code: def prod(self, dim=None, keepdim=False):
      """
      Returns the product of each row of the `input` tensor in the given
      dimension `dim`.
  
      If `keepdim` is `True`, the output tensor is of the same size as `input`
      except in the dimension `dim` where it is of size 1. Otherwise, `dim` is
      squeezed, resulting in the output tensor having 1 fewer dimension than
      `input`.
      """
      if dim is None:
          return self.flatten().prod(dim=0)
  
      result = self.clone()
      while result.size(dim) > 1:
          size = result.size(dim)
          x, y, remainder = result.split(
              [size // 2, size // 2, size % 2], dim=dim
          )
          result = x.mul_(y)
          result = type(self).cat([result, remainder], dim=dim)
  
      # Squeeze result if necessary
      if not keepdim:
          result = result.squeeze(dim)
      return result
  
imports: import torch
  from ..tensor_types import is_tensor
  from ..util import torch_cat, torch_stack
label_desc: Use image node_id 11 for calling a global function with example usage: prod(dim, keepdim) and returns: result, self