forked from mindspore-Ecosystem/mindspore
65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
# Copyright 2022 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.
|
|
# ============================================================================
|
|
|
|
from mindspore.nn import Cell
|
|
from mindspore.common import Tensor, dtype
|
|
import mindspore.ops.operations as P
|
|
import mindspore.ops.functional as F
|
|
import numpy as np
|
|
import pytest
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.env_onecard
|
|
def test_watch_get_func_graphs_from_abstract():
|
|
"""
|
|
Feature: Get func_graph from abstract.
|
|
Description: Watching the function of getting func graph from abstract.
|
|
Expectation: Output correct.
|
|
"""
|
|
|
|
class Net(Cell):
|
|
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.op = P.Add()
|
|
|
|
def construct(self, x, y):
|
|
for t in range(2):
|
|
if y != x:
|
|
if x > 4:
|
|
x = y / x
|
|
y = 1 - x
|
|
y = y - y
|
|
elif x > 2:
|
|
y = x - 1
|
|
else:
|
|
y = 3 - y
|
|
y = t * x
|
|
elif x != 3:
|
|
x = x - x
|
|
if x == y:
|
|
continue
|
|
return self.op(x, y)
|
|
|
|
x = np.array([4], np.float32)
|
|
y = np.array([1], np.float32)
|
|
net = Net()
|
|
grad_net = F.grad(net, grad_position=(0, 1))
|
|
fgrad = grad_net(Tensor(x), Tensor(y))
|
|
assert fgrad[0] == Tensor([2], dtype.float32)
|
|
assert fgrad[1] == Tensor([0], dtype.float32)
|