跳转至

Outputs

译者：片刻小哥哥

项目地址：https://huggingface.apachecn.org/docs/diffusers/api/outputs

原始地址：https://huggingface.co/docs/diffusers/api/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:

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

](https://github.com/huggingface/diffusers/blob/v0.23.0/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() method to convert it to a tuple first.

to_tuple

[<

source

](https://github.com/huggingface/diffusers/blob/v0.23.0/src/diffusers/utils/outputs.py#L126)

(

)

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/v0.23.0/src/diffusers/pipelines/pipeline_utils.py#L110)

(

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/v0.23.0/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/v0.23.0/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/v0.23.0/src/diffusers/pipelines/pipeline_utils.py#L124)

(

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/v0.23.0/src/diffusers/pipelines/unidiffuser/pipeline_unidiffuser.py#L34)

(

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.

回到顶部