code: def polynomial(self, coeffs, func="mul"):
      """Computes a polynomial function on a tensor with given coefficients,
      `coeffs`, that can be a list of values or a 1-D tensor.
  
      Coefficients should be ordered from the order 1 (linear) term first,
      ending with the highest order term. (Constant is not included).
      """
      # Coefficient input type-checking
      if isinstance(coeffs, list):
          coeffs = torch.tensor(coeffs, device=self.device)
      assert is_tensor(coeffs) or crypten.is_encrypted_tensor(
          coeffs
      ), "Polynomial coefficients must be a list or tensor"
      assert (
          coeffs.dim() == 1
      ), "Polynomial coefficients must be a 1-D tensor"
  
      # Handle linear case
      if coeffs.size(0) == 1:
          return self.mul(coeffs)
  
      # Compute terms of polynomial using exponentially growing tree
      terms = crypten.stack([self, self.square()])
      while terms.size(0) < coeffs.size(0):
          highest_term = terms.index_select(
              0, torch.tensor(terms.size(0) - 1, device=self.device)
          )
          new_terms = getattr(terms, func)(highest_term)
          terms = crypten.cat([terms, new_terms])
  
      # Resize the coefficients for broadcast
      terms = terms[: coeffs.size(0)]
      for _ in range(terms.dim() - 1):
          coeffs = coeffs.unsqueeze(1)
  
      # Multiply terms by coefficients and sum
      return terms.mul(coeffs).sum(0)
  
imports: import crypten
  import torch
  from ..tensor_types import is_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: polynomial(coeffs, func) and returns: terms, self