code: def _soft_thresholding_data(draw):
      x_min, x_max = 1e-2, 1e2
      x_dtype, x, shape = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("float"),
              ret_shape=True,
              min_value=x_min,
              max_value=x_max,
          )
      )
      threshold_choice_1 = draw(
          helpers.floats(min_value=x_min, max_value=x_max)
      )
      t_dtype, threshold_choice_2 = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("valid"),
              shape=shape,
              min_value=x_min,
              max_value=x_max,
          )
      )
      threshold = draw(
          st.sampled_from([threshold_choice_1, threshold_choice_2])
      )
      return x_dtype + t_dtype, x, threshold
  
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 13 for calling a global function with example usage: _soft_thresholding_data(draw) and returns: unknown,  x,  threshold