credit.preblock.concat
======================

.. py:module:: credit.preblock.concat


Classes
-------

.. autoapisummary::

   credit.preblock.concat.ConcatToTensor


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

.. py:class:: ConcatToTensor(*args: Any, **kwargs: Any)

   Bases: :py:obj:`credit.preblock.base.BasePreblock`


   End-of-chain preblock that concatenates a nested batch dict of tensors
   into a single input tensor (and optionally a target tensor).

   Expects a batch dict of the form::

       batch[source][data_type][var_name] -> torch.Tensor

   where tensor shapes are (batch, channel, time, lon, lat) and concatenation
   is performed along dim=1 (channel). Traversal order follows key insertion
   order: for each source, all var_names under a data_type are concatenated,
   then the next source, and so on.

   ``metadata`` keys are passed through as-is (not concatenated).

   Returns either::

       (input_tensor, metadata)                    # if no "target" data_type present
       (input_tensor, target_tensor, metadata)     # if "target" is present

   Example config::

       type: "concatenate_to_tensor"
       args: {}


   .. py:method:: forward(batch)