czbenchmarks.models.validators.base_model_validator
===================================================

.. py:module:: czbenchmarks.models.validators.base_model_validator


Attributes
----------

.. autoapisummary::

   czbenchmarks.models.validators.base_model_validator.logger


Classes
-------

.. autoapisummary::

   czbenchmarks.models.validators.base_model_validator.BaseModelValidator


Module Contents
---------------

.. py:data:: logger

.. py:class:: BaseModelValidator

   Bases: :py:obj:`abc.ABC`


   Abstract base class for model validators.

   Defines the interface for validating datasets against model requirements.
   Validators ensure datasets meet model-specific requirements like:
   - Compatible data types
   - Required metadata fields
   - Organism compatibility
   - Feature name formats

   Each validator must:
   1. Define a dataset_type class variable
   2. Define a model_type class variable or model_name property
   3. Implement _validate_dataset, inputs, and outputs


   .. py:attribute:: dataset_type
      :type:  ClassVar[Type[czbenchmarks.datasets.BaseDataset]]


   .. py:attribute:: model_type
      :type:  ClassVar[czbenchmarks.models.types.ModelType]


   .. py:method:: __init_subclass__() -> None
      :classmethod:


      Validate that subclasses define required class variables and
      follow naming conventions.

      :raises TypeError: If required class variables are missing or invalid
      :raises ValueError: If class naming doesn't follow conventions



   .. py:property:: inputs
      :type: Set[czbenchmarks.datasets.DataType]

      :abstractmethod:


      Required input data types this model requires.

      :returns: Set of required DataType enums


   .. py:property:: outputs
      :type: Set[czbenchmarks.datasets.DataType]

      :abstractmethod:


      Output data types produced by this model.

      :returns: Set of output DataType enums


   .. py:method:: validate_dataset(dataset: czbenchmarks.datasets.BaseDataset)

      Validate a dataset meets all model requirements.

      Checks:
      1. Dataset type matches model requirements
      2. Required inputs are available
      3. Model-specific validation rules

      :param dataset: Dataset to validate

      :raises ValueError: If validation fails