Layers API Reference
====================

All layers are importable directly from ``idx_flow``. Internally they live in
separate modules (``conv``, ``mlp``, ``norm``, ``regularization``, ``attention``,
``vit``, ``pooling``, ``functional``).

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Convolution Layers
------------------

SpatialConv
^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialConv
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SpatialTransposeConv
^^^^^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialTransposeConv
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SpatialUpsampling
^^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialUpsampling
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MLP Layers
----------

SpatialMLP
^^^^^^^^^^

.. autoclass:: idx_flow.SpatialMLP
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GlobalMLP
^^^^^^^^^

.. autoclass:: idx_flow.GlobalMLP
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Normalization Layers
--------------------

SpatialBatchNorm
^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialBatchNorm
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SpatialLayerNorm
^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialLayerNorm
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SpatialInstanceNorm
^^^^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialInstanceNorm
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SpatialGroupNorm
^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialGroupNorm
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Regularization Layers
---------------------

SpatialDropout
^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialDropout
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ChannelDropout
^^^^^^^^^^^^^^

.. autoclass:: idx_flow.ChannelDropout
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Attention Layers
----------------

SpatialSelfAttention
^^^^^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialSelfAttention
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Vision Transformer Layers
-------------------------

SpatialPatchEmbedding
^^^^^^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialPatchEmbedding
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SpatialTransformerBlock
^^^^^^^^^^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialTransformerBlock
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SpatialViT
^^^^^^^^^^

.. autoclass:: idx_flow.SpatialViT
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Pooling and Utility Layers
--------------------------

SpatialPooling
^^^^^^^^^^^^^^

.. autoclass:: idx_flow.SpatialPooling
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Squeeze
^^^^^^^

.. autoclass:: idx_flow.Squeeze
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Unsqueeze
^^^^^^^^^

.. autoclass:: idx_flow.Unsqueeze
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Functional Utilities
--------------------

get_initializer
^^^^^^^^^^^^^^^

.. autofunction:: idx_flow.get_initializer

get_activation
^^^^^^^^^^^^^^

.. autofunction:: idx_flow.get_activation

Type Aliases
^^^^^^^^^^^^

.. py:data:: idx_flow.InitMethod

   Weight initialization methods:
   ``"xavier_uniform"``, ``"xavier_normal"``, ``"kaiming_uniform"``,
   ``"kaiming_normal"``, ``"orthogonal"``, ``"normal"``, ``"uniform"``, ``"zeros"``

.. py:data:: idx_flow.ActivationType

   Activation functions:
   ``"relu"``, ``"selu"``, ``"leaky_relu"``, ``"gelu"``, ``"elu"``,
   ``"tanh"``, ``"sigmoid"``, ``"swish"``, ``"mish"``, ``"linear"``

.. py:data:: idx_flow.InterpolationMethod

   Interpolation methods:
   ``"linear"``, ``"idw"``, ``"gaussian"``

.. py:data:: idx_flow.PoolingMethod

   Pooling methods:
   ``"mean"``, ``"max"``, ``"sum"``

.. py:data:: idx_flow.AttnBackend

   Attention computation backends:
   ``"auto"`` (SDPA when available, else manual),
   ``"sdpa"`` (force scaled_dot_product_attention, requires PyTorch >= 2.0),
   ``"manual"`` (explicit matmul-softmax-matmul)