class_docstr: EmbeddingBag layer that initialises its values
  to using a normal variable scaled by the inverse
  of the embedding dimension.
class_docstr_tok: ["EmbeddingBag","layer","that","initialises","its","values","to","using","a","normal","variable","scaled","by","the","inverse","of","the","embedding","dimension","."]
docstr: Initialize parameters.
docstr_tok: ["Initialize","parameters","."]
code: def reset_parameters(self):
      """
      Initialize parameters.
      """
  
      self.weight.data.normal_(0, 1.0 / self.embedding_dim)
  
file_path: spotlight/spotlight/layers.py
imports: import numpy
  from sklearn.utils import murmurhash3_32
  import torch
  import torch.nn
label_desc: Use image node_id 1 for calling the ScaledEmbeddingBag obj's underlying member method code with example usage: obj.reset_parameters() without return types