code: def forward(self, input, params=None):
      if params is None:
          params = OrderedDict(self.named_parameters())
      return F.embedding(
          input,
          params["weight"],
          self.padding_idx,
          self.max_norm,
          self.norm_type,
          self.scale_grad_by_freq,
          self.sparse,
      )
  
file_path: pytorch-meta/torchmeta/modules/sparse.py
imports: import torch.nn
  import torch.nn.functional
  from collections import OrderedDict
  from torchmeta.modules.module import MetaModule
label_desc: Use image node_id 1 for calling the MetaEmbedding obj's underlying member method code with example usage: obj.forward(input, params) and returns: F