code: def test_torch_embedding(
      *,
      dtypes_indices_weights,
      max_norm,
      p,
      on_device,
      fn_tree,
      frontend,
      test_flags,
      backend_fw,
  ):
      dtypes, indices, weight, padding_idx = dtypes_indices_weights
      helpers.test_frontend_function(
          input_dtypes=dtypes,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          input=indices,
          weight=weight,
          padding_idx=padding_idx,
          max_norm=max_norm,
          norm_type=p,
      )
  
imports: from hypothesis import strategies
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
label_desc: Use image node_id 2 for calling a global function with example usage: test_torch_embedding() without return types