forked from mindspore-Ecosystem/mindspore
140 lines
4.1 KiB
Python
140 lines
4.1 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.
|
|
# ============================================================================
|
|
""" test control ops """
|
|
import functools
|
|
import numpy as np
|
|
|
|
from mindspore import Tensor
|
|
from mindspore import context
|
|
from mindspore import nn
|
|
from mindspore.common import dtype as mstype
|
|
from mindspore.ops import operations as P
|
|
from ....mindspore_test_framework.mindspore_test import mindspore_test
|
|
from ....mindspore_test_framework.pipeline.forward.compile_forward \
|
|
import pipeline_for_compile_forward_ge_graph_for_case_by_case_config
|
|
|
|
context.set_context(mode=context.GRAPH_MODE)
|
|
|
|
|
|
class ComparisonOpsNet(nn.Cell):
|
|
def __init__(self):
|
|
super(ComparisonOpsNet, self).__init__()
|
|
|
|
def construct(self, x, y):
|
|
a = x <= y
|
|
b = x <= 1.0
|
|
c = y >= 1.0
|
|
d = y >= x
|
|
e = x < y
|
|
f = x < 1.0
|
|
g = y < 1.0
|
|
h = y > x
|
|
i = y == 3.0
|
|
j = x != 4
|
|
k = + x
|
|
l = + 1.0
|
|
m = k != l
|
|
return a or b or c or d or e or f or g or h or i or j or m
|
|
|
|
|
|
class MathOpsNet(nn.Cell):
|
|
def __init__(self):
|
|
super(MathOpsNet, self).__init__()
|
|
self.relu = P.ReLU()
|
|
|
|
def construct(self, x, y):
|
|
x = x - (-1)
|
|
return self.relu(x)
|
|
|
|
|
|
class ScalarCompareNet(nn.Cell):
|
|
def __init__(self):
|
|
super(ScalarCompareNet, self).__init__()
|
|
self.relu = P.ReLU()
|
|
|
|
def construct(self, x, y):
|
|
t = 0
|
|
if 3 > 3.2:
|
|
t = x + y
|
|
else:
|
|
t = x - y
|
|
if 3.1 <= 5:
|
|
t = t - x
|
|
else:
|
|
t = t + x
|
|
a = 32.0 * 12
|
|
b = 12 / 3.0
|
|
if a > b:
|
|
t = t * x
|
|
else:
|
|
t = t / x
|
|
return t
|
|
|
|
|
|
class LogicalNumberOpsNet(nn.Cell):
|
|
def __init__(self):
|
|
super(LogicalNumberOpsNet, self).__init__()
|
|
self.cond = True
|
|
self.one = 0
|
|
self.zero = 0.0
|
|
|
|
def construct(self, x, y):
|
|
if self.cond and self.one or self.zero and not self.one:
|
|
return x + y
|
|
return x - y
|
|
|
|
|
|
class LogicalTensorOpsNet(nn.Cell):
|
|
def __init__(self):
|
|
""""""
|
|
super(LogicalTensorOpsNet, self).__init__()
|
|
self.const_true = Tensor(True, dtype=mstype.bool_)
|
|
|
|
def construct(self, x, y):
|
|
ret = x and y and (y or self.const_true) and (not y)
|
|
return ret
|
|
|
|
|
|
test_case_ops = [
|
|
('CompareOpsNet', {
|
|
'block': ComparisonOpsNet(),
|
|
'desc_inputs': [Tensor(1.0, dtype=mstype.float32),
|
|
Tensor(1.0, dtype=mstype.float32)]}),
|
|
('MathOpsNet', {
|
|
'block': MathOpsNet(),
|
|
'desc_inputs': [Tensor(np.ones([6, 9, 10]), dtype=mstype.float32),
|
|
Tensor(np.zeros([6, 9, 10]), dtype=mstype.float32)]}),
|
|
('ScalarCompareNet', {
|
|
'block': ScalarCompareNet(),
|
|
'desc_inputs': [Tensor(np.ones([6, 9, 10]), dtype=mstype.float32),
|
|
Tensor(np.zeros([6, 9, 10]), dtype=mstype.float32)]}),
|
|
('LogicalNumberOps', {
|
|
'block': LogicalNumberOpsNet(),
|
|
'desc_inputs': [Tensor(np.ones([6, 9, 10]), dtype=mstype.float32),
|
|
Tensor(np.zeros([6, 9, 10]), dtype=mstype.float32)]}),
|
|
('LogicalTensorOps', {
|
|
'block': LogicalTensorOpsNet(),
|
|
'desc_inputs': [Tensor(True, dtype=mstype.bool_),
|
|
Tensor(False, dtype=mstype.bool_)]}),
|
|
]
|
|
|
|
test_case_lists = [test_case_ops]
|
|
test_exec_case = functools.reduce(lambda x, y: x + y, test_case_lists)
|
|
|
|
|
|
@mindspore_test(pipeline_for_compile_forward_ge_graph_for_case_by_case_config)
|
|
def test_compile():
|
|
return test_exec_case
|