class_docstr: Language model head that shares the same parameters with the embedding matrix.
class_docstr_tok: ["Language","model","head","that","shares","the","same","parameters","with","the","embedding","matrix","."]
code: def forward(self, x: Tensor) -> Tensor:
      if self.synced_embed:
          x = F.linear(x, self.head.weight)
      else:
          x = self.head(x)
  
      return x
  
imports: import torch
  import torch.nn.init
  from torch import Tensor
  from torch import nn
  from torch.nn import functional
  from torch.nn.parameter import Parameter
  from colossalai.legacy.context import ParallelMode, seed
  from colossalai.legacy.core import global_context
  from colossalai.legacy.nn.layer.base_layer import ParallelLayer
  from colossalai.legacy.nn.layer.parallel_1d._utils import gather_forward_split_backward, reduce_grad, reduce_input
  from colossalai.legacy.nn.layer.parallel_1d.layers import Linear1D_Row
  from colossalai.legacy.nn.layer.utils import divide
  from colossalai.legacy.registry import LAYERS, LOSSES
  from colossalai.utils import get_current_device
label_desc: Use image node_id 2 for calling the HiddenParallelGPTLMHead1D obj's underlying member method code with example usage: obj.forward(x) and returns: x