fix: tags for jumpstart model package models#4061

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Merged
knikure merged 6 commits into from
Aug 14, 2023
Merged

fix: tags for jumpstart model package models #4061

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c1157bd
fix: tags for jumpstart model package models
evakravi Aug 9, 2023
f64ca6d
fix: tags for ModelPackage
evakravi Aug 10, 2023
41a2113
chore: improve docstring
evakravi Aug 10, 2023
e4fb3bc
fix: unit tests
evakravi Aug 11, 2023
0b1ce9f
Merge branch 'master' into fix/tags-js-model-packages
evakravi Aug 11, 2023
15b20d5
Merge branch 'master' into fix/tags-js-model-packages
evakravi Aug 11, 2023
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39 changes: 33 additions & 6 deletions src/sagemaker/jumpstart/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
def _create_sagemaker_model(
self,
instance_type=None,
accelerator_type=None,
tags=None,
serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.
**kwargs,
):
"""Create a SageMaker Model Entity

Args:
args: Positional arguments coming from the caller. This class does not require
any so they are ignored.

instance_type (str): Optional. The EC2 instance type that this Model will be
used for, this is only used to determine if the image needs GPU
support or not. (Default: None).
accelerator_type (str): Optional. Type of Elastic Inference accelerator to
attach to an endpoint for model loading and inference, for
example, 'ml.eia1.medium'. If not specified, no Elastic
Inference accelerator will be attached to the endpoint. (Default: None).
tags (List[dict[str, str]]): Optional. The list of tags to add to
the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
'tagvalue'}] For more information about tags, see
https://boto3.amazonaws.com/v1/documentation
/api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
(Default: None).
serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
Optional. Specifies configuration related to serverless endpoint. Instance type is
not provided in serverless inference. So this is used to find image URIs.
(Default: None).
kwargs: Keyword arguments coming from the caller. This class does not require
any so they are ignored.
"""
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
container_def,
vpc_config=self.vpc_config,
enable_network_isolation=self.enable_network_isolation(),
tags=kwargs.get("tags"),
tags=tags,
)
else:
super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
super(JumpStartModel, self)._create_sagemaker_model(
instance_type=instance_type,
accelerator_type=accelerator_type,
tags=tags,

@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?

@evakravievakraviAug 9, 2023

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.

@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed

@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs

serverless_inference_config=serverless_inference_config,
**kwargs,
)

def deploy(
self,
Expand Down
5 changes: 4 additions & 1 deletion src/sagemaker/model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
self._base_name = "-".join((self._base_name, compiled_model_suffix))

self._create_sagemaker_model(
instance_type, accelerator_type, tags, serverless_inference_config
instance_type=instance_type,
accelerator_type=accelerator_type,
tags=tags,
serverless_inference_config=serverless_inference_config,
)

serverless_inference_config_dict = (
Expand Down
7 changes: 6 additions & 1 deletion tests/unit/sagemaker/jumpstart/model/test_model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

model = JumpStartModel(model_id=model_id)

model.deploy()
tag = {"Key": "foo", "Value": "bar"}
tags = [tag]

model.deploy(tags=tags)

self.assertEqual(
mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
},
)

self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

@mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
@mock.patch("sagemaker.jumpstart.factory.model.Session")
@mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down
21 changes: 18 additions & 3 deletions tests/unit/sagemaker/model/test_deploy.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
accelerator_type=ACCELERATOR_TYPE,
)

create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
create_sagemaker_model.assert_called_with(
instance_type=INSTANCE_TYPE,
accelerator_type=ACCELERATOR_TYPE,
tags=None,
serverless_inference_config=None,
)
production_variant.assert_called_with(
MODEL_NAME,
INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
tags = [{"Key": "ModelName", "Value": "TestModel"}]
model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
create_sagemaker_model.assert_called_with(
instance_type=INSTANCE_TYPE,
accelerator_type=None,
tags=tags,
serverless_inference_config=None,
)
sagemaker_session.endpoint_from_production_variants.assert_called_with(
name=ENDPOINT_NAME,
production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
serverless_inference_config=serverless_inference_config,
)

create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
create_sagemaker_model.assert_called_with(
instance_type=None,
accelerator_type=None,
tags=None,
serverless_inference_config=serverless_inference_config,
)
production_variant.assert_called_with(
MODEL_NAME,
None,
Expand Down
2 changes: 1 addition & 1 deletion tests/unit/sagemaker/model/test_model_package.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
sagemaker_session=sagemaker_session,
)

model_package._create_sagemaker_model(tags=tags)
model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

sagemaker_session.create_model.assert_called_with(
model_name,
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" + '

Skip to content
fix: tags for jumpstart model package models#4061

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to your account

 Merged

knikure
merged 6 commits into

from

Aug 14, 2023
 Merged


fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
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('^' + ".*" + '

Skip to content
fix: tags for jumpstart model package models#4061

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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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Sign in
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 Merged

knikure
merged 6 commits into

from

Aug 14, 2023
 Merged


fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
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('^' + ".*" + '

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fix: tags for jumpstart model package models#4061

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 Merged

knikure
merged 6 commits into

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Aug 14, 2023
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fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
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" + '

Skip to content
fix: tags for jumpstart model package models#4061

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 Merged

knikure
merged 6 commits into

from

Aug 14, 2023
 Merged


fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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Choose a reason for hiding this comment

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
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('^' + ".*" + '

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fix: tags for jumpstart model package models#4061

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 Merged

knikure
merged 6 commits into

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Aug 14, 2023
 Merged


fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
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('^' + ".*" + '

Skip to content
fix: tags for jumpstart model package models#4061

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 Merged

knikure
merged 6 commits into

from

Aug 14, 2023
 Merged


fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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Choose a reason for hiding this comment

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
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); }
})();
})();

Skip to content
fix: tags for jumpstart model package models#4061

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

Already on GitHub?
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 Merged

knikure
merged 6 commits into

from

Aug 14, 2023
 Merged


fix: tags for jumpstart model package models
#4061
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c1157bd

fix: tags for jumpstart model package models


evakravi Aug 9, 2023
f64ca6d

fix: tags for ModelPackage


evakravi Aug 10, 2023
41a2113

chore: improve docstring


evakravi Aug 10, 2023
e4fb3bc

fix: unit tests


evakravi Aug 11, 2023
0b1ce9f

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023
15b20d5

Merge branch 'master' into fix/tags-js-model-packages


evakravi Aug 11, 2023

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39 changes: 33 additions & 6 deletions
src/sagemaker/jumpstart/model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -310,13 +310,34 @@ def _is_valid_model_id_hook():

 super(JumpStartModel, self).__init__(**model_init_kwargs.to_kwargs_dict())

 def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-argument
 def _create_sagemaker_model(
 self,
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=None,
Comment thread
mufaddal-rohawala marked this conversation as resolved.

 **kwargs,
 ):
 """Create a SageMaker Model Entity

 Args:
 args: Positional arguments coming from the caller. This class does not require
 any so they are ignored.

 instance_type (str): Optional. The EC2 instance type that this Model will be
 used for, this is only used to determine if the image needs GPU
 support or not. (Default: None).
 accelerator_type (str): Optional. Type of Elastic Inference accelerator to
 attach to an endpoint for model loading and inference, for
 example, 'ml.eia1.medium'. If not specified, no Elastic
 Inference accelerator will be attached to the endpoint. (Default: None).
 tags (List[dict[str, str]]): Optional. The list of tags to add to
 the model. Example: >>> tags = [{'Key': 'tagname', 'Value':
 'tagvalue'}] For more information about tags, see
 https://boto3.amazonaws.com/v1/documentation
 /api/latest/reference/services/sagemaker.html#SageMaker.Client.add_tags
 (Default: None).
 serverless_inference_config (sagemaker.serverless.ServerlessInferenceConfig):
 Optional. Specifies configuration related to serverless endpoint. Instance type is
 not provided in serverless inference. So this is used to find image URIs.
 (Default: None).
 kwargs: Keyword arguments coming from the caller. This class does not require
 any so they are ignored.
 """
Expand DownExpand Up@@ -347,10 +368,16 @@ def _create_sagemaker_model(self, *args, **kwargs): # pylint: disable=unused-ar
 container_def,
 vpc_config=self.vpc_config,
 enable_network_isolation=self.enable_network_isolation(),
 tags=kwargs.get("tags"),
 tags=tags,
 )
 else:
 super(JumpStartModel, self)._create_sagemaker_model(*args, **kwargs)
 super(JumpStartModel, self)._create_sagemaker_model(
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
@whittech1whittech1Aug 9, 2023

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Sanity check: will tags value end up being None here? Or will the values in kwargs cause a keyword argument name conflict?
@evakravievakraviAug 9, 2023

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tags cannot be in kwargs since it's an explicit argument. kwargs will only contain new parameters should they get added in the future, to ensure it gets passed to the parent class.
@whittech1whittech1Aug 10, 2023

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Just confirming that in the previous behavior, kwargs.get("tags") returned None b/c the tags key would not have existed
@mufaddal-rohawalamufaddal-rohawalaAug 10, 2023

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+1, if just to make sure on above, if it does maybe we just append the tags from kwargs
 serverless_inference_config=serverless_inference_config,
 **kwargs,
 )

 def deploy(
 self,
Expand Down

5 changes: 4 additions & 1 deletion
src/sagemaker/model.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -1375,7 +1375,10 @@ def deploy(
 self._base_name = "-".join((self._base_name, compiled_model_suffix))

 self._create_sagemaker_model(
 instance_type, accelerator_type, tags, serverless_inference_config
 instance_type=instance_type,
 accelerator_type=accelerator_type,
 tags=tags,
 serverless_inference_config=serverless_inference_config,
 )

 serverless_inference_config_dict = (
Expand Down

7 changes: 6 additions & 1 deletion
tests/unit/sagemaker/jumpstart/model/test_model.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -589,7 +589,10 @@ def test_jumpstart_model_package_arn(

 model = JumpStartModel(model_id=model_id)

 model.deploy()
 tag = {"Key": "foo", "Value": "bar"}
 tags = [tag]

 model.deploy(tags=tags)

 self.assertEqual(
 mock_session.return_value.create_model.call_args[0][2],
Expand All@@ -599,6 +602,8 @@ def test_jumpstart_model_package_arn(
 },
 )

 self.assertIn(tag, mock_session.return_value.create_model.call_args[1]["tags"])

 @mock.patch("sagemaker.jumpstart.model.is_valid_model_id")
 @mock.patch("sagemaker.jumpstart.factory.model.Session")
 @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs")
Expand Down

21 changes: 18 additions & 3 deletions
tests/unit/sagemaker/model/test_deploy.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -159,7 +159,12 @@ def test_deploy_accelerator_type(
 accelerator_type=ACCELERATOR_TYPE,
 )

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=ACCELERATOR_TYPE,
 tags=None,
 serverless_inference_config=None,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 INSTANCE_TYPE,
Expand DownExpand Up@@ -271,7 +276,12 @@ def test_deploy_tags(create_sagemaker_model, production_variant, name_from_base,
 tags = [{"Key": "ModelName", "Value": "TestModel"}]
 model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, tags=tags)

 create_sagemaker_model.assert_called_with(INSTANCE_TYPE, None, tags, None)
 create_sagemaker_model.assert_called_with(
 instance_type=INSTANCE_TYPE,
 accelerator_type=None,
 tags=tags,
 serverless_inference_config=None,
 )
 sagemaker_session.endpoint_from_production_variants.assert_called_with(
 name=ENDPOINT_NAME,
 production_variants=[BASE_PRODUCTION_VARIANT],
Expand DownExpand Up@@ -463,7 +473,12 @@ def test_deploy_serverless_inference(production_variant, create_sagemaker_model,
 serverless_inference_config=serverless_inference_config,
 )

 create_sagemaker_model.assert_called_with(None, None, None, serverless_inference_config)
 create_sagemaker_model.assert_called_with(
 instance_type=None,
 accelerator_type=None,
 tags=None,
 serverless_inference_config=serverless_inference_config,
 )
 production_variant.assert_called_with(
 MODEL_NAME,
 None,
Expand Down

2 changes: 1 addition & 1 deletion
tests/unit/sagemaker/model/test_model_package.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -197,7 +197,7 @@ def test_create_sagemaker_model_include_tags(sagemaker_session):
 sagemaker_session=sagemaker_session,
 )

 model_package._create_sagemaker_model(tags=tags)
 model_package.deploy(tags=tags, instance_type="ml.p2.xlarge", initial_instance_count=1)

 sagemaker_session.create_model.assert_called_with(
 model_name,
Expand Down