Outputs

Outputs

All models outputs are subclasses of 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 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>

( )

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() method to convert it to a tuple first.

to_tuple

<source>

( )

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

ImagePipelineOutput

class diffusers.ImagePipelineOutput

<source>

( 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>

( 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>

( **updates )

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

AudioPipelineOutput

class diffusers.AudioPipelineOutput

<source>

( 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>

( 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.