code: def test_multi_head_attention_layer(
      dtype_mha,
      init_with_v,
      method_with_v,
      build_mode,
      on_device,
      class_name,
      method_name,
      backend_fw,
      ground_truth_backend,
      init_flags,
      method_flags,
  ):
      (
          input_dtype,
          x_mha,
          scale,
          num_heads,
          context,
          mask,
          query_dim,
          head_dim,
          dropout_rate,
          context_dim,
          with_to_q_fn,
          with_to_kv_fn,
          with_to_out_fn,
      ) = dtype_mha
      ret_np_flat, ret_np_from_gt_flat = helpers.test_method(
          backend_to_test=backend_fw,
          ground_truth_backend=ground_truth_backend,
          init_flags=init_flags,
          method_flags=method_flags,
          init_all_as_kwargs_np={
              "query_dim": query_dim,
              "num_heads": num_heads,
              "head_dim": head_dim,
              "dropout_rate": dropout_rate,
              "context_dim": context_dim,
              "with_to_q_fn": with_to_q_fn,
              "with_to_kv_fn": with_to_kv_fn,
              "with_to_out_fn": with_to_out_fn,
              "build_mode": build_mode,
              "device": on_device,
              "dtype": input_dtype[0],
          },
          method_input_dtypes=input_dtype,
          method_all_as_kwargs_np={
              "inputs": np.asarray(x_mha, dtype=input_dtype[0]),
              "context": np.asarray(context, dtype=input_dtype[0]),
              "mask": np.asarray(mask, dtype=input_dtype[0]),
          },
          class_name=class_name,
          method_name=method_name,
          init_with_v=init_with_v,
          method_with_v=method_with_v,
          rtol_=1e-2,
          atol_=1e-2,
          test_values=False,
          return_flat_np_arrays=True,
          on_device=on_device,
      )
      assert_same_type_and_shape([ret_np_flat, ret_np_from_gt_flat])
  
imports: import numpy
  from hypothesis import assume
  from hypothesis import strategies
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy.data_classes.container import Container
  from ivy.functional.ivy.gradients import _variable
  from ivy.functional.ivy.layers import _deconv_length
  from ivy_tests.test_ivy.helpers import handle_method
  from ivy_tests.test_ivy.helpers.assertions import assert_same_type_and_shape
  from ivy_tests.test_ivy.test_functional.test_experimental.test_nn import test_layers
  from ivy_tests.test_ivy.test_functional.test_experimental.test_nn.test_layers import _valid_dct
label_desc: Use image node_id 32 for calling a global function with example usage: test_multi_head_attention_layer(dtype_mha, init_with_v, method_with_v, build_mode, on_device, class_name, method_name, backend_fw, ground_truth_backend, init_flags, method_flags) without return types