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45 lines
1.5 KiB
45 lines
1.5 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.ops import operations as P
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from mindspore.common import dtype as mstype
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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class Net(nn.Cell):
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def __init__(self, fill_mode=0):
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super(Net, self).__init__()
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self.det_triangle = P.DetTriangle(fill_mode=fill_mode)
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def construct(self, x):
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return self.det_triangle(x)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_net_1D():
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fill_mode = 0
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input_x = np.array([[1, 0, 0], [2, 3, 0], [4, 5, 6]]).astype(np.float32)
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net = Net(fill_mode=fill_mode)
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tx = Tensor(input_x, mstype.float32)
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output = net(tx)
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assert output == 18
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