code: def _normalize_moments_helper(draw):
      shape1, shape2, shape3 = draw(
          helpers.mutually_broadcastable_shapes(3)
      )
      counts_dtype, counts = draw(
          helpers.dtype_and_values(
              available_dtypes=helpers.get_dtypes("float"),
              max_value=999,
              min_value=-1001,
              max_num_dims=1,
              max_dim_size=1,
              min_dim_size=1,
          )
      )
      _, mean = draw(
          helpers.dtype_and_values(
              available_dtypes=counts_dtype,
              shape=shape1,
              min_value=1,
              max_num_dims=1,
              max_dim_size=1,
              min_dim_size=1,
          )
      )
      _, variance = draw(
          helpers.dtype_and_values(
              available_dtypes=counts_dtype,
              shape=shape2,
              min_value=1,
              max_num_dims=1,
              max_dim_size=1,
              min_dim_size=1,
          )
      )
      _, shift = draw(
          helpers.dtype_and_values(
              available_dtypes=counts_dtype,
              shape=shape3,
              min_value=1,
              max_num_dims=1,
              max_dim_size=1,
              min_dim_size=1,
          )
      )
  
      return counts_dtype, counts[0], mean[0], variance[0], shift[0]
  
imports: from hypothesis import assume, strategies
  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_statistical import _statistical_dtype_values
  from ivy_tests.test_ivy.test_functional.test_nn.test_layers import _assume_tf_dilation_gt_1, _output_shape
label_desc: Use image node_id 6 for calling a global function with example usage: _normalize_moments_helper(draw) and returns: counts_dtype,  counts,  mean,  variance,  shift