class_docstr: Define a logistic regression classifier to evaluate the quality of embedding results
class_docstr_tok: ["Define","a","logistic","regression","classifier","to","evaluate","the","quality","of","embedding","results"]
code: def forward(self, x):
      preds = self.lrc(x)
      return preds
  
file_path: dgl/examples/pytorch/rect/classify.py
imports: from statistics import mean
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the LogisticRegressionClassifier obj's underlying member method code with example usage: obj.forward(x) and returns: preds