new_contents: # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF licenses this file
  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License.  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  import tvm
  import numpy as np
  
  
  def test_rocm_cross_thread_reduction():
      if not tvm.rocm(0).exist or not tvm.module.enabled("rocm"):
          print("skip because rocm is not enabled..")
          return
  
      # based on the reduction tutorial
      n = tvm.var("n")
      m = tvm.var("m")
      A = tvm.placeholder((n, m), name='A')
      k = tvm.reduce_axis((0, m), "k")
      B = tvm.compute((n,), lambda i: tvm.sum(A[i, k], axis=k), name="B")
      s = tvm.create_schedule(B.op)
      ko, ki = s[B].split(B.op.reduce_axis[0], factor=16)
      BF = s.rfactor(B, ki)
      xo, xi = s[B].split(s[B].op.axis[0], factor=32)
      s[B].bind(xo, tvm.thread_axis("blockIdx.x"))
      s[B].bind(xi, tvm.thread_axis("threadIdx.y"))
      tx = tvm.thread_axis("threadIdx.x")
      s[B].bind(s[B].op.reduce_axis[0], tx)
      s[BF].compute_at(s[B], s[B].op.reduce_axis[0])
      s[B].set_store_predicate(tx.var.equal(0))
      frocm = tvm.build(s, [A, B], "rocm")
  
      nn = 128
      ctx = tvm.rocm(0)
      a = tvm.nd.array(np.random.uniform(size=(nn, nn)).astype(A.dtype), ctx)
      b = tvm.nd.array(np.zeros(nn, dtype=B.dtype), ctx)
      frocm(a, b)
      tvm.testing.assert_allclose(
        b.asnumpy(),  np.sum(a.asnumpy(), axis=1), rtol=1e-4)
  
  
  if __name__ == "__main__":
      test_rocm_cross_thread_reduction()
  
subject: add rocm codegen unittest for cross thread reduction (#4423)