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- # 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 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, shape, seed=0, seed2=0):
- super(Net, self).__init__()
- self.uniformint = P.UniformInt(seed=seed)
- self.shape = shape
-
- def construct(self, a, b):
- return self.uniformint(self.shape, a, b)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_net_1D():
- seed = 10
- shape = (3, 2, 4)
- a = 1
- b = 5
- net = Net(shape, seed=seed)
- ta, tb = Tensor(a, mstype.int32), Tensor(b, mstype.int32)
- output = net(ta, tb)
- assert output.shape == (3, 2, 4)
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