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| # BaseOutputs | |
| All models have outputs that are instances of subclasses of [`~utils.BaseOutput`]. Those are | |
| data structures containing all the information returned by the model, but that can also be used as tuples or | |
| dictionaries. | |
| Let's see how this looks in an example: | |
| ```python | |
| from diffusers import DDIMPipeline | |
| pipeline = DDIMPipeline.from_pretrained("google/ddpm-cifar10-32") | |
| outputs = pipeline() | |
| ``` | |
| The `outputs` object is a [`~pipelines.ImagePipelineOutput`], as we can see in the | |
| documentation of that class below, it means it has an image attribute. | |
| You can access each attribute as you would usually do, and if that attribute has not been returned by the model, you will get `None`: | |
| ```python | |
| outputs.images | |
| ``` | |
| or via keyword lookup | |
| ```python | |
| outputs["images"] | |
| ``` | |
| When considering our `outputs` object as tuple, it only considers the attributes that don't have `None` values. | |
| Here for instance, we could retrieve images via indexing: | |
| ```python | |
| outputs[:1] | |
| ``` | |
| which will return the tuple `(outputs.images)` for instance. | |
| ## BaseOutput | |
| [[autodoc]] utils.BaseOutput | |
| - to_tuple | |