# Copyright 2024 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 as ms
import mindspore.nn as nn
import mindspore.ops as ops


class Net(nn.Cell):
    def __init__(self, size):
        super().__init__()
        self.cauchy = ops.Cauchy(size)

    def construct(self):
        return self.cauchy()

@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_arm_cpu
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_cauchy(mode):
    """
    Feature: Cauchy op
    Description: Verify the result of cauchy
    Expectation: success
    """
    ms.set_context(mode=mode)
    size = [2, 3]
    net = Net(size)
    out = net()
    assert out.shape == tuple(size)