# 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)