code: def forward(self, input):
      qweight = self.weight_fake_quant(self.weight)
      return _F.embedding(
          input,
          qweight,
          self.padding_idx,
          self.max_norm,
          self.norm_type,
          self.scale_grad_by_freq,
          self.sparse,
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .palettization_config import SUPPORTED_PYTORCH_QAT_MODULES
label_desc: Use image node_id 1 for calling the Embedding obj's underlying member method code with example usage: obj.forward(input) and returns: _F