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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 numpy as np
- import pytest
- from mindspore.ops import composite as C
- import mindspore.context as context
- from mindspore import Tensor
-
- context.set_context(device_target='GPU')
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_multinomial():
- x0 = Tensor(np.array([0.9, 0.2]).astype(np.float32))
- x1 = Tensor(np.array([[0.9, 0.2], [0.9, 0.2]]).astype(np.float32))
- out0 = C.multinomial(x0, 1, True)
- out1 = C.multinomial(x0, 2, True)
- out2 = C.multinomial(x1, 6, True)
- assert out0.asnumpy().shape == (1,)
- assert out1.asnumpy().shape == (2,)
- assert out2.asnumpy().shape == (2, 6)
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