code: def forward(self, max_seq_len, *, device):
      seq = torch.arange(
          max_seq_len, device=device, dtype=self.inv_freq.dtype
      )
      freqs = einsum("i , j -> i j", seq, self.inv_freq)
      return torch.cat((freqs, freqs), dim=-1)
  
imports: import torch
  from torch import einsum, nn
  import torch.nn.functional
  from einops import rearrange
  from towhee.models.layers.activations.swiglu import SwiGLU
label_desc: Use image node_id 2 for calling the RotaryEmbedding obj's underlying member method code with example usage: obj.forward(max_seq_len) and returns: torch