:py:mod:`anomalib.models.components.base.anomaly_module`
========================================================

.. py:module:: anomalib.models.components.base.anomaly_module

.. autoapi-nested-parse::

   Base Anomaly Module for Training Task.



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

Classes
~~~~~~~

.. autoapisummary::

   anomalib.models.components.base.anomaly_module.AnomalyModule




Attributes
~~~~~~~~~~

.. autoapisummary::

   anomalib.models.components.base.anomaly_module.logger


.. py:data:: logger
   

   

.. py:class:: AnomalyModule

   Bases: :py:obj:`pytorch_lightning.LightningModule`, :py:obj:`abc.ABC`

   AnomalyModule to train, validate, predict and test images.

   Acts as a base class for all the Anomaly Modules in the library.

   .. py:method:: forward(batch)

      Forward-pass input tensor to the module.

      :param batch: Input Tensor
      :type batch: Tensor

      :returns: Output tensor from the model.
      :rtype: Tensor


   .. py:method:: validation_step(batch, batch_idx) -> dict
      :abstractmethod:

      To be implemented in the subclasses.


   .. py:method:: predict_step(batch: Any, batch_idx: int, _dataloader_idx: Optional[int] = None) -> Any

      Step function called during :meth:`~pytorch_lightning.trainer.trainer.Trainer.predict`.

      By default, it calls :meth:`~pytorch_lightning.core.lightning.LightningModule.forward`.
      Override to add any processing logic.

      :param batch: Current batch
      :type batch: Tensor
      :param batch_idx: Index of current batch
      :type batch_idx: int
      :param _dataloader_idx: Index of the current dataloader
      :type _dataloader_idx: int

      :returns: Predicted output


   .. py:method:: test_step(batch, _)

      Calls validation_step for anomaly map/score calculation.

      :param batch: Input batch
      :type batch: Tensor
      :param _: Index of the batch.

      :returns: Dictionary containing images, features, true labels and masks.
                These are required in `validation_epoch_end` for feature concatenation.


   .. py:method:: validation_step_end(val_step_outputs)

      Called at the end of each validation step.


   .. py:method:: test_step_end(test_step_outputs)

      Called at the end of each test step.


   .. py:method:: validation_epoch_end(outputs)

      Compute threshold and performance metrics.

      :param outputs: Batch of outputs from the validation step


   .. py:method:: test_epoch_end(outputs)

      Compute and save anomaly scores of the test set.

      :param outputs: Batch of outputs from the validation step


   .. py:method:: _compute_adaptive_threshold(outputs)


   .. py:method:: _collect_outputs(image_metric, pixel_metric, outputs)


   .. py:method:: _post_process(outputs)

      Compute labels based on model predictions.


   .. py:method:: _outputs_to_cpu(output)


   .. py:method:: _log_metrics()

      Log computed performance metrics.