config.get("training")
     original_version = huggingface_vesion
@@ -200,21 +200,26 @@ def _huggingface_pytorch_version(huggingface_vesion):
         )
     version_config = training_config.get("versions").get(huggingface_vesion)
     for key in list(version_config.keys()):
-        if key.startswith("pytorch"):
-            pt_version = key[7:]
+        if key.startswith(base_fw):
+            base_fw_version = key[len(base_fw) :]
             if len(original_version.split(".")) == 2:
-                pt_version = ".".join(pt_version.split(".")[:-1])
-            return pt_version
+                base_fw_version = ".".join(base_fw_version.split(".")[:-1])
+            return base_fw_version
 
 
 @pytest.fixture(scope="module")
 def huggingface_pytorch_version(huggingface_training_version):
-    return _huggingface_pytorch_version(huggingface_training_version)
+    return _huggingface_base_fm_version(huggingface_training_version, "pytorch")
 
 
 @pytest.fixture(scope="module")
 def huggingface_pytorch_latest_version(huggingface_training_latest_version):
-    return _huggingface_pytorch_version(huggingface_training_latest_version)
+    return _huggingface_base_fm_version(huggingface_training_latest_version, "pytorch")
+
+
+@pytest.fixture(scope="module")
+def huggingface_tensorflow_latest_version(huggingface_training_latest_version):
+    return _huggingface_base_fm_version(huggingface_training_latest_version, "tensorflow")
 
 
 @pytest.fixture(scope="module")