code: def test_torch_dropout2d(
      *,
      dtype_and_x,
      prob,
      training,
      on_device,
      fn_tree,
      frontend,
      test_flags,
      backend_fw,
  ):
      dtype, x = dtype_and_x
      ret = helpers.test_frontend_function(
          input_dtypes=dtype,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          input=x[0],
          p=prob,
          training=training,
          test_values=False,
      )
      ret = helpers.flatten_and_to_np(backend=backend_fw, ret=ret)
      x = np.asarray(x[0], dtype[0])
      for u in ret:
          # cardinality test
          assert u.shape == x.shape
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_torch/test_nn/test_functional/test_dropout_functions.py
imports: import numpy
  from hypothesis import strategies
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  import ivy_tests.test_ivy.helpers
label_desc: Use image node_id 4 for calling a global function with example usage: test_torch_dropout2d() without return types