cellmap_flow.models.cellmap_models ================================== .. py:module:: cellmap_flow.models.cellmap_models Attributes ---------- .. autoapisummary:: cellmap_flow.models.cellmap_models.ort cellmap_flow.models.cellmap_models.torch Classes ------- .. autoapisummary:: cellmap_flow.models.cellmap_models.ModelMetadata cellmap_flow.models.cellmap_models.CellmapModel cellmap_flow.models.cellmap_models.CellmapModels Module Contents --------------- .. py:data:: ort :value: None .. py:data:: torch :value: None .. py:class:: ModelMetadata(/, **data: Any) !!! abstract "Usage Documentation" [Models](../concepts/models.md) A base class for creating Pydantic models. .. attribute:: __class_vars__ The names of the class variables defined on the model. .. attribute:: __private_attributes__ Metadata about the private attributes of the model. .. attribute:: __signature__ The synthesized `__init__` [`Signature`][inspect.Signature] of the model. .. attribute:: __pydantic_complete__ Whether model building is completed, or if there are still undefined fields. .. attribute:: __pydantic_core_schema__ The core schema of the model. .. attribute:: __pydantic_custom_init__ Whether the model has a custom `__init__` function. .. attribute:: __pydantic_decorators__ Metadata containing the decorators defined on the model. This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1. .. attribute:: __pydantic_generic_metadata__ Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these. .. attribute:: __pydantic_parent_namespace__ Parent namespace of the model, used for automatic rebuilding of models. .. attribute:: __pydantic_post_init__ The name of the post-init method for the model, if defined. .. attribute:: __pydantic_root_model__ Whether the model is a [`RootModel`][pydantic.root_model.RootModel]. .. attribute:: __pydantic_serializer__ The `pydantic-core` `SchemaSerializer` used to dump instances of the model. .. attribute:: __pydantic_validator__ The `pydantic-core` `SchemaValidator` used to validate instances of the model. .. attribute:: __pydantic_fields__ A dictionary of field names and their corresponding [`FieldInfo`][pydantic.fields.FieldInfo] objects. .. attribute:: __pydantic_computed_fields__ A dictionary of computed field names and their corresponding [`ComputedFieldInfo`][pydantic.fields.ComputedFieldInfo] objects. .. attribute:: __pydantic_extra__ A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra] is set to `'allow'`. .. attribute:: __pydantic_fields_set__ The names of fields explicitly set during instantiation. .. attribute:: __pydantic_private__ Values of private attributes set on the model instance. .. py:attribute:: model_name :type: Optional[str] :value: None .. py:attribute:: model_type :type: Optional[str] :value: None .. py:attribute:: framework :type: Optional[str] :value: None .. py:attribute:: spatial_dims :type: Optional[int] :value: None .. py:attribute:: in_channels :type: Optional[int] :value: None .. py:attribute:: out_channels :type: Optional[int] :value: None .. py:attribute:: iteration :type: Optional[int] :value: None .. py:attribute:: input_voxel_size :type: Optional[List[int]] :value: None .. py:attribute:: output_voxel_size :type: Optional[List[int]] :value: None .. py:attribute:: channels_names :type: Optional[List[str]] :value: None .. py:attribute:: input_shape :type: Optional[List[int]] :value: None .. py:attribute:: output_shape :type: Optional[List[int]] :value: None .. py:attribute:: inference_input_shape :type: Optional[List[int]] :value: None .. py:attribute:: inference_output_shape :type: Optional[List[int]] :value: None .. py:attribute:: author :type: Optional[str] :value: None .. py:attribute:: description :type: Optional[str] :value: None .. py:attribute:: version :type: Optional[str] :value: None .. py:class:: CellmapModel(folder_path: str) Represents a single model directory. Lazily loads: - metadata.json --> pydantic ModelMetadata - model.onnx --> ONNX model session (if onnxruntime is available) - model.pt --> PyTorch model (if torch is available) - model.ts --> TorchScript model (if torch is available) - README.md --> str .. py:attribute:: folder_path .. py:property:: metadata :type: ModelMetadata Lazy load the metadata.json file and parse it into a ModelMetadata object. .. py:property:: onnx_model If 'model.onnx' exists, lazily load it as an ONNX Runtime InferenceSession. Use GPU if available (requires onnxruntime-gpu installed), otherwise CPU. Returns None if the file doesn't exist or onnxruntime isn't installed. .. py:property:: pytorch_model If 'model.pt' exists, lazily load it using torch.load(). Returns None if the file doesn't exist or PyTorch isn't installed. NOTE: Adjust this for how your .pt was saved (entire model vs state_dict). .. py:property:: ts_model If 'model.ts' exists, lazily load it using torch.jit.load(). Returns None if the file doesn't exist or PyTorch isn't installed. .. py:property:: readme :type: Optional[str] Lazy load the README.md content if it exists, else None. .. py:class:: CellmapModels(root_dir: str) A container that discovers all subfolders in the given directory and provides them as model attributes. .. py:attribute:: root_dir .. py:method:: list_models() -> List[str] Returns the list of detected model names (subfolder names that contain 'metadata.json').