code: def test_bernoulli(
      *,
      dtype_and_probs,
      seed,
      test_flags,
      backend_fw,
      fn_name,
      on_device,
  ):
      dtype, probs = dtype_and_probs
      # torch doesn't support half precision on CPU
      assume(
          not (
              "torch" in str(backend_fw)
              and "float16" in dtype
              and on_device == "cpu"
          )
      )
      helpers.test_function(
          input_dtypes=dtype,
          test_flags=test_flags,
          on_device=on_device,
          backend_to_test=backend_fw,
          fn_name=fn_name,
          test_values=False,
          probs=probs[0],
          logits=None,
          shape=None,
          seed=seed,
      )
  
file_path: ivy/ivy_tests/test_ivy/test_functional/test_experimental/test_core/test_random.py
imports: from hypothesis import strategies, assume
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
label_desc: Use image node_id 1 for calling a global function with example usage: test_bernoulli() without return types