> For the complete documentation index, see [llms.txt](https://boinc-ai.gitbook.io/diffusers/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://boinc-ai.gitbook.io/diffusers/api/main-classes/outputs.md).

# Outputs

## Outputs

All models outputs are subclasses of [BaseOutput](https://huggingface.co/docs/diffusers/v0.21.0/en/api/outputs#diffusers.utils.BaseOutput), data structures containing all the information returned by the model. The outputs can also be used as tuples or dictionaries.

For example:

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```
from diffusers import DDIMPipeline

pipeline = DDIMPipeline.from_pretrained("google/ddpm-cifar10-32")
outputs = pipeline()
```

The `outputs` object is a [ImagePipelineOutput](https://huggingface.co/docs/diffusers/v0.21.0/en/api/pipelines/latent_diffusion_uncond#diffusers.ImagePipelineOutput) which means it has an image attribute.

You can access each attribute as you normally would or with a keyword lookup, and if that attribute is not returned by the model, you will get `None`:

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```
outputs.images
outputs["images"]
```

When considering the `outputs` object as a tuple, it only considers the attributes that don’t have `None` values. For instance, retrieving an image by indexing into it returns the tuple `(outputs.images)`:

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```
outputs[:1]
```

To check a specific pipeline or model output, refer to its corresponding API documentation.

### BaseOutput

#### class diffusers.utils.BaseOutput

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/diffusers/utils/outputs.py#L40)

( )

Base class for all model outputs as dataclass. Has a `__getitem__` that allows indexing by integer or slice (like a tuple) or strings (like a dictionary) that will ignore the `None` attributes. Otherwise behaves like a regular Python dictionary.

You can’t unpack a `BaseOutput` directly. Use the [to\_tuple()](https://huggingface.co/docs/diffusers/v0.21.0/en/api/outputs#diffusers.utils.BaseOutput.to_tuple) method to convert it to a tuple first.

**to\_tuple**

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/diffusers/utils/outputs.py#L104)

( )

Convert self to a tuple containing all the attributes/keys that are not `None`.

### ImagePipelineOutput

#### class diffusers.ImagePipelineOutput

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/diffusers/pipelines/pipeline_utils.py#L112)

( images: typing.Union\[typing.List\[PIL.Image.Image], numpy.ndarray] )

Parameters

* **images** (`List[PIL.Image.Image]` or `np.ndarray`) — List of denoised PIL images of length `batch_size` or NumPy array of shape `(batch_size, height, width, num_channels)`.

Output class for image pipelines.

### FlaxImagePipelineOutput

#### class diffusers.pipelines.pipeline\_flax\_utils.FlaxImagePipelineOutput

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/diffusers/pipelines/pipeline_flax_utils.py#L88)

( images: typing.Union\[typing.List\[PIL.Image.Image], numpy.ndarray] )

Parameters

* **images** (`List[PIL.Image.Image]` or `np.ndarray`) — List of denoised PIL images of length `batch_size` or NumPy array of shape `(batch_size, height, width, num_channels)`.

Output class for image pipelines.

**replace**

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/flax/struct.py#L111)

( \*\*updates )

“Returns a new object replacing the specified fields with new values.

### AudioPipelineOutput

#### class diffusers.AudioPipelineOutput

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/diffusers/pipelines/pipeline_utils.py#L126)

( audios: ndarray )

Parameters

* **audios** (`np.ndarray`) — List of denoised audio samples of a NumPy array of shape `(batch_size, num_channels, sample_rate)`.

Output class for audio pipelines.

### ImageTextPipelineOutput

#### class diffusers.ImageTextPipelineOutput

[\<source>](https://github.com/huggingface/diffusers/blob/v0.21.0/src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py#L55)

( images: typing.Union\[typing.List\[PIL.Image.Image], numpy.ndarray, NoneType]text: typing.Union\[typing.List\[str], typing.List\[typing.List\[str]], NoneType] )

Parameters

* **images** (`List[PIL.Image.Image]` or `np.ndarray`) — List of denoised PIL images of length `batch_size` or NumPy array of shape `(batch_size, height, width, num_channels)`.
* **text** (`List[str]` or `List[List[str]]`) — List of generated text strings of length `batch_size` or a list of list of strings whose outer list has length `batch_size`.

Output class for joint image-text pipelines.


---

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