[AQUA] Added support for deploy stack model. #1223
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| Union[DataScienceModel, DataScienceModelGroup] | ||
| The instance of DataScienceModel or DataScienceModelGroup. | ||
| """ | ||
| fine_tune_weights = ( |
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looks like there are several place where we do same validation. Wouldn't it be better to have something like:
if isinstance(model_id, AquaMultiModelRef):
....
else:
....
| f"Aqua Model {custom_model.id} created with the service model {model_id}." | ||
| ) | ||
| custom_model = None | ||
| if fine_tune_weights: |
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Wouldn’t it be better, instead of handling everything in one place, to split the implementation into two separate methods, one for creating the MC record and another for creating the group?
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Because creating model or model group will share some configs, like compartment/project/all tags, that's why I put it in one method. I just created separate helper functions for each creation.
| if create_deployment_details.model_id: | ||
| if ( | ||
| create_deployment_details.model_id | ||
| or create_deployment_details.deployment_type == DEFAULT_DEPLOYMENT_TYPE |
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I think this is a bit dangerous, what if someone change the default deployment type?
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We can add a validation for it and only MODEL_STACK is supported at this moment.
| model_app = AquaModelApp() | ||
| if create_deployment_details.model_id: | ||
| if ( | ||
| create_deployment_details.model_id |
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I think this assumption is a bit wrong, no?
create_deployment_details.model_id can be provided only for a single model deployment. In case of MMD or Stacked deployment we should rely on create_deployment_details.models, no?
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I think we talked about this before, that is for single dployment, we adopt model_id and for stacked deployment, we adopt models with deployment_type. This assumption will filter out both single and stack deployment cases.
| build_model_group_details = copy.deepcopy(self._spec) | ||
| build_model_group_details.pop(self.CONST_CUSTOM_METADATA_LIST) | ||
| build_model_group_details.pop(self.CONST_MEMBER_MODELS) | ||
| build_model_group_details.pop(self.CONST_CUSTOM_METADATA_LIST, None) |
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Add a comment here, why we are doing this?
| is not None | ||
| or service_model.freeform_tags.get(Tags.AQUA_FINE_TUNED_MODEL_TAG) | ||
| is not None | ||
| ): |
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NIT: if (
service_model.freeform_tags.get(Tags.BASE_MODEL_CUSTOM) is None and
service_model.freeform_tags.get(Tags.AQUA_FINE_TUNED_MODEL_TAG) is None
):
| for fine_tune_weight in fine_tune_weights | ||
| ] | ||
| ) | ||
| .create() |
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so is this only for 1 FT model + multiple LoRA modules?
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Only one base model + multiple LoRA modules
| defined_tags: Optional[Dict] = None, | ||
| **kwargs, | ||
| ) -> DataScienceModel: | ||
| ) -> Union[DataScienceModel, DataScienceModelGroup]: |
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Myabe we can rename model_id to model now, it would make sense for me, but I guess will require some changes to the unit tests.
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Added support for deploy stack model.
MODEL_STACKas single model deployment using model groupmodelsanddeployment_type=MODEL_STACKtocreateat the same time will trigger this type of deploymentMODELwill be added and the--served-model-nameinPARAMSwill be updated to the model id.Integration tests
Unit tests