code: def tensorinv(input, ind=2, *, out=None):
      not_invertible = "Reshaped tensor is not invertible"
      prod_cond = "Tensor shape must satisfy prod(A.shape[:ind]) == prod(A.shape[ind:])"
      positive_ind_cond = (
          "Expected a strictly positive integer for 'ind'"
      )
      input_shape = ivy.shape(input)
      assert ind > 0, f"{positive_ind_cond}"
      shape_ind_end = input_shape[:ind]
      shape_ind_start = input_shape[ind:]
      prod_ind_end = 1
      prod_ind_start = 1
      for i in shape_ind_start:
          prod_ind_start *= i
      for j in shape_ind_end:
          prod_ind_end *= j
      assert prod_ind_end == prod_ind_start, f"{prod_cond}."
      inverse_shape = shape_ind_start + shape_ind_end
      input = ivy.reshape(input, shape=(prod_ind_end, -1))
      inverse_shape_tuple = (*inverse_shape,)
      assert inv_ex(input, check_errors=True), f"{not_invertible}."
      inverse_tensor = ivy.inv(input)
      return ivy.reshape(
          inverse_tensor, shape=inverse_shape_tuple, out=out
      )
  
imports: import math
  import ivy
  import ivy.functional.frontends.torch
  from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
  from ivy.func_wrapper import with_supported_dtypes, with_unsupported_dtypes
  from collections import namedtuple
label_desc: Use image node_id 29 for calling a global function with example usage: tensorinv(input, ind) and returns: ivy