mindspore2022/tests/st/control/inner/test_000_single_if.py

# Copyright 2021 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
from mindspore import context
from mindspore import Tensor, nn
from mindspore.ops import composite as C
from mindspore.common import dtype as mstype

grad_all = C.GradOperation(get_all=True)


class SingleIfNet(nn.Cell):
    def construct(self, x, y):
        x += 1
        if x < y:
            y += x
        else:
            y -= x
        y += 5
        return y


class SingleIfNet1(nn.Cell):
    def construct(self, x, y):
        x += 1
        out = self.func(x, y)
        out *= 2
        return out

    def func(self, x, y):
        if x < y:
            y += x
        else:
            y -= x
        y += 5
        return y


class GradNet(nn.Cell):
    def __init__(self, net):
        super(GradNet, self).__init__()
        self.net = net

    def construct(self, *inputs):
        return grad_all(self.net)(*inputs)


def control_flow_single_if(input_net, x, y, expect1, expect2):
    # graph mode
    context.set_context(mode=context.GRAPH_MODE)
    net = input_net()
    grad_net = GradNet(net)

    forward_net = input_net()
    graph_forward_res = forward_net(x, y)
    graph_backward_res = grad_net(x, y)

    assert graph_forward_res == expect1
    assert graph_backward_res == expect2


@pytest.mark.level1
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_single_if():
    x = Tensor(2, mstype.int32)
    y = Tensor(5, mstype.int32)
    expect1 = Tensor(26, mstype.int32)
    expect2 = (Tensor(2, mstype.int32), Tensor(2, mstype.int32))
    control_flow_single_if(SingleIfNet1, x, y, expect1, expect2)


@pytest.mark.level1
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_single_if_01():
    x = Tensor(2, mstype.int32)
    y = Tensor(5, mstype.int32)
    expect1 = Tensor(26, mstype.int32)
    expect2 = (Tensor(2, mstype.int32), Tensor(2, mstype.int32))
    control_flow_single_if(SingleIfNet1, x, y, expect1, expect2)