Fix: JS Model with non-TGI/non-DJL deployment failure#4688

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Merged
mufaddal-rohawala merged 10 commits into from
May 16, 2024
Merged

Fix: JS Model with non-TGI/non-DJL deployment failure #4688

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fix docstyle
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Add Integ tests
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b345aff
Merge branch 'master' into local-mode
makungaj1 May 16, 2024
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90 changes: 42 additions & 48 deletions src/sagemaker/serve/builder/jumpstart_builder.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
returns:
Tuned Model.
"""
if self.mode == Mode.SAGEMAKER_ENDPOINT:
logger.warning(
"Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
)
return self.pysdk_model

num_shard_env_var_name = "SM_NUM_GPUS"
if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
self.secret_key = None
self.jumpstart = True

self.pysdk_model = self._create_pre_trained_js_model()
self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

logger.info(
"JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
)

if self.mode != Mode.SAGEMAKER_ENDPOINT:
if self._is_gated_model(self.pysdk_model):
raise ValueError(
"JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
)

if "djl-inference" in self.pysdk_model.image_uri:
logger.info("Building for DJL JumpStart Model ID...")
self.model_server = ModelServer.DJL_SERVING
self.image_uri = self.pysdk_model.image_uri

self._build_for_djl_jumpstart()

self.pysdk_model.tune = self.tune_for_djl_jumpstart
elif "tgi-inference" in self.pysdk_model.image_uri:
logger.info("Building for TGI JumpStart Model ID...")
self.model_server = ModelServer.TGI
self.image_uri = self.pysdk_model.image_uri

self._build_for_tgi_jumpstart()
pysdk_model = self._create_pre_trained_js_model()
image_uri = pysdk_model.image_uri

self.pysdk_model.tune = self.tune_for_tgi_jumpstart
elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
logger.info("Building for MMS JumpStart Model ID...")
self.model_server = ModelServer.MMS
self.image_uri = self.pysdk_model.image_uri
logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

self._build_for_mms_jumpstart()
else:
raise ValueError(
"JumpStart Model ID was not packaged "
"with djl-inference, tgi-inference, or mms-inference container."
)

return self.pysdk_model
if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
raise ValueError(
"JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
)

def _default_tune(self):
"""Logs a warning message if tune is invoked on endpoint mode.
if "djl-inference" in image_uri:
logger.info("Building for DJL JumpStart Model ID...")
self.model_server = ModelServer.DJL_SERVING
self.pysdk_model = pysdk_model
self.image_uri = self.pysdk_model.image_uri

self._build_for_djl_jumpstart()

self.pysdk_model.tune = self.tune_for_djl_jumpstart
elif "tgi-inference" in image_uri:
logger.info("Building for TGI JumpStart Model ID...")
self.model_server = ModelServer.TGI
self.pysdk_model = pysdk_model
self.image_uri = self.pysdk_model.image_uri

self._build_for_tgi_jumpstart()

self.pysdk_model.tune = self.tune_for_tgi_jumpstart
elif "huggingface-pytorch-inference:" in image_uri:
logger.info("Building for MMS JumpStart Model ID...")
self.model_server = ModelServer.MMS
self.pysdk_model = pysdk_model
self.image_uri = self.pysdk_model.image_uri

self._build_for_mms_jumpstart()
elif self.mode != Mode.SAGEMAKER_ENDPOINT:
raise ValueError(
"JumpStart Model ID was not packaged "
"with djl-inference, tgi-inference, or mms-inference container."
)

Returns:
Jumpstart Model: ``This`` model
"""
logger.warning(
"Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
)
return self.pysdk_model

def _is_gated_model(self, model) -> bool:
Expand Down
50 changes: 50 additions & 0 deletions tests/integ/sagemaker/serve/test_serve_js_happy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
"How cute your dog is!",
"Your dog is so cute.",
"The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
)


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
iam_client = sagemaker_session.boto_session.client("iam")
return ModelBuilder(
model=JS_MMS_MODEL_ID,
schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
sagemaker_session=sagemaker_session,
)


@pytest.mark.skipif(
PYTHON_VERSION_IS_NOT_310,
reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
)
if caught_ex:
raise caught_ex


@pytest.mark.skipif(
PYTHON_VERSION_IS_NOT_310,
reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
logger.info("Running in SAGEMAKER_ENDPOINT mode...")
caught_ex = None
model = happy_mms_model_builder.build()

with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
try:
logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
logger.info("Endpoint successfully deployed.")

updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

predictor.predict(updated_sample_input)
except Exception as e:
caught_ex = e
finally:
cleanup_model_resources(
sagemaker_session=happy_mms_model_builder.sagemaker_session,
model_name=model.name,
endpoint_name=model.endpoint_name,
)
if caught_ex:
raise caught_ex
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Fix: JS Model with non-TGI/non-DJL deployment failure#4688

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to your account

 Merged

mufaddal-rohawala
merged 10 commits into

from

May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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43d3eb1

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May 16, 2024
8af45e3

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7e8d50c

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May 16, 2024
378e93b

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May 16, 2024
f29adee

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May 16, 2024
cac4716

Debug

May 16, 2024
927be8c

fix docstyle

May 16, 2024
8509e3b

Refactoring

May 16, 2024
93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Fix: JS Model with non-TGI/non-DJL deployment failure#4688

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
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to your account

 Merged

mufaddal-rohawala
merged 10 commits into

from

May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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43d3eb1

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May 16, 2024
8af45e3

Debug

May 16, 2024
7e8d50c

Debug

May 16, 2024
378e93b

Debug

May 16, 2024
f29adee

Debug

May 16, 2024
cac4716

Debug

May 16, 2024
927be8c

fix docstyle

May 16, 2024
8509e3b

Refactoring

May 16, 2024
93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Fix: JS Model with non-TGI/non-DJL deployment failure#4688

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May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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fix docstyle

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8509e3b

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93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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Fix: JS Model with non-TGI/non-DJL deployment failure#4688

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 Merged

mufaddal-rohawala
merged 10 commits into

from

May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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43d3eb1

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7e8d50c

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378e93b

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May 16, 2024
f29adee

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May 16, 2024
cac4716

Debug

May 16, 2024
927be8c

fix docstyle

May 16, 2024
8509e3b

Refactoring

May 16, 2024
93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Fix: JS Model with non-TGI/non-DJL deployment failure#4688

New issue

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 Merged

mufaddal-rohawala
merged 10 commits into

from

May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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927be8c

fix docstyle

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8509e3b

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93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Fix: JS Model with non-TGI/non-DJL deployment failure#4688

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 Merged

mufaddal-rohawala
merged 10 commits into

from

May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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927be8c

fix docstyle

May 16, 2024
8509e3b

Refactoring

May 16, 2024
93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
Fix: JS Model with non-TGI/non-DJL deployment failure#4688

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 Merged

mufaddal-rohawala
merged 10 commits into

from

May 16, 2024
 Merged


Fix: JS Model with non-TGI/non-DJL deployment failure
#4688
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43d3eb1

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May 16, 2024
8af45e3

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May 16, 2024
7e8d50c

Debug

May 16, 2024
378e93b

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May 16, 2024
f29adee

Debug

May 16, 2024
cac4716

Debug

May 16, 2024
927be8c

fix docstyle

May 16, 2024
8509e3b

Refactoring

May 16, 2024
93fee7e

Add Integ tests

May 16, 2024
b345aff

Merge branch 'master' into local-mode


makungaj1 May 16, 2024

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90 changes: 42 additions & 48 deletions
src/sagemaker/serve/builder/jumpstart_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -300,6 +300,11 @@ def _tune_for_js(self, sharded_supported: bool, max_tuning_duration: int = 1800)
 returns:
 Tuned Model.
 """
 if self.mode == Mode.SAGEMAKER_ENDPOINT:
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 num_shard_env_var_name = "SM_NUM_GPUS"
 if "OPTION_TENSOR_PARALLEL_DEGREE" in self.pysdk_model.env.keys():
Expand DownExpand Up@@ -468,58 +473,47 @@ def _build_for_jumpstart(self):
 self.secret_key = None
 self.jumpstart = True

 self.pysdk_model = self._create_pre_trained_js_model()
 self.pysdk_model.tune = lambda *args, **kwargs: self._default_tune()

 logger.info(
 "JumpStart ID %s is packaged with Image URI: %s", self.model, self.pysdk_model.image_uri
 )

 if self.mode != Mode.SAGEMAKER_ENDPOINT:
 if self._is_gated_model(self.pysdk_model):
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 if "djl-inference" in self.pysdk_model.image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in self.pysdk_model.image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()
 pysdk_model = self._create_pre_trained_js_model()
 image_uri = pysdk_model.image_uri

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in self.pysdk_model.image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.image_uri = self.pysdk_model.image_uri
 logger.info("JumpStart ID %s is packaged with Image URI: %s", self.model, image_uri)

 self._build_for_mms_jumpstart()
 else:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 return self.pysdk_model
 if self._is_gated_model(pysdk_model) and self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Gated Models are only supported in SAGEMAKER_ENDPOINT mode."
 )

 def _default_tune(self):
 """Logs a warning message if tune is invoked on endpoint mode.
 if "djl-inference" in image_uri:
 logger.info("Building for DJL JumpStart Model ID...")
 self.model_server = ModelServer.DJL_SERVING
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_djl_jumpstart()

 self.pysdk_model.tune = self.tune_for_djl_jumpstart
 elif "tgi-inference" in image_uri:
 logger.info("Building for TGI JumpStart Model ID...")
 self.model_server = ModelServer.TGI
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_tgi_jumpstart()

 self.pysdk_model.tune = self.tune_for_tgi_jumpstart
 elif "huggingface-pytorch-inference:" in image_uri:
 logger.info("Building for MMS JumpStart Model ID...")
 self.model_server = ModelServer.MMS
 self.pysdk_model = pysdk_model
 self.image_uri = self.pysdk_model.image_uri

 self._build_for_mms_jumpstart()
 elif self.mode != Mode.SAGEMAKER_ENDPOINT:
 raise ValueError(
 "JumpStart Model ID was not packaged "
 "with djl-inference, tgi-inference, or mms-inference container."
 )

 Returns:
 Jumpstart Model: ``This`` model
 """
 logger.warning(
 "Tuning is only a %s capability. Returning original model.", Mode.LOCAL_CONTAINER
 )
 return self.pysdk_model

 def _is_gated_model(self, model) -> bool:
Expand Down

50 changes: 50 additions & 0 deletions
tests/integ/sagemaker/serve/test_serve_js_happy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,6 +34,14 @@
JS_MODEL_ID = "huggingface-textgeneration1-gpt-neo-125m-fp16"
ROLE_NAME = "SageMakerRole"

SAMPLE_MMS_PROMPT = [
 "How cute your dog is!",
 "Your dog is so cute.",
 "The mitochondria is the powerhouse of the cell.",
]
SAMPLE_MMS_RESPONSE = {"embedding": []}
JS_MMS_MODEL_ID = "huggingface-sentencesimilarity-bge-m3"


@pytest.fixture
def happy_model_builder(sagemaker_session):
Expand All@@ -46,6 +54,17 @@ def happy_model_builder(sagemaker_session):
 )


@pytest.fixture
def happy_mms_model_builder(sagemaker_session):
 iam_client = sagemaker_session.boto_session.client("iam")
 return ModelBuilder(
 model=JS_MMS_MODEL_ID,
 schema_builder=SchemaBuilder(SAMPLE_MMS_PROMPT, SAMPLE_MMS_RESPONSE),
 role_arn=iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"],
 sagemaker_session=sagemaker_session,
 )


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
Expand DownExpand Up@@ -75,3 +94,34 @@ def test_happy_tgi_sagemaker_endpoint(happy_model_builder, gpu_instance_type):
 )
 if caught_ex:
 raise caught_ex


@pytest.mark.skipif(
 PYTHON_VERSION_IS_NOT_310,
 reason="The goal of these test are to test the serving components of our feature",
)
@pytest.mark.slow_test
def test_happy_mms_sagemaker_endpoint(happy_mms_model_builder, gpu_instance_type):
 logger.info("Running in SAGEMAKER_ENDPOINT mode...")
 caught_ex = None
 model = happy_mms_model_builder.build()

 with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
 try:
 logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
 predictor = model.deploy(instance_type=gpu_instance_type, endpoint_logging=False)
 logger.info("Endpoint successfully deployed.")

 updated_sample_input = happy_mms_model_builder.schema_builder.sample_input

 predictor.predict(updated_sample_input)
 except Exception as e:
 caught_ex = e
 finally:
 cleanup_model_resources(
 sagemaker_session=happy_mms_model_builder.sagemaker_session,
 model_name=model.name,
 endpoint_name=model.endpoint_name,
 )
 if caught_ex:
 raise caught_ex