API Reference
=============

This reference is generated from source docstrings and grouped by workflow. Use
:doc:`world_models_guide` for conceptual explanations and this page for exact
classes, functions, and module-level APIs.

Public package surface
----------------------

These modules expose the most common imports and lazy constructors.

Use ``synora`` for common workflows::

   import synora
   agent = synora.create_model("dreamer", env="walker-walk")

**Primary modules:** ``synora``, ``synora.models``, ``synora.configs``, ``synora.catalog``, and ``synora.envs``.

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.. automodule:: synora.models
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Model catalog
-------------

Core model families
~~~~~~~~~~~~~~~~~~~

**Key classes:** ``Dreamer``, ``DreamerAgent``, ``RSSM``, ``RecurrentStateSpaceModel``, ``Planet``, ``ModularRSSM``, ``JEPAAgent``, ``VisionTransformer``, ``IRISAgent``, ``IRISTransformer``, ``IRISWorldModel``, ``Genie``, ``LatentActionModel``, and ``DynamicsModel``.

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.. automodule:: synora.models.modular_rssm
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.. automodule:: synora.models.jepa_agent
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.. automodule:: synora.models.vit
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.. automodule:: synora.models.iris_agent
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Diffusion and DIAMOND components
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Key classes:** ``DiamondAgent``, ``DDPM``, ``DiT``, ``DiffusionUNet``, ``EDMPreconditioner``, ``EulerSampler``, ``RewardTerminationModel``, and ``ActorCriticNetwork``.

DIAMOND exposes ``DiamondAgent`` from ``synora.training.train_diamond``; there is no separate ``DIAMONDAgent`` class name in the package.

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Vision, tokenization, and layers
--------------------------------

**Key classes:** ``ConvEncoder``, ``ConvDecoder``, ``DenseDecoder``, ``ActionDecoder``, ``CNNEncoder``, ``CNNDecoder``, ``IRISEncoder``, ``IRISDecoder``, ``DiscreteAutoencoder``, ``VectorQuantizer``, ``VectorQuantizerEMA``, ``VideoTokenizer``, ``MultiHeadSelfAttention``, and ``STTransformer``.

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.. automodule:: synora.vision.video_tokenizer
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.. automodule:: synora.blocks
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Configuration objects
---------------------

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Training entry points
---------------------

**Key classes and functions:** ``DiamondAgent``, ``train_diamond``, ``train_dreamer``, ``GenieTrainer``, ``IRISTrainer``, and related training entry points.

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Memory and controllers
----------------------

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Datasets, environments, and transforms
--------------------------------------

Environment adapters
~~~~~~~~~~~~~~~~~~~~

The environment APIs below mirror the dedicated environment guide pages: DMC,
DeepMind Lab, Gym/Gymnasium, Atari/ALE, Procgen, MuJoCo, Unity ML-Agents, and vectorization utilities.
DIAMOND-style Atari support is intentionally not listed as an environment
adapter because it is Atari preprocessing rather than a separate environment
family.

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Atari preprocessing helpers
~~~~~~~~~~~~~~~~~~~~~~~~~~~

These helpers wrap Atari environments for specific training recipes. They are
not separate environment families.

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Datasets and transforms
~~~~~~~~~~~~~~~~~~~~~~~

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Masking and JEPA helpers
------------------------

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Benchmarks and reports
----------------------

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Utilities
---------

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