[Docs] Convert rST to MyST (Markdown) (#11145)

Signed-off-by: Rafael Vasquez <rafvasq21@gmail.com>
This commit is contained in:
Rafael Vasquez
2024-12-23 17:35:38 -05:00
committed by GitHub
parent 94d545a1a1
commit 32aa2059ad
167 changed files with 7863 additions and 8131 deletions

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(input-processing-pipeline)=
# Input Processing Pipeline
1. Input data is passed to {class}`~vllm.LLMEngine` (or {class}`~vllm.AsyncLLMEngine`).
2. Tokenize the data if necessary.
3. Process the inputs using {meth}`INPUT_REGISTRY.process_input <vllm.inputs.registry.InputRegistry.process_input>`.
- For example, add placeholder tokens to reserve KV cache for multi-modal embeddings.
4. Send the processed inputs to {class}`~vllm.executor.executor_base.ExecutorBase`.
5. Distribute the inputs via {class}`~vllm.worker.worker_base.WorkerBase` to {class}`~vllm.worker.model_runner_base.ModelRunnerBase`.
6. If the data contains multi-modal data, convert it into keyword arguments using {meth}`MULTIMODAL_REGISTRY.map_input <vllm.multimodal.MultiModalRegistry.map_input>`.
- For example, convert a {class}`PIL.Image.Image` input to its pixel values for a vision model.

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.. _input_processing_pipeline:
Input Processing Pipeline
=========================
1. Input data is passed to :class:`~vllm.LLMEngine` (or :class:`~vllm.AsyncLLMEngine`).
2. Tokenize the data if necessary.
3. Process the inputs using :meth:`INPUT_REGISTRY.process_input <vllm.inputs.registry.InputRegistry.process_input>`.
- For example, add placeholder tokens to reserve KV cache for multi-modal embeddings.
4. Send the processed inputs to :class:`~vllm.executor.executor_base.ExecutorBase`.
5. Distribute the inputs via :class:`~vllm.worker.worker_base.WorkerBase` to :class:`~vllm.worker.model_runner_base.ModelRunnerBase`.
6. If the data contains multi-modal data, convert it into keyword arguments using :meth:`MULTIMODAL_REGISTRY.map_input <vllm.multimodal.MultiModalRegistry.map_input>`.
- For example, convert a :class:`PIL.Image.Image` input to its pixel values for a vision model.

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(input-processing)=
# Input Processing
```{eval-rst}
.. currentmodule:: vllm.inputs
```
Each model can override parts of vLLM's [input processing pipeline](#input-processing-pipeline) via
{data}`~vllm.inputs.INPUT_REGISTRY` and {data}`~vllm.multimodal.MULTIMODAL_REGISTRY`.
Currently, this mechanism is only utilized in [multi-modal](#multi-modality) models for preprocessing multi-modal input
data in addition to input prompt, but it can be extended to text-only language models when needed.
## Guides
```{toctree}
:maxdepth: 1
input_processing_pipeline
```
## Module Contents
### LLM Engine Inputs
```{eval-rst}
.. autoclass:: vllm.inputs.DecoderOnlyInputs
:members:
:show-inheritance:
```
### Registry
```{eval-rst}
.. autodata:: vllm.inputs.INPUT_REGISTRY
```
```{eval-rst}
.. automodule:: vllm.inputs.registry
:members:
:show-inheritance:
```

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.. _input_processing:
Input Processing
================
.. currentmodule:: vllm.inputs
Each model can override parts of vLLM's :ref:`input processing pipeline <input_processing_pipeline>` via
:data:`~vllm.inputs.INPUT_REGISTRY` and :data:`~vllm.multimodal.MULTIMODAL_REGISTRY`.
Currently, this mechanism is only utilized in :ref:`multi-modal <multi_modality>` models for preprocessing multi-modal input
data in addition to input prompt, but it can be extended to text-only language models when needed.
Guides
++++++
.. toctree::
:maxdepth: 1
input_processing_pipeline
Module Contents
+++++++++++++++
LLM Engine Inputs
-----------------
.. autoclass:: vllm.inputs.DecoderOnlyInputs
:members:
:show-inheritance:
Registry
--------
.. autodata:: vllm.inputs.INPUT_REGISTRY
.. automodule:: vllm.inputs.registry
:members:
:show-inheritance: