forked from mindspore-Ecosystem/mindspore
102 lines
3.5 KiB
Python
102 lines
3.5 KiB
Python
# Copyright 2019 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 bprop disorder """
|
|
import functools
|
|
import numpy as np
|
|
|
|
import mindspore.nn as nn
|
|
import mindspore.context as context
|
|
from mindspore import Tensor, Parameter
|
|
from mindspore.common.parameter import ParameterTuple
|
|
from mindspore.ops import composite as C
|
|
from mindspore.ops import operations as P
|
|
from ..ut_filter import non_graph_engine
|
|
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
|
|
|
|
|
|
grad_by_list_with_sens = C.GradOperation(get_by_list=True, sens_param=True)
|
|
|
|
|
|
class DisOrderTest1(nn.Cell):
|
|
""" DisOrderTest1 definition """
|
|
|
|
def __init__(self):
|
|
super(DisOrderTest1, self).__init__()
|
|
weight = Tensor(np.ones([1], np.float32))
|
|
self.s1 = Parameter(weight, name="s1")
|
|
self.s2 = Parameter(weight, name="s2")
|
|
self.s3 = Parameter(weight, name="s3")
|
|
self.s4 = Parameter(weight, name="s4")
|
|
self.mul = P.Mul()
|
|
self.add = P.Add()
|
|
|
|
def construct(self, x):
|
|
return x * (self.s1 * self.s2 + self.s2 * self.s3 + self.s3 * self.s4 + self.s4 * self.s1)
|
|
|
|
|
|
class DisOrderTest2(nn.Cell):
|
|
""" DisOrderTest2 definition """
|
|
|
|
def __init__(self):
|
|
super(DisOrderTest2, self).__init__()
|
|
weight = Tensor(np.ones([1], np.float32))
|
|
self.s1 = Parameter(weight, name="s1")
|
|
self.s2 = Parameter(weight, name="s2")
|
|
self.s3 = Parameter(weight, name="s3")
|
|
self.s4 = Parameter(weight, name="s4")
|
|
self.mul = P.Mul()
|
|
self.add = P.Add()
|
|
|
|
def construct(self, x):
|
|
return self.mul(x, (self.add(self.add(self.add(self.mul(self.s1, self.s2), self.mul(self.s2, self.s3)),
|
|
self.mul(self.s3, self.s4)), self.mul(self.s4, self.s1))))
|
|
|
|
|
|
class GradNetWrap(nn.Cell):
|
|
""" GradNetWrap definition """
|
|
|
|
def __init__(self, net):
|
|
super(GradNetWrap, self).__init__()
|
|
self.net = net
|
|
self.weights = ParameterTuple(net.get_parameters())
|
|
|
|
def construct(self, x, sens):
|
|
return grad_by_list_with_sens(self.net, self.weights)(x, sens)
|
|
|
|
|
|
test_case_ops = [
|
|
('DisOrderTest1', {
|
|
'block': GradNetWrap(DisOrderTest1()),
|
|
'desc_inputs': [Tensor(np.ones([1], np.float32)), Tensor(np.ones([1], np.float32))]}),
|
|
('DisOrderTest2', {
|
|
'block': GradNetWrap(DisOrderTest2()),
|
|
'desc_inputs': [Tensor(np.ones([1], np.float32)), Tensor(np.ones([1], np.float32))]}),
|
|
]
|
|
|
|
test_case_lists = [test_case_ops]
|
|
test_exec_case = functools.reduce(lambda x, y: x + y, test_case_lists)
|
|
# use -k to select certain testcast
|
|
# pytest tests/python/ops/test_ops.py::test_backward -k LayerNorm
|
|
|
|
|
|
|
|
@non_graph_engine
|
|
@mindspore_test(pipeline_for_compile_forward_ge_graph_for_case_by_case_config)
|
|
def test_exec():
|
|
context.set_context(mode=context.GRAPH_MODE)
|
|
return test_exec_case
|