code: def _fold_data(draw):
      shape = draw(
          helpers.get_shape(
              min_num_dims=2,
              max_num_dims=5,
              min_dim_size=2,
              max_dim_size=3,
          )
      )
      mode = draw(helpers.ints(min_value=0, max_value=len(shape) - 1))
      reduced_dims = int(
          ivy.prod(shape[0:mode]) * ivy.prod(shape[mode + 1 :])
      )
      unfolded_shape = (shape[mode], reduced_dims)
      dtype, input = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("valid"),
              shape=unfolded_shape,
          )
      )
      return dtype, input, shape, mode
  
imports: from hypothesis import strategies, assume
  import hypothesis.extra.numpy
  import numpy
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, create_concatenable_arrays_dtypes
  from ivy.functional.ivy.experimental.manipulation import _check_bounds
  from ivy_tests.test_ivy.test_functional.test_core.test_manipulation import _get_splits
label_desc: Use image node_id 5 for calling a global function with example usage: _fold_data(draw) and returns: dtype,  input,  shape,  mode