Remove InfSpec from branch

Author: Bryannah Hernandez

src/sagemaker/serve/model_server/multi_model_server/inference.py

@@ -92,13 +92,7 @@ def _start_serving(
                     "mode": "rw",
                 },
             },
-            environment={
-                "SAGEMAKER_SUBMIT_DIRECTORY": "/opt/ml/model/code",
-                "SAGEMAKER_PROGRAM": "inference.py",
-                "SAGEMAKER_SERVE_SECRET_KEY": secret_key,
-                "LOCAL_PYTHON": platform.python_version(),
-                **env_vars,
-            },
+            environment=_update_env_vars(env_vars),
         )
 
     def _invoke_multi_model_server_serving(self, request: object, content_type: str, accept: str):
@@ -173,14 +167,6 @@ def _upload_server_artifacts(
             }
         }
 
-        env_vars = {
-            "SAGEMAKER_SUBMIT_DIRECTORY": "/opt/ml/model/code",
-            "SAGEMAKER_PROGRAM": "inference.py",
-            "SAGEMAKER_REGION": sagemaker_session.boto_region_name,
-            "SAGEMAKER_CONTAINER_LOG_LEVEL": "10",
-            "LOCAL_PYTHON": platform.python_version(),
-        }
-
         return model_data, _update_env_vars(env_vars)
 
 

src/sagemaker/serve/model_server/multi_model_server/server.py

@@ -12,64 +12,13 @@
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
 
-from pathlib import PosixPath
-import platform
 from unittest import TestCase
 from unittest.mock import Mock, patch
 
-import numpy as np
-
 from sagemaker.serve.model_server.multi_model_server.prepare import _create_dir_structure
 
-from sagemaker.serve.model_server.multi_model_server.server import (
-    LocalMultiModelServer,
-)
-
-CPU_TF_IMAGE = "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:2.0.0-transformers4.28.1-cpu-py310-ubuntu20.04"
-MODEL_PATH = "model_path"
-MODEL_REPO = f"{MODEL_PATH}/1"
-ENV_VAR = {"KEY": "VALUE"}
-PAYLOAD = np.random.rand(3, 4).astype(dtype=np.float32)
-DTYPE = "TYPE_FP32"
-SECRET_KEY = "secret_key"
-INFER_RESPONSE = {"outputs": [{"name": "output_name"}]}
-
 
 class MultiModelServerPrepareTests(TestCase):
-    def test_start_invoke_destroy_local_multi_model_server(self):
-        mock_container = Mock()
-        mock_docker_client = Mock()
-        mock_docker_client.containers.run.return_value = mock_container
-
-        local_multi_model_server = LocalMultiModelServer()
-        mock_schema_builder = Mock()
-        mock_schema_builder.input_serializer.serialize.return_value = PAYLOAD
-        local_multi_model_server.schema_builder = mock_schema_builder
-
-        local_multi_model_server._start_serving(
-            client=mock_docker_client,
-            model_path=MODEL_PATH,
-            secret_key=SECRET_KEY,
-            env_vars=ENV_VAR,
-            image=CPU_TF_IMAGE,
-        )
-
-        mock_docker_client.containers.run.assert_called_once_with(
-            CPU_TF_IMAGE,
-            "serve",
-            detach=True,
-            auto_remove=True,
-            network_mode="host",
-            volumes={PosixPath("model_path"): {"bind": "/opt/ml/model", "mode": "rw"}},
-            environment={
-                "SAGEMAKER_SUBMIT_DIRECTORY": "/opt/ml/model/code",
-                "SAGEMAKER_PROGRAM": "inference.py",
-                "SAGEMAKER_SERVE_SECRET_KEY": "secret_key",
-                "LOCAL_PYTHON": platform.python_version(),
-                "KEY": "VALUE",
-            },
-        )
-
     @patch("sagemaker.serve.model_server.multi_model_server.prepare._check_disk_space")
     @patch("sagemaker.serve.model_server.multi_model_server.prepare._check_docker_disk_usage")
     @patch("sagemaker.serve.model_server.multi_model_server.prepare.Path")
@@ -102,3 +51,4 @@ def test_create_dir_structure_invalid_path(self, mock_path):
             _create_dir_structure(mock_model_path)
 
         self.assertEquals("model_dir is not a valid directory", str(context.exception))
+