Diffusers documentation

Outputs

Diffusers

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Outputs

All model 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:

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:

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):

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.

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