Fix: Updated js mb compression logic - ModelBuilder (aws#4294)

Co-authored-by: EC2 Default User <ec2-user@ip-172-16-54-104.us-west-2.compute.internal>

src/sagemaker/serve/builder/jumpstart_builder.py

@@ -95,6 +95,7 @@ def _is_jumpstart_model_id(self) -> bool:
     def _create_pre_trained_js_model(self) -> Type[Model]:
         """Placeholder docstring"""
         pysdk_model = JumpStartModel(self.model)
+        pysdk_model.sagemaker_session = self.sagemaker_session
 
         self._original_deploy = pysdk_model.deploy
         pysdk_model.deploy = self._js_builder_deploy_wrapper

src/sagemaker/serve/builder/tgi_builder.py

@@ -133,7 +133,10 @@ def _create_tgi_model(self) -> Type[Model]:
             logger.info("Auto detected %s. Proceeding with the the deployment.", self.image_uri)
 
         pysdk_model = HuggingFaceModel(
-            image_uri=self.image_uri, env=self.env_vars, role=self.role_arn
+            image_uri=self.image_uri,
+            env=self.env_vars,
+            role=self.role_arn,
+            sagemaker_session=self.sagemaker_session,
         )
 
         self._original_deploy = pysdk_model.deploy

src/sagemaker/serve/model_server/djl_serving/prepare.py

@@ -14,14 +14,14 @@
 
 from __future__ import absolute_import
 import shutil
-import tarfile
-import subprocess
 import json
+import tarfile
 import logging
 from typing import List
 from pathlib import Path
 
 from sagemaker.utils import _tmpdir
+from sagemaker.s3 import S3Downloader
 from sagemaker.djl_inference import DJLModel
 from sagemaker.djl_inference.model import _read_existing_serving_properties
 from sagemaker.serve.utils.local_hardware import _check_disk_space, _check_docker_disk_usage
@@ -34,27 +34,57 @@
 
 
 def _has_serving_properties_file(code_dir: Path) -> bool:
-    """Placeholder Docstring"""
+    """Check for existing serving properties in the directory"""
     return code_dir.joinpath(_SERVING_PROPERTIES_FILE).is_file()
 
 
-def _members(resources: object, depth: int):
-    """Placeholder Docstring"""
-    for member in resources.getmembers():
-        member.path = member.path.split("/", depth)[-1]
-        yield member
+def _move_to_code_dir(js_model_dir: str, code_dir: Path):
+    """Move DJL Jumpstart resources from model to code_dir"""
+    js_model_resources = Path(js_model_dir).joinpath("model")
+    for resource in js_model_resources.glob("*"):
+        try:
+            shutil.move(resource, code_dir)
+        except shutil.Error as e:
+            if "already exists" in str(e):
+                continue
+
+
+def _extract_js_resource(js_model_dir: str, js_id: str):
+    """Uncompress the jumpstart resource"""
+    tmp_sourcedir = Path(js_model_dir).joinpath(f"infer-prepack-{js_id}.tar.gz")
+    with tarfile.open(str(tmp_sourcedir)) as resources:
+        resources.extractall(path=js_model_dir)
 
 
 def _copy_jumpstart_artifacts(model_data: str, js_id: str, code_dir: Path):
-    """Placeholder Docstring"""
+    """Copy the associated JumpStart Resource into the code directory"""
     logger.info("Downloading JumpStart artifacts from S3...")
-    with _tmpdir(directory=str(code_dir)) as js_model_dir:
-        subprocess.run(["aws", "s3", "cp", model_data, js_model_dir])
 
-        logger.info("Uncompressing JumpStart artifacts for faster loading...")
-        tmp_sourcedir = Path(js_model_dir).joinpath(f"infer-prepack-{js_id}.tar.gz")
-        with tarfile.open(str(tmp_sourcedir)) as resources:
-            resources.extractall(path=code_dir, members=_members(resources, 1))
+    s3_downloader = S3Downloader()
+    invalid_model_data_format = False
+    with _tmpdir(directory=str(code_dir)) as js_model_dir:
+        if isinstance(model_data, str):
+            if model_data.endswith(".tar.gz"):
+                logger.info("Uncompressing JumpStart artifacts for faster loading...")
+                s3_downloader.download(model_data, js_model_dir)
+                _extract_js_resource(js_model_dir, js_id)
+            else:
+                logger.info("Copying uncompressed JumpStart artifacts...")
+                s3_downloader.download(model_data, js_model_dir)
+        elif (
+            isinstance(model_data, dict)
+            and model_data.get("S3DataSource")
+            and model_data.get("S3DataSource").get("S3Uri")
+        ):
+            logger.info("Copying uncompressed JumpStart artifacts...")
+            s3_downloader.download(model_data.get("S3DataSource").get("S3Uri"), js_model_dir)
+        else:
+            invalid_model_data_format = True
+        if not invalid_model_data_format:
+            _move_to_code_dir(js_model_dir, code_dir)
+
+    if invalid_model_data_format:
+        raise ValueError("JumpStart model data compression format is unsupported: %s", model_data)
 
     existing_properties = _read_existing_serving_properties(code_dir)
     config_json_file = code_dir.joinpath("config.json")
@@ -70,7 +100,7 @@ def _copy_jumpstart_artifacts(model_data: str, js_id: str, code_dir: Path):
 def _generate_properties_file(
     model: DJLModel, code_dir: Path, overwrite_props_from_file: bool, manual_set_props: dict
 ):
-    """Placeholder Docstring"""
+    """Construct serving properties file taking into account of overrides or manual specs"""
     if _has_serving_properties_file(code_dir):
         existing_properties = _read_existing_serving_properties(code_dir)
     else:

src/sagemaker/serve/model_server/tgi/prepare.py

@@ -1,37 +1,66 @@
+# Copyright 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
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
 """Prepare TgiModel for Deployment"""
 
 from __future__ import absolute_import
 import tarfile
-import subprocess
 import logging
 from typing import List
 from pathlib import Path
 
 from sagemaker.serve.utils.local_hardware import _check_disk_space, _check_docker_disk_usage
 from sagemaker.utils import _tmpdir
+from sagemaker.s3 import S3Downloader
 
 logger = logging.getLogger(__name__)
 
 
+def _extract_js_resource(js_model_dir: str, code_dir: Path, js_id: str):
+    """Uncompress the jumpstart resource"""
+    tmp_sourcedir = Path(js_model_dir).joinpath(f"infer-prepack-{js_id}.tar.gz")
+    with tarfile.open(str(tmp_sourcedir)) as resources:
+        resources.extractall(path=code_dir)
+
+
 def _copy_jumpstart_artifacts(model_data: str, js_id: str, code_dir: Path) -> bool:
-    """Placeholder Docstring"""
+    """Copy the associated JumpStart Resource into the code directory"""
     logger.info("Downloading JumpStart artifacts from S3...")
-    with _tmpdir(directory=str(code_dir)) as js_model_dir:
-        js_model_data_loc = model_data.get("S3DataSource").get("S3Uri")
-        # TODO: leave this check here until we are sure every js model has moved to uncompressed
-        if js_model_data_loc.endswith("tar.gz"):
-            subprocess.run(["aws", "s3", "cp", js_model_data_loc, js_model_dir])
+
+    s3_downloader = S3Downloader()
+    if isinstance(model_data, str):
+        if model_data.endswith(".tar.gz"):
             logger.info("Uncompressing JumpStart artifacts for faster loading...")
-            tmp_sourcedir = Path(js_model_dir).joinpath(f"infer-prepack-{js_id}.tar.gz")
-            with tarfile.open(str(tmp_sourcedir)) as resources:
-                resources.extractall(path=code_dir)
+            with _tmpdir(directory=str(code_dir)) as js_model_dir:
+                s3_downloader.download(model_data, js_model_dir)
+                _extract_js_resource(js_model_dir, code_dir, js_id)
         else:
-            subprocess.run(["aws", "s3", "cp", js_model_data_loc, js_model_dir, "--recursive"])
+            logger.info("Copying uncompressed JumpStart artifacts...")
+            s3_downloader.download(model_data, code_dir)
+    elif (
+        isinstance(model_data, dict)
+        and model_data.get("S3DataSource")
+        and model_data.get("S3DataSource").get("S3Uri")
+    ):
+        logger.info("Copying uncompressed JumpStart artifacts...")
+        s3_downloader.download(model_data.get("S3DataSource").get("S3Uri"), code_dir)
+    else:
+        raise ValueError("JumpStart model data compression format is unsupported: %s", model_data)
+
     return True
 
 
 def _create_dir_structure(model_path: str) -> tuple:
-    """Placeholder Docstring"""
+    """Create the expected model directory structure for the TGI server"""
     model_path = Path(model_path)
     if not model_path.exists():
         model_path.mkdir(parents=True)

tests/unit/sagemaker/serve/builder/test_djl_builder.py

@@ -114,10 +114,12 @@ def test_build_deploy_for_djl_local_container(
             mode=Mode.LOCAL_CONTAINER,
             model_server=ModelServer.DJL_SERVING,
         )
+
         builder._prepare_for_mode = MagicMock()
         builder._prepare_for_mode.side_effect = None
 
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
 
         assert isinstance(model, HuggingFaceAccelerateModel)
         assert (
@@ -176,6 +178,7 @@ def test_build_for_djl_local_container_faster_transformer(
             model_server=ModelServer.DJL_SERVING,
         )
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
 
         assert isinstance(model, FasterTransformerModel)
         assert (
@@ -211,6 +214,7 @@ def test_build_for_djl_local_container_deepspeed(
             model_server=ModelServer.DJL_SERVING,
         )
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
 
         assert isinstance(model, DeepSpeedModel)
         assert model.generate_serving_properties() == mock_expected_deepspeed_serving_properties
@@ -268,6 +272,7 @@ def test_tune_for_djl_local_container(
         builder._djl_model_builder_deploy_wrapper = MagicMock()
 
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
         tuned_model = model.tune()
         assert tuned_model.generate_serving_properties() == mock_most_performant_serving_properties
 
@@ -317,6 +322,7 @@ def test_tune_for_djl_local_container_deep_ping_ex(
         builder._prepare_for_mode.side_effect = None
 
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
         tuned_model = model.tune()
         assert (
             tuned_model.generate_serving_properties()
@@ -369,6 +375,7 @@ def test_tune_for_djl_local_container_load_ex(
         builder._prepare_for_mode.side_effect = None
 
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
         tuned_model = model.tune()
         assert (
             tuned_model.generate_serving_properties()
@@ -421,6 +428,7 @@ def test_tune_for_djl_local_container_oom_ex(
         builder._prepare_for_mode.side_effect = None
 
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
         tuned_model = model.tune()
         assert (
             tuned_model.generate_serving_properties()
@@ -473,6 +481,7 @@ def test_tune_for_djl_local_container_invoke_ex(
         builder._prepare_for_mode.side_effect = None
 
         model = builder.build()
+        builder.serve_settings.telemetry_opt_out = True
         tuned_model = model.tune()
         assert (
             tuned_model.generate_serving_properties()

tests/unit/sagemaker/serve/model_server/constants.py

@@ -0,0 +1,33 @@
+# Copyright 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
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+from __future__ import absolute_import
+
+MOCK_MODEL_PATH = "/path/to/mock/model/dir"
+MOCK_CODE_DIR = "/path/to/mock/model/dir/code"
+MOCK_JUMPSTART_ID = "mock_llm_js_id"
+MOCK_TMP_DIR = "tmp123456"
+MOCK_COMPRESSED_MODEL_DATA_STR = (
+    "s3://jumpstart-cache/to/infer-prepack-huggingface-llm-falcon-7b-bf16.tar.gz"
+)
+MOCK_UNCOMPRESSED_MODEL_DATA_STR = "s3://jumpstart-cache/to/artifacts/inference-prepack/v1.0.1/"
+MOCK_UNCOMPRESSED_MODEL_DATA_STR_FOR_DICT = (
+    "s3://jumpstart-cache/to/artifacts/inference-prepack/v1.0.1/dict/"
+)
+MOCK_UNCOMPRESSED_MODEL_DATA_DICT = {
+    "S3DataSource": {
+        "S3Uri": MOCK_UNCOMPRESSED_MODEL_DATA_STR_FOR_DICT,
+        "S3DataType": "S3Prefix",
+        "CompressionType": "None",
+    }
+}
+MOCK_INVALID_MODEL_DATA_DICT = {}