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[Doc] minor improvements: move base NCO classes out
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fedebotu committed Apr 30, 2024
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7 changes: 4 additions & 3 deletions docs/_content/api/models/common/__init__.md
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We categorize NCO approaches (which are in fact not necessarily trained with RL!) into the following: 1) constructive, 2) improvement, 3) transductive.



```{eval-rst}
.. tip::
Note that in RL4CO we distinguish the RL algorithms and the actors via the following naming:
Expand All @@ -29,17 +30,17 @@ The following table contains the categorization that we follow in RL4CO:
- Input
- Output
- Description
* - Constructive
* - `Constructive <constructive.md>`_
- Policy
- Instance
- Solution
- Policies trained to generate solutions from scratch. Can be categorized into AutoRegressive (AR) and Non-Autoregressive (NAR).
* - Improvement
* - `Improvement <improvement.md>`_
- Policy
- Instance, Current Solution
- Improved Solution
- Policies trained to improve existing solutions iteratively, akin to local search algorithms. They focus on refining *existing* solutions rather than generating them from scratch.
* - Transductive
* - `Transductive <transductive.md>`_
- Model
- Instance, (Policy)
- Solution, (Updated Policy)
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3 changes: 3 additions & 0 deletions docs/_content/api/models/zoo/__init__.md
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# Model Zoo

Models from the literature and contributions are contained in the Model Zoo.
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# Model Zoo

Models from the literature and contributions are contained in the Model Zoo.

---

# Constructive Methods

These can be classified into Auto-Regressive (AR) and Non-Auto-Regressive (NAR) policies. These constructive methods also include ad-hoc RL algorithms for constructive policies.
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.. automodule:: rl4co.models.zoo.nargnn.encoder
:members:
:undoc-members:
```

---

# Improvement Methods

These methods are trained to improve existing solutions iteratively, akin to local search algorithms. They focus on refining existing solutions rather than generating them from scratch.

_coming soon!_


---

# Transductive Methods

These methods update policy parameters during online testing to improve the solutions of a specific instance.

## Active Search (AS)

```{eval-rst}
.. automodule:: rl4co.models.zoo.active_search.search
:members:
:undoc-members:
```

## Efficent Active Search (EAS)

```{eval-rst}
.. automodule:: rl4co.models.zoo.eas.search
:members:
:undoc-members:
```

```{eval-rst}
.. automodule:: rl4co.models.zoo.eas.decoder
:members:
:undoc-members:
```

```{eval-rst}
.. automodule:: rl4co.models.zoo.eas.nn
:members:
:undoc-members:
```
5 changes: 5 additions & 0 deletions docs/_content/api/models/zoo/improvement.md
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# Improvement Methods

These methods are trained to improve existing solutions iteratively, akin to local search algorithms. They focus on refining existing solutions rather than generating them from scratch.

_coming soon!_
31 changes: 31 additions & 0 deletions docs/_content/api/models/zoo/transductive.md
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# Transductive Methods

These methods update policy parameters during online testing to improve the solutions of a specific instance.

## Active Search (AS)

```{eval-rst}
.. automodule:: rl4co.models.zoo.active_search.search
:members:
:undoc-members:
```

## Efficent Active Search (EAS)

```{eval-rst}
.. automodule:: rl4co.models.zoo.eas.search
:members:
:undoc-members:
```

```{eval-rst}
.. automodule:: rl4co.models.zoo.eas.decoder
:members:
:undoc-members:
```

```{eval-rst}
.. automodule:: rl4co.models.zoo.eas.nn
:members:
:undoc-members:
```
7 changes: 5 additions & 2 deletions docs/index.md
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Expand Up @@ -37,6 +37,7 @@ RL4CO is built upon:
_content/start/installation
_collections/1-quickstart
_content/start/hydra
_content/api/models/common/__init__
.. toctree::
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:maxdepth: 3
:caption: Base NCO Methods
_content/api/models/common/__init__
_content/api/models/common/constructive
_content/api/models/common/improvement
_content/api/models/common/transductive
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:maxdepth: 3
:caption: Model Zoo
_content/api/models/zoo
_content/api/models/common/zoo/__init__
_content/api/models/common/zoo/constructive
_content/api/models/common/zoo/improvement
_content/api/models/common/zoo/transductive
.. toctree::
:maxdepth: 3
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