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feature: Serve model directly from original model artifact directory … #71

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Merged
merged 1 commit into from
Oct 17, 2022
Merged

feature: Serve model directly from original model artifact directory … #71

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2 changes: 1 addition & 1 deletion setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,7 +80,7 @@
extras["benchmark"] = ["boto3", "locust"]

extras["quality"] = [
"black==21.4b0",
"black>=21.10",
"isort>=5.5.4",
"flake8>=3.8.3",
]
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29 changes: 19 additions & 10 deletions src/sagemaker_huggingface_inference_toolkit/mms_model_server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,9 +18,9 @@
import subprocess

from sagemaker_inference import environment, logging
from sagemaker_inference.environment import model_dir
from sagemaker_inference.model_server import (
DEFAULT_MMS_LOG_FILE,
DEFAULT_MMS_MODEL_NAME,
ENABLE_MULTI_MODEL,
MMS_CONFIG_FILE,
REQUIREMENTS_PATH,
Expand All @@ -45,8 +45,8 @@

DEFAULT_HANDLER_SERVICE = handler_service.__name__

DEFAULT_MMS_MODEL_DIRECTORY = os.path.join(os.getcwd(), ".sagemaker/mms/models")
MODEL_STORE = "/" if ENABLE_MULTI_MODEL else DEFAULT_MMS_MODEL_DIRECTORY
DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY = os.path.join(os.getcwd(), ".sagemaker/mms/models")
DEFAULT_MODEL_STORE = "/"


def start_model_server(handler_service=DEFAULT_HANDLER_SERVICE):
Expand All @@ -64,28 +64,35 @@ def start_model_server(handler_service=DEFAULT_HANDLER_SERVICE):
Defaults to ``sagemaker_huggingface_inference_toolkit.handler_service``.

"""
use_hf_hub = "HF_MODEL_ID" in os.environ
model_store = DEFAULT_MODEL_STORE
if ENABLE_MULTI_MODEL:
if not os.getenv("SAGEMAKER_HANDLER"):
os.environ["SAGEMAKER_HANDLER"] = handler_service
_set_python_path()
elif "HF_MODEL_ID" in os.environ:
elif use_hf_hub:
# Use different model store directory
model_store = DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY
if is_aws_neuron_available():
raise ValueError(
"Hugging Face Hub deployments are currently not supported with AWS Neuron and Inferentia."
"You need to create a `inference.py` script to run your model using AWS Neuron"
)
storage_dir = _load_model_from_hub(
model_id=os.environ["HF_MODEL_ID"],
model_dir=DEFAULT_MMS_MODEL_DIRECTORY,
model_dir=DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY,
revision=HF_MODEL_REVISION,
use_auth_token=HF_API_TOKEN,
)
_adapt_to_mms_format(handler_service, storage_dir)
else:
_adapt_to_mms_format(handler_service, model_dir)
_set_python_path()

env = environment.Environment()
_create_model_server_config_file(env)

# Note: multi-model default config already sets default_service_handler
handler_service_for_config = None if ENABLE_MULTI_MODEL else handler_service
_create_model_server_config_file(env, handler_service_for_config)

if os.path.exists(REQUIREMENTS_PATH):
_install_requirements()
Expand All @@ -94,12 +101,14 @@ def start_model_server(handler_service=DEFAULT_HANDLER_SERVICE):
"multi-model-server",
"--start",
"--model-store",
MODEL_STORE,
model_store,
"--mms-config",
MMS_CONFIG_FILE,
"--log-config",
DEFAULT_MMS_LOG_FILE,
]
if not ENABLE_MULTI_MODEL and not use_hf_hub:
multi_model_server_cmd += ["--models", DEFAULT_MMS_MODEL_NAME + "=" + environment.model_dir]

logger.info(multi_model_server_cmd)
subprocess.Popen(multi_model_server_cmd)
Expand All @@ -113,7 +122,7 @@ def start_model_server(handler_service=DEFAULT_HANDLER_SERVICE):


def _adapt_to_mms_format(handler_service, model_path):
os.makedirs(DEFAULT_MMS_MODEL_DIRECTORY, exist_ok=True)
os.makedirs(DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY, exist_ok=True)

# gets the model from the path, default is model/
model = pathlib.PurePath(model_path)
Expand All @@ -128,7 +137,7 @@ def _adapt_to_mms_format(handler_service, model_path):
"--model-path",
model_path,
"--export-path",
DEFAULT_MMS_MODEL_DIRECTORY,
DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY,
"--archive-format",
"no-archive",
"--f",
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30 changes: 20 additions & 10 deletions tests/unit/test_mms_model_server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,20 +47,24 @@ def test_start_mms_default_service_handler(
env.return_value.startup_timeout = 10000
mms_model_server.start_model_server()

adapt.assert_called_once_with(mms_model_server.DEFAULT_HANDLER_SERVICE, model_dir)
create_config.assert_called_once_with(env.return_value)
# In this case, we should not rearchive the model
adapt.assert_not_called()

create_config.assert_called_once_with(env.return_value, mms_model_server.DEFAULT_HANDLER_SERVICE)
exists.assert_called_once_with(mms_model_server.REQUIREMENTS_PATH)
install_requirements.assert_called_once_with()

multi_model_server_cmd = [
"multi-model-server",
"--start",
"--model-store",
mms_model_server.MODEL_STORE,
mms_model_server.DEFAULT_MODEL_STORE,
"--mms-config",
mms_model_server.MMS_CONFIG_FILE,
"--log-config",
mms_model_server.DEFAULT_MMS_LOG_FILE,
"--models",
"{}={}".format(mms_model_server.DEFAULT_MMS_MODEL_NAME, model_dir),
]

subprocess_popen.assert_called_once_with(multi_model_server_cmd)
Expand Down Expand Up @@ -98,20 +102,24 @@ def test_start_mms_neuron(
env.return_value.startup_timeout = 10000
mms_model_server.start_model_server()

adapt.assert_called_once_with(mms_model_server.DEFAULT_HANDLER_SERVICE, model_dir)
create_config.assert_called_once_with(env.return_value)
# In this case, we should not call model archiver
adapt.assert_not_called()

create_config.assert_called_once_with(env.return_value, mms_model_server.DEFAULT_HANDLER_SERVICE)
exists.assert_called_once_with(mms_model_server.REQUIREMENTS_PATH)
install_requirements.assert_called_once_with()

multi_model_server_cmd = [
"multi-model-server",
"--start",
"--model-store",
mms_model_server.MODEL_STORE,
mms_model_server.DEFAULT_MODEL_STORE,
"--mms-config",
mms_model_server.MMS_CONFIG_FILE,
"--log-config",
mms_model_server.DEFAULT_MMS_LOG_FILE,
"--models",
"{}={}".format(mms_model_server.DEFAULT_MMS_MODEL_NAME, model_dir),
]

subprocess_popen.assert_called_once_with(multi_model_server_cmd)
Expand Down Expand Up @@ -152,21 +160,23 @@ def test_start_mms_with_model_from_hub(

load_model_from_hub.assert_called_once_with(
model_id=os.environ["HF_MODEL_ID"],
model_dir=mms_model_server.DEFAULT_MMS_MODEL_DIRECTORY,
model_dir=mms_model_server.DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY,
revision=transformers_utils.HF_MODEL_REVISION,
use_auth_token=transformers_utils.HF_API_TOKEN,
)

# When loading model from hub, we do call model archiver
adapt.assert_called_once_with(mms_model_server.DEFAULT_HANDLER_SERVICE, load_model_from_hub())
create_config.assert_called_once_with(env.return_value)

create_config.assert_called_once_with(env.return_value, mms_model_server.DEFAULT_HANDLER_SERVICE)
exists.assert_called_with(mms_model_server.REQUIREMENTS_PATH)
install_requirements.assert_called_once_with()

multi_model_server_cmd = [
"multi-model-server",
"--start",
"--model-store",
mms_model_server.MODEL_STORE,
mms_model_server.DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY,
"--mms-config",
mms_model_server.MMS_CONFIG_FILE,
"--log-config",
Expand All @@ -175,7 +185,7 @@ def test_start_mms_with_model_from_hub(

subprocess_popen.assert_called_once_with(multi_model_server_cmd)
sigterm.assert_called_once_with(retrieve.return_value)
os.remove(mms_model_server.DEFAULT_MMS_MODEL_DIRECTORY)
os.remove(mms_model_server.DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY)


@patch("sagemaker_huggingface_inference_toolkit.transformers_utils._aws_neuron_available", return_value=True)
Expand Down