code: def test_torch_view_as_complex(
      *,
      dtype_and_values,
      on_device,
      fn_tree,
      frontend,
      test_flags,
      backend_fw,
  ):
      dtype, value = dtype_and_values
      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=value[0],
      )
  
imports: import math
  import numpy
  from hypothesis import assume, strategies
  import hypothesis.extra.numpy
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _get_dtype_value1_value2_axis_for_tensordot
label_desc: Use image node_id 49 for calling a global function with example usage: test_torch_view_as_complex() without return types