forked from mindspore-Ecosystem/mindspore
100 lines
2.9 KiB
Python
100 lines
2.9 KiB
Python
# 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
|
|
from mindspore.common import dtype as mstype
|
|
from mindspore import nn
|
|
from mindspore import Tensor, jit
|
|
from mindspore.ops import composite as C
|
|
from mindspore import context
|
|
|
|
context.set_context(mode=context.GRAPH_MODE)
|
|
|
|
|
|
class ForwardNet(nn.Cell):
|
|
def construct(self, x, y):
|
|
y = y + 10
|
|
while x < y:
|
|
x = (x + 2) * (y - 9)
|
|
y = y + 2
|
|
x = x + 5
|
|
return x
|
|
|
|
|
|
class BackwardNet(nn.Cell):
|
|
def __init__(self, forward_net):
|
|
super(BackwardNet, self).__init__()
|
|
self.forward_net = forward_net
|
|
self.grad = C.GradOperation()
|
|
|
|
def construct(self, *inputs):
|
|
grads = self.grad(self.forward_net)(*inputs)
|
|
return grads
|
|
|
|
|
|
@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_forward():
|
|
c1 = Tensor([0], mstype.int32)
|
|
c2 = Tensor([0], mstype.int32)
|
|
expect = Tensor([75], mstype.int32)
|
|
forward_net = ForwardNet()
|
|
output = forward_net(c1, c2)
|
|
assert expect == output
|
|
|
|
|
|
@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_backward():
|
|
c1 = Tensor([0], mstype.int32)
|
|
c2 = Tensor([0], mstype.int32)
|
|
expect = Tensor([15], mstype.int32)
|
|
forward_net = ForwardNet()
|
|
backward_net = BackwardNet(forward_net)
|
|
output = backward_net(c1, c2)
|
|
assert expect == output
|
|
|
|
|
|
@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_while():
|
|
"""
|
|
Feature: The else branches of while loops aren't supported.
|
|
Description: The else branches of while loops aren't supported.
|
|
Expectation: No exception.
|
|
"""
|
|
@jit
|
|
def control_flow_while(x, y):
|
|
while x > y:
|
|
y += x
|
|
break
|
|
else:
|
|
y = x + 6
|
|
return y
|
|
|
|
with pytest.raises(RuntimeError, match="The 'while...else...' statement is not supported now."):
|
|
input_x = Tensor([0], mstype.int32)
|
|
input_y = Tensor([2], mstype.int32)
|
|
res = control_flow_while(input_x, input_y)
|
|
print("res:", res)
|