message: [Python]: update test
diff: @@ -17,7 +17,7 @@ def top_level_task():
  num_samples = 60000
  t = ffmodel.conv2d(input1, 32, 3, 3, 1, 1, 1, 1, ActiMode.AC_MODE_RELU, True)
  - t = ffmodel.conv2d(t, 64, 3, 3, 1, 1, 1, 1, ActiMode.AC_MODE_RELU, True) # enable this line, then it could converge
  + t = ffmodel.conv2d(t, 64, 3, 3, 1, 1, 1, 1, ActiMode.AC_MODE_RELU, True)
  t = ffmodel.pool2d(t, 2, 2, 2, 2, 0, 0)
  t = ffmodel.flat(t);
  t = ffmodel.dense(t, 128, ActiMode.AC_MODE_RELU)
  @@ -57,6 +57,7 @@ def top_level_task():
  ffmodel.init_layers()
  epochs = ffconfig.get_epochs()
  + num_samples = 10000
  ts_start = ffconfig.get_current_time()
  for epoch in range(0,epochs):
  @@ -84,19 +85,17 @@ def top_level_task():
  dense1 = ffmodel.get_layer_by_id(0)
  - dbias_tensor = label#dense1.get_bias_tensor()
  - dbias_tensor.inline_map(ffconfig)
  - dbias = dbias_tensor.get_array(ffconfig, DataType.DT_INT32)
  - print(dbias.shape)
  - print(dbias)
  - dbias_tensor.inline_unmap(ffconfig)
  -
  - # dweight_tensor = dense1.get_output_tensor()
  - # dweight_tensor.inline_map(ffconfig)
  - # dweight = dweight_tensor.get_array(ffconfig, DataType.DT_FLOAT)
  - # print(dweight.shape)
  - # print(dweight)
  - # dweight_tensor.inline_unmap(ffconfig)
  + label.inline_map(ffconfig)
  + label_array = label.get_array(ffconfig, DataType.DT_INT32)
  + print(label_array.shape)
  + print(label_array)
  + label.inline_unmap(ffconfig)
  +
  + input1.inline_map(ffconfig)
  + input1_array = input1.get_array(ffconfig, DataType.DT_FLOAT)
  + print(input1_array.shape)
  + print(input1_array[10, :, :, :])
  + input1.inline_unmap(ffconfig)
  if __name__ == "__main__":
  