text: # Copyright 2020 Huawei Technologies Co., Ltd
  #
  # Licensed 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 numpy as np
  import pytest
  import mindspore.context as context
  import mindspore.nn as nn
  from mindspore import Tensor
  from mindspore.ops import operations as P
  from mindspore.common import dtype as mstype
  
  context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
  
  
  class Net(nn.Cell):
      def __init__(self, fill_mode=0):
          super(Net, self).__init__()
          self.det_triangle = P.DetTriangle(fill_mode=fill_mode)
  
      def construct(self, x):
          return self.det_triangle(x)
  
  @pytest.mark.level2
  @pytest.mark.platform_x86_gpu_training
  @pytest.mark.env_onecard
  def test_net_1D():
      fill_mode = 0
      input_x = np.array([[1, 0, 0], [2, 3, 0], [4, 5, 6]]).astype(np.float32)
      net = Net(fill_mode=fill_mode)
      tx = Tensor(input_x, mstype.float32)
      output = net(tx)
      assert output == 18
  