From where can i get a detailed description of all the methods for the model in pytorch torchvison？
I am a beginner of pytorch ，when i read the source code of a project about mask rcnn .I don't konw from where can i  get  some information about some methods that i  don't understand .The official documentation doesn't seem very detailed?
# load an instance segmentation model pre-trained pre-trained on COCO
model = torchvision.models.detection.maskrcnn_resnet50_fpn(pretrained=True)
# get number of input features for the classifier
in_features = model.roi_heads.box_predictor.cls_score.in_features
# replace the pre-trained head with a new one
model.roi_heads.box_predictor = FastRCNNPredictor(in_features, num_classes)

Just like code above ,I could not get detailed information about the &quot; roi_head&quot; attribute from doc of model .From where i can learn about it？

You won't be able to find such thing on the documentation. You'll have to dive into the source code. Object Detection APIs, especially anchor-based two-stage approaches, are a little bit complex, and they tend to have too many components and hyper-parameters. PyTorch team already made an incredible job making this API modular and kinda easy-to-use. In the specific case of roi_heads you can take a look here to learn more about it. In general, all components can be found in torchvision/models/detection.
Anyway, you can always open an issue, requesting them to expand the documentation. Or we can even do it ourselves and make a pull request :)
