fix: Model server override logic#4733

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Merged
erickb336 merged 4 commits into from
Jun 19, 2024
Merged

fix: Model server override logic #4733

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e5b38aa
fix: Model server override logic
samruds Jun 18, 2024
6f88922
Fix formatting
samruds Jun 18, 2024
98b8233
Merge branch 'master' into fix-overrides-cr
erickb336 Jun 18, 2024
4fe78bc
Merge branch 'master' into fix-overrides-cr
samruds Jun 19, 2024
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84 changes: 56 additions & 28 deletions src/sagemaker/serve/builder/model_builder.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
ModelServer.TORCHSERVE,
ModelServer.TRITON,
ModelServer.DJL_SERVING,
ModelServer.TENSORFLOW_SERVING,
ModelServer.MMS,
ModelServer.TGI,
ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
},
)

def _build_validations(self):
"""Placeholder docstring"""
# TODO: Beta validations - remove after the launch
if self.mode == Mode.IN_PROCESS:
raise ValueError("IN_PROCESS mode is not supported yet!")

if self.inference_spec and self.model:
raise ValueError("Cannot have both the Model and Inference spec in the builder")

if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
raise ValueError(
"Model_server must be set when non-first-party image_uri is set. "
+ "Supported model servers: %s" % supported_model_server
)

# Set TorchServe as default model server
if not self.model_server:
self.model_server = ModelServer.TORCHSERVE

if self.model_server not in supported_model_server:
raise ValueError(
"%s is not supported yet! Supported model servers: %s"
% (self.model_server, supported_model_server)
)

def _save_model_inference_spec(self):
"""Placeholder docstring"""
# check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

self._handle_mlflow_input()

self._build_validations()

if self.model_server:
return self._build_for_model_server()

if isinstance(self.model, str):
model_task = None
if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
else:
return self._build_for_transformers()

self._build_validations()
# Set TorchServe as default model server
if not self.model_server:
self.model_server = ModelServer.TORCHSERVE
return self._build_for_torchserve()

raise ValueError("%s model server is not supported" % self.model_server)

def _build_validations(self):
"""Validations needed for model server overrides, or auto-detection or fallback"""
if self.mode == Mode.IN_PROCESS:
raise ValueError("IN_PROCESS mode is not supported yet!")

if self.inference_spec and self.model:
raise ValueError("Can only set one of the following: model, inference_spec.")

if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
raise ValueError(
"Model_server must be set when non-first-party image_uri is set. "
+ "Supported model servers: %s" % supported_model_servers
)

def _build_for_model_server(self): # pylint: disable=R0911, R1710
"""Model server overrides"""
if self.model_server not in supported_model_servers:
raise ValueError(
"%s is not supported yet! Supported model servers: %s"
% (self.model_server, supported_model_servers)
)

mlflow_path = None
if self.model_metadata:
mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

if not self.model and not mlflow_path:
raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.

if self.model_server == ModelServer.TORCHSERVE:
return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
if self.model_server == ModelServer.TENSORFLOW_SERVING:
return self._build_for_tensorflow_serving()

raise ValueError("%s model server is not supported" % self.model_server)
if self.model_server == ModelServer.DJL_SERVING:
return self._build_for_djl()

if self.model_server == ModelServer.TEI:
return self._build_for_tei()

if self.model_server == ModelServer.TGI:
return self._build_for_tgi()

if self.model_server == ModelServer.MMS:
return self._build_for_transformers()

def save(
self,
Expand Down
125 changes: 121 additions & 4 deletions tests/unit/sagemaker/serve/builder/test_model_builder.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
ModelServer.TORCHSERVE,
ModelServer.TRITON,
ModelServer.DJL_SERVING,
ModelServer.TENSORFLOW_SERVING,
ModelServer.MMS,
ModelServer.TGI,
ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
self.assertRaisesRegex(
Exception,
"Cannot have both the Model and Inference spec in the builder",
"Can only set one of the following: model, inference_spec.",
builder.build,
Mode.SAGEMAKER_ENDPOINT,
mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
self.assertRaisesRegex(
Exception,
"%s is not supported yet! Supported model servers: %s"
% (builder.model_server, supported_model_server),
% (builder.model_server, supported_model_servers),
builder.build,
Mode.SAGEMAKER_ENDPOINT,
mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
self.assertRaisesRegex(
Exception,
"Model_server must be set when non-first-party image_uri is set. "
+ "Supported model servers: %s" % supported_model_server,
+ "Supported model servers: %s" % supported_model_servers,
builder.build,
Mode.SAGEMAKER_ENDPOINT,
mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
mock_session,
)

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_djl.assert_called_once()

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
builder = ModelBuilder(
model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
)
self.assertRaisesRegex(
Exception,
"Missing required parameter `model` or 'ml_flow' path",
builder.build,
Mode.SAGEMAKER_ENDPOINT,
mock_role_arn,
mock_session,
)

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
def test_model_server_override_torchserve_with_model(
self, mock_build_for_ts, mock_serve_settings
):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_ts.assert_called_once()

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
self.assertRaisesRegex(
Exception,
"Missing required parameter `model` or 'ml_flow' path",
builder.build,
Mode.SAGEMAKER_ENDPOINT,
mock_role_arn,
mock_session,
)

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_ts.assert_called_once()

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_ts.assert_called_once()

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_ts.assert_called_once()

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_ts.assert_called_once()

@patch("sagemaker.serve.builder.model_builder._ServeSettings")
@patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
def test_model_server_override_transformers_with_model(
self, mock_build_for_ts, mock_serve_settings
):
mock_setting_object = mock_serve_settings.return_value
mock_setting_object.role_arn = mock_role_arn
mock_setting_object.s3_model_data_url = mock_s3_model_data_url

builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
builder.build(sagemaker_session=mock_session)

mock_build_for_ts.assert_called_once()

@patch("os.makedirs", Mock())
@patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
@patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down
, '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: Model server override logic#4733

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

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to your account

 Merged

erickb336
merged 4 commits into

from

Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down

, '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('^' + ".*" + '

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fix: Model server override logic#4733

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 Merged

erickb336
merged 4 commits into

from

Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down

, '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('^' + ".*" + '

Skip to content
fix: Model server override logic#4733

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Sign in
to your account

 Merged

erickb336
merged 4 commits into

from

Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down

, '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: Model server override logic#4733

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 Merged

erickb336
merged 4 commits into

from

Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down

, '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: Model server override logic#4733

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?
Sign in
to your account

 Merged

erickb336
merged 4 commits into

from

Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down

, '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: Model server override logic#4733

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 Merged

erickb336
merged 4 commits into

from

Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down

, '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); }
})();
})();

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fix: Model server override logic#4733

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 Merged

erickb336
merged 4 commits into

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Jun 19, 2024
 Merged


fix: Model server override logic
#4733
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e5b38aa

fix: Model server override logic


samruds Jun 18, 2024
6f88922

Fix formatting


samruds Jun 18, 2024
98b8233

Merge branch 'master' into fix-overrides-cr


erickb336 Jun 18, 2024
4fe78bc

Merge branch 'master' into fix-overrides-cr


samruds Jun 19, 2024

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84 changes: 56 additions & 28 deletions
src/sagemaker/serve/builder/model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -94,11 +94,15 @@

logger = logging.getLogger(__name__)

supported_model_server = {
# Any new server type should be added here
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}


Expand DownExpand Up@@ -288,31 +292,6 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing,
 },
 )

 def _build_validations(self):
 """Placeholder docstring"""
 # TODO: Beta validations - remove after the launch
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Cannot have both the Model and Inference spec in the builder")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server
 )

 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE

 if self.model_server not in supported_model_server:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_server)
 )

 def _save_model_inference_spec(self):
 """Placeholder docstring"""
 # check if path exists and create if not
Expand DownExpand Up@@ -839,6 +818,11 @@ def build( # pylint: disable=R0911

 self._handle_mlflow_input()

 self._build_validations()

 if self.model_server:
 return self._build_for_model_server()

 if isinstance(self.model, str):
 model_task = None
 if self.model_metadata:
Expand DownExpand Up@@ -870,7 +854,41 @@ def build( # pylint: disable=R0911
 else:
 return self._build_for_transformers()

 self._build_validations()
 # Set TorchServe as default model server
 if not self.model_server:
 self.model_server = ModelServer.TORCHSERVE
 return self._build_for_torchserve()

 raise ValueError("%s model server is not supported" % self.model_server)

 def _build_validations(self):
 """Validations needed for model server overrides, or auto-detection or fallback"""
 if self.mode == Mode.IN_PROCESS:
 raise ValueError("IN_PROCESS mode is not supported yet!")

 if self.inference_spec and self.model:
 raise ValueError("Can only set one of the following: model, inference_spec.")

 if self.image_uri and not is_1p_image_uri(self.image_uri) and self.model_server is None:
 raise ValueError(
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_servers
 )

 def _build_for_model_server(self): # pylint: disable=R0911, R1710
 """Model server overrides"""
 if self.model_server not in supported_model_servers:
 raise ValueError(
 "%s is not supported yet! Supported model servers: %s"
 % (self.model_server, supported_model_servers)
 )

 mlflow_path = None
 if self.model_metadata:
 mlflow_path = self.model_metadata.get(MLFLOW_MODEL_PATH)

 if not self.model and not mlflow_path:
 raise ValueError("Missing required parameter `model` or 'ml_flow' path")
Comment thread
samruds marked this conversation as resolved.


 if self.model_server == ModelServer.TORCHSERVE:
 return self._build_for_torchserve()
Expand All@@ -881,7 +899,17 @@ def build( # pylint: disable=R0911
 if self.model_server == ModelServer.TENSORFLOW_SERVING:
 return self._build_for_tensorflow_serving()

 raise ValueError("%s model server is not supported" % self.model_server)
 if self.model_server == ModelServer.DJL_SERVING:
 return self._build_for_djl()

 if self.model_server == ModelServer.TEI:
 return self._build_for_tei()

 if self.model_server == ModelServer.TGI:
 return self._build_for_tgi()

 if self.model_server == ModelServer.MMS:
 return self._build_for_transformers()

 def save(
 self,
Expand Down

125 changes: 121 additions & 4 deletions
tests/unit/sagemaker/serve/builder/test_model_builder.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -50,11 +50,14 @@
mock_secret_key = "mock_secret_key"
mock_instance_type = "mock instance type"

supported_model_server = {
supported_model_servers = {
 ModelServer.TORCHSERVE,
 ModelServer.TRITON,
 ModelServer.DJL_SERVING,
 ModelServer.TENSORFLOW_SERVING,
 ModelServer.MMS,
 ModelServer.TGI,
 ModelServer.TEI,
}

mock_session = MagicMock()
Expand All@@ -78,7 +81,7 @@ def test_validation_cannot_set_both_model_and_inference_spec(self, mock_serveSet
 builder = ModelBuilder(inference_spec="some value", model=Mock(spec=object))
 self.assertRaisesRegex(
 Exception,
 "Cannot have both the Model and Inference spec in the builder",
 "Can only set one of the following: model, inference_spec.",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -91,7 +94,7 @@ def test_validation_unsupported_model_server_type(self, mock_serveSettings):
 self.assertRaisesRegex(
 Exception,
 "%s is not supported yet! Supported model servers: %s"
 % (builder.model_server, supported_model_server),
 % (builder.model_server, supported_model_servers),
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -104,7 +107,7 @@ def test_validation_model_server_not_set_with_image_uri(self, mock_serveSettings
 self.assertRaisesRegex(
 Exception,
 "Model_server must be set when non-first-party image_uri is set. "
 + "Supported model servers: %s" % supported_model_server,
 + "Supported model servers: %s" % supported_model_servers,
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
Expand All@@ -125,6 +128,120 @@ def test_save_model_throw_exception_when_none_of_model_and_inference_spec_is_set
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_djl")
 def test_model_server_override_djl_with_model(self, mock_build_for_djl, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.DJL_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_djl.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_djl_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(
 model_server=ModelServer.DJL_SERVING, model=None, inference_spec=None
 )
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_torchserve")
 def test_model_server_override_torchserve_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 def test_model_server_override_torchserve_without_model_or_mlflow(self, mock_serve_settings):
 builder = ModelBuilder(model_server=ModelServer.TORCHSERVE)
 self.assertRaisesRegex(
 Exception,
 "Missing required parameter `model` or 'ml_flow' path",
 builder.build,
 Mode.SAGEMAKER_ENDPOINT,
 mock_role_arn,
 mock_session,
 )

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_triton")
 def test_model_server_override_triton_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TRITON, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tensorflow_serving")
 def test_model_server_override_tensor_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TENSORFLOW_SERVING, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tei")
 def test_model_server_override_tei_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TEI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_tgi")
 def test_model_server_override_tgi_with_model(self, mock_build_for_ts, mock_serve_settings):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.TGI, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("sagemaker.serve.builder.model_builder._ServeSettings")
 @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_transformers")
 def test_model_server_override_transformers_with_model(
 self, mock_build_for_ts, mock_serve_settings
 ):
 mock_setting_object = mock_serve_settings.return_value
 mock_setting_object.role_arn = mock_role_arn
 mock_setting_object.s3_model_data_url = mock_s3_model_data_url

 builder = ModelBuilder(model_server=ModelServer.MMS, model="gpt_llm_burt")
 builder.build(sagemaker_session=mock_session)

 mock_build_for_ts.assert_called_once()

 @patch("os.makedirs", Mock())
 @patch("sagemaker.serve.builder.model_builder._detect_framework_and_version")
 @patch("sagemaker.serve.builder.model_builder.prepare_for_torchserve")
Expand Down