code: # 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.
  
  # brief Example code on load and run TVM module.s
  # file python_deploy.py
  
  import tvm
  import numpy as np
  
  def verify(mod, fname):
    # Get the function from the module
    f = mod.get_function(fname)
    # Use tvm.nd.array to convert numpy ndarray to tvm
    # NDArray type, so that function can be invoked normally
    N = 10 
    x = tvm.nd.array(np.arange(N, dtype=np.float32))
    y = tvm.nd.array(np.zeros(N, dtype=np.float32))
    # Invoke the function
    f(x, y)
    np_x = x.asnumpy() 
    np_y = y.asnumpy() 
    # Verify correctness of function
    assert(np.all([xi+1 == yi for xi, yi in zip(np_x, np_y)]))
    print("Finish verification...")
    
  
  if __name__ == "__main__":
    # The normal dynamic loading method for deployment
    mod_dylib = tvm.module.load("lib/test_addone_dll.so")
    print("Verify dynamic loading from test_addone_dll.so")
    verify(mod_dylib, "addone")
    # There might be methods to use the system lib way in
    # python, but dynamic loading is good enough for now.
  
apis: numpy.arange numpy.zeros