docs/source/en/modular_diffusers/modular_diffusers_states.md

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# States

Blocks rely on the [`~modular_pipelines.PipelineState`] and [`~modular_pipelines.BlockState`] data structures for communicating and sharing data.

| State | Description |
|-------|-------------|
| [`~modular_pipelines.PipelineState`] | Maintains the overall data required for a pipeline's execution and allows blocks to read and update its data. |
| [`~modular_pipelines.BlockState`] | Allows each block to perform its computation with the necessary data from `inputs`|

This guide explains how states work and how they connect blocks.

## PipelineState

The [`~modular_pipelines.PipelineState`] is a global state container for all blocks. It maintains the complete runtime state of the pipeline and provides a structured way for blocks to read from and write to shared data.

There are two dict's in [`~modular_pipelines.PipelineState`] for structuring data.

- The `values` dict is a **mutable** state containing a copy of user provided input values and intermediate output values generated by blocks. If a block modifies an `input`, it will be reflected in the `values` dict after calling `set_block_state`.

```py
PipelineState(
  values={
    'prompt': 'a cat'
    'guidance_scale': 7.0
    'num_inference_steps': 25
    'prompt_embeds': Tensor(dtype=torch.float32, shape=torch.Size([1, 1, 1, 1]))
    'negative_prompt_embeds': None
  },
)
```

## BlockState

The [`~modular_pipelines.BlockState`] is a local view of the relevant variables an individual block needs from [`~modular_pipelines.PipelineState`] for performing it's computations.

Access these variables directly as attributes like `block_state.image`.

```py
BlockState(
    image: <PIL.Image.Image image mode=RGB size=512x512 at 0x7F3ECC494640>
)
```

When a block's `__call__` method is executed, it retrieves the [`BlockState`] with `self.get_block_state(state)`, performs it's operations, and updates [`~modular_pipelines.PipelineState`] with `self.set_block_state(state, block_state)`.

```py
def __call__(self, components, state):
    # retrieve BlockState
    block_state = self.get_block_state(state)

    # computation logic on inputs

    # update PipelineState
    self.set_block_state(state, block_state)
    return components, state
```

## State interaction

[`~modular_pipelines.PipelineState`] and [`~modular_pipelines.BlockState`] interaction is defined by a block's `inputs`, and `intermediate_outputs`.

- `inputs`, a block can modify an input - like `block_state.image` - and this change can be propagated globally to [`~modular_pipelines.PipelineState`] by calling `set_block_state`.
- `intermediate_outputs`, is a new variable that a block creates. It is added to the [`~modular_pipelines.PipelineState`]'s `values` dict and is available as for subsequent blocks or accessed by users as a final output from the pipeline.