code: def cauchy_mult(v, z, w, symmetric=True):
      """Wrap the cuda method to deal with shapes."""
      v, w = torch.broadcast_tensors(v, w)
      shape = v.shape
      # z_shape = z.shape
      z = z.squeeze()
      assert len(z.shape) == 1
  
      v = v.contiguous()
      w = w.contiguous()
      z = z.contiguous()
  
      N = v.size(-1)
      assert w.size(-1) == N
      y = _cauchy_mult(
          v.view(-1, N), z, w.view(-1, N), symmetric=symmetric
      )
      y = y.view(*shape[:-1], z.size(-1))
      # y = z.new_zeros(*shape[:-1], z.size(-1))
      return y
  
file_path: espnet/espnet2/asr/state_spaces/cauchy.py
imports: import torch
  from cauchy_mult import cauchy_mult_bwd, cauchy_mult_fwd, cauchy_mult_sym_bwd, cauchy_mult_sym_fwd
  from einops import rearrange
label_desc: Use image node_id 4 for calling a global function with example usage: cauchy_mult(v, z, w, symmetric) and returns: y