code: def test_npi_concatenate_multicast(np_shape_array, amp_init):
      class Foo(nn.HybridBlock):
          def __init__(self, **kwargs):
              super().__init__(**kwargs)
              self.dense0 = nn.Dense(16, in_units=8)
  
          def forward(self, x):
              y = self.dense0(x)
              return mx.np.concatenate([y, x], axis=-1)
  
      foo = Foo()
      foo.initialize(ctx=mx.gpu())
  
      data = mx.np.ones((32, 8), ctx=mx.gpu())
      out = foo(data)
      assert out.dtype == np.float32
  
imports: from contextlib import contextmanager
  import ctypes
  import numpy
  import pytest
  import mxnet
  from mxnet import amp
  from mxnet.base import check_call, _LIB
  from mxnet.gluon import nn
  from mxnet.test_utils import assert_allclose
label_desc: Use image node_id 4 for calling a global function with example usage: test_npi_concatenate_multicast(np_shape_array, amp_init) and returns: mx