Continuation of issue #2474 as discussed here

Add default parameters for all projection heads

It's helpful to know what the default parameters were in the papers to get started. We should add the default projection head parameters which were used for pre-training on Imagenet to all projection and prediction heads in lightly/models/modules/heads.py.

The default RubrixLogHTTPMiddleware record mapper for token classification expect a structured including a text field for inputs. This could make prediction model inputs a bit cumbersome. Default mapper could accepts also flat strings as inputs:

def token_classification_mapper(inputs, outputs):
    i

When computing the isosurface, when 4 simplex edges crosses the isosurface, we add 2 triangles to the isosurface triangulation.

Right now we add these arbitrarily (in these 3 lines) but we should add them so that the curvature is minimized.

The current state o

We should swap most of our metrics for torchmetrics this would make our code more robust.

Only ECE is special I think and we should keep our own implementation.

This PR adds the option to re-import RIS files into reference software to the documentation.

To do:

• add more information on how the labels are stored in which field of the RIS file (@ottomattas )
• add a screenshot of how this looks in reference manager software (@ottomattas )

X_U = X_all[-cfg.X_L_0_size:].copy()
您好,请问这里未标注数据的选取是不是多了一个负号?