code: def _tt_matrix_to_tensor_data(draw):
      rank = 1
      num_factors = draw(st.integers(min_value=1, max_value=3))
      factor_dims = draw(
          st.tuples(
              st.integers(min_value=1, max_value=3),
              st.integers(min_value=1, max_value=3),
          )
      )
      shape = (num_factors, rank, *factor_dims, rank)
      x_dtype, x = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("numeric"),
              num_arrays=1,
              shape=shape,
              shared_dtype=True,
          )
      )
      return x_dtype, x
  
imports: import math
  from hypothesis import strategies
  from hypothesis import assume
  import numpy
  import pytest
  import itertools
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
  import ivy
label_desc: Use image node_id 19 for calling a global function with example usage: _tt_matrix_to_tensor_data(draw) and returns: x_dtype,  x