code: def _pop_size_num_samples_replace_n_probs(draw):
      prob_dtype = draw(helpers.get_dtypes("float", full=False))
      batch_size = draw(helpers.ints(min_value=1, max_value=5))
      replace = draw(st.booleans())
      num_samples = draw(helpers.ints(min_value=1, max_value=20))
      probs = draw(
          helpers.array_values(
              dtype=prob_dtype[0],
              shape=[batch_size, num_samples],
              min_value=1.0013580322265625e-05,
              max_value=1.0,
              exclude_min=True,
          )
      )
      return prob_dtype, batch_size, num_samples, replace, probs
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_torch/test_random_sampling.py
imports: from hypothesis import strategies
  import importlib
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
label_desc: Use image node_id 1 for calling a global function with example usage: _pop_size_num_samples_replace_n_probs(draw) and returns: prob_dtype,  batch_size,  num_samples,  replace,  probs