azure.ai.ml.entities.ModelPackage.yml

### YamlMime:PythonClass
uid: azure.ai.ml.entities.ModelPackage
name: ModelPackage
fullName: azure.ai.ml.entities.ModelPackage
module: azure.ai.ml.entities
inheritances:
- azure.ai.ml.entities._resource.Resource
- azure.ai.ml._restclient.v2023_08_01_preview.models._models_py3.PackageRequest
summary: '> [!NOTE]

  > This is an experimental class, and may change at any time. Please see [https://aka.ms/azuremlexperimental](https://aka.ms/azuremlexperimental)
  for more information.

  >


  Model package.'
constructor:
  syntax: 'ModelPackage(*, target_environment: str | Dict[str, str], inferencing_server:
    AzureMLOnlineInferencingServer | AzureMLBatchInferencingServer, base_environment_source:
    BaseEnvironment | None = None, environment_variables: Dict[str, str] | None =
    None, inputs: List[ModelPackageInput] | None = None, model_configuration: ModelConfiguration
    | None = None, tags: Dict[str, str] | None = None, **kwargs: Any)'
  parameters:
  - name: target_environment_name
    description: The target environment name for the model package.
    isRequired: true
    types:
    - <xref:str>
  - name: inferencing_server
    description: The inferencing server of the model package.
    isRequired: true
    types:
    - <xref:typing.Union>[<xref:azure.ai.ml.entities.AzureMLOnlineInferencingServer>,
      <xref:azure.ai.ml.entities.AzureMLBatchInferencingServer>]
  - name: base_environment_source
    description: The base environment source of the model package.
    isRequired: true
    types:
    - <xref:typing.Optional>[<xref:azure.ai.ml.entities.BaseEnvironment>]
  - name: target_environment_version
    description: The version of the model package.
    isRequired: true
    types:
    - <xref:typing.Optional>[<xref:str>]
  - name: environment_variables
    description: The environment variables of the model package.
    isRequired: true
    types:
    - <xref:typing.Optional>[<xref:dict>[<xref:str>, <xref:str>]]
  - name: inputs
    description: The inputs of the model package.
    isRequired: true
    types:
    - <xref:typing.Optional>[<xref:list>[<xref:azure.ai.ml.entities.ModelPackageInput>]]
  - name: model_configuration
    description: The model configuration.
    isRequired: true
    types:
    - <xref:typing.Optional>[<xref:azure.ai.ml.entities.ModelConfiguration>]
  - name: tags
    description: The tags of the model package.
    isRequired: true
    types:
    - <xref:typing.Optional>[<xref:dict>[<xref:str>, <xref:str>]]
examples:
- "Create a Model Package object.<!--[!code-python[Main](les\\ml_samples_misc.py )]-->\n\
  \n<!-- literal_block {\"ids\": [], \"classes\": [], \"names\": [], \"dupnames\"\
  : [], \"backrefs\": [], \"source\": \"C:\\\\hostedtoolcache\\\\windows\\\\Python\\\
  \\3.11.9\\\\x64\\\\Lib\\\\site-packages\\\\py2docfx\\\\dist_temp\\\\10\\\\azure-ai-ml-1.16.0\\\
  \\samples\\\\ml_samples_misc.py\", \"xml:space\": \"preserve\", \"force\": false,\
  \ \"language\": \"python\", \"highlight_args\": {\"linenostart\": 1}, \"linenos\"\
  : false} -->\n\n````python\n\n   from azure.ai.ml.entities import AzureMLOnlineInferencingServer,\
  \ CodeConfiguration, ModelPackage\n\n   modelPackage = ModelPackage(\n       inferencing_server=AzureMLOnlineInferencingServer(\n\
  \           code_configuration=CodeConfiguration(code=\"../model-1/foo/\", scoring_script=\"\
  score.py\")\n       ),\n       target_environment_name=\"env-name\",\n       target_environment_version=\"\
  1.0\",\n       environment_variables={\"env1\": \"value1\", \"env2\": \"value2\"\
  },\n       tags={\"tag1\": \"value1\", \"tag2\": \"value2\"},\n   )\n\n   ````\n"
methods:
- uid: azure.ai.ml.entities.ModelPackage.as_dict
  name: as_dict
  summary: "Return a dict that can be JSONify using json.dump.\n\nAdvanced usage might\
    \ optionally use a callback as parameter:\n\nKey is the attribute name used in\
    \ Python. Attr_desc\nis a dict of metadata. Currently contains 'type' with the\n\
    msrest type and 'key' with the RestAPI encoded key.\nValue is the current value\
    \ in this object.\n\nThe string returned will be used to serialize the key.\n\
    If the return type is a list, this is considered hierarchical\nresult dict.\n\n\
    See the three examples in this file:\n\n* attribute_transformer \n\n* full_restapi_key_transformer\
    \ \n\n* last_restapi_key_transformer \n\nIf you want XML serialization, you can\
    \ pass the kwargs is_xml=True."
  signature: as_dict(keep_readonly=True, key_transformer=<function attribute_transformer>,
    **kwargs)
  parameters:
  - name: key_transformer
    description: A key transformer function.
    types:
    - <xref:function>
  - name: keep_readonly
    defaultValue: 'True'
  return:
    description: A dict JSON compatible object
    types:
    - <xref:dict>
- uid: azure.ai.ml.entities.ModelPackage.deserialize
  name: deserialize
  summary: Parse a str using the RestAPI syntax and return a model.
  signature: deserialize(data, content_type=None)
  parameters:
  - name: data
    description: A str using RestAPI structure. JSON by default.
    isRequired: true
    types:
    - <xref:str>
  - name: content_type
    description: JSON by default, set application/xml if XML.
    defaultValue: None
    types:
    - <xref:str>
  return:
    description: An instance of this model
  exceptions:
  - type: DeserializationError if something went wrong
- uid: azure.ai.ml.entities.ModelPackage.dump
  name: dump
  summary: Dumps the job content into a file in YAML format.
  signature: 'dump(dest: str | PathLike | IO, **kwargs: Any) -> None'
  parameters:
  - name: dest
    description: 'The local path or file stream to write the YAML content to.

      If dest is a file path, a new file will be created.

      If dest is an open file, the file will be written to directly.'
    isRequired: true
    types:
    - <xref:typing.Union>[<xref:PathLike>, <xref:str>, <xref:typing.IO>[<xref:typing.AnyStr>]]
  exceptions:
  - type: FileExistsError
    description: Raised if dest is a file path and the file already exists.
  - type: IOError
    description: Raised if dest is an open file and the file is not writable.
- uid: azure.ai.ml.entities.ModelPackage.enable_additional_properties_sending
  name: enable_additional_properties_sending
  signature: enable_additional_properties_sending()
- uid: azure.ai.ml.entities.ModelPackage.from_dict
  name: from_dict
  summary: 'Parse a dict using given key extractor return a model.


    By default consider key

    extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor

    and last_rest_key_case_insensitive_extractor)'
  signature: from_dict(data, key_extractors=None, content_type=None)
  parameters:
  - name: data
    description: A dict using RestAPI structure
    isRequired: true
    types:
    - <xref:dict>
  - name: content_type
    description: JSON by default, set application/xml if XML.
    defaultValue: None
    types:
    - <xref:str>
  - name: key_extractors
    defaultValue: None
  return:
    description: An instance of this model
  exceptions:
  - type: DeserializationError if something went wrong
- uid: azure.ai.ml.entities.ModelPackage.is_xml_model
  name: is_xml_model
  signature: is_xml_model()
- uid: azure.ai.ml.entities.ModelPackage.serialize
  name: serialize
  summary: 'Return the JSON that would be sent to azure from this model.


    This is an alias to *as_dict(full_restapi_key_transformer, keep_readonly=False)*.


    If you want XML serialization, you can pass the kwargs is_xml=True.'
  signature: serialize(keep_readonly=False, **kwargs)
  parameters:
  - name: keep_readonly
    description: If you want to serialize the readonly attributes
    defaultValue: 'False'
    types:
    - <xref:bool>
  return:
    description: A dict JSON compatible object
    types:
    - <xref:dict>
- uid: azure.ai.ml.entities.ModelPackage.validate
  name: validate
  summary: Validate this model recursively and return a list of ValidationError.
  signature: validate()
  return:
    description: A list of validation error
    types:
    - <xref:list>
attributes:
- uid: azure.ai.ml.entities.ModelPackage.base_path
  name: base_path
  summary: The base path of the resource.
  return:
    description: The base path of the resource.
    types:
    - <xref:str>
- uid: azure.ai.ml.entities.ModelPackage.creation_context
  name: creation_context
  summary: The creation context of the resource.
  return:
    description: The creation metadata for the resource.
    types:
    - <xref:typing.Optional>[<xref:azure.ai.ml.entities.SystemData>]
- uid: azure.ai.ml.entities.ModelPackage.id
  name: id
  summary: The resource ID.
  return:
    description: The global ID of the resource, an Azure Resource Manager (ARM) ID.
    types:
    - <xref:typing.Optional>[<xref:str>]