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mindspore/tests/ut/python/parallel/test_auto_parallel_reshape.py

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# 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.
import numpy as np
from mindspore import context
import mindspore.nn as nn
from mindspore.ops import operations as P
from mindspore import Tensor
from tests.ut.python.ops.test_math_ops import VirtualLoss
import mindspore as ms
from mindspore.common.api import _executor
from mindspore.ops import composite as C
from mindspore.common.parameter import Parameter
class NetWithLoss(nn.Cell):
def __init__(self, network):
super(NetWithLoss, self).__init__()
self.loss = VirtualLoss()
self.network = network
def construct(self, x):
predict = self.network(x)
return self.loss(predict)
class GradWrap(nn.Cell):
def __init__(self, network):
super(GradWrap, self).__init__()
self.network = network
def construct(self, x):
return C.grad_all(self.network)(x)
# core dump, step_auto_parallel should SetInputs for transpose axis
def test_reshape_matmul():
class Net(nn.Cell):
def __init__(self):
super().__init__()
self.reshape = P.Reshape()
self.matmul = P.MatMul()
self.matmul_weight = Parameter(Tensor(np.ones([25088, 256]), dtype=ms.float32), name="weight")
def construct(self, x):
out = self.reshape(x, (256, 25088))
out = self.matmul(out, self.matmul_weight)
return out
size = 8
context.set_auto_parallel_context(device_num=size, global_rank=0)
x = Tensor(np.ones([32*size, 512, 7, 7]), dtype=ms.float32)
net = GradWrap(NetWithLoss(Net()))
context.set_auto_parallel_context(parallel_mode="auto_parallel")
_executor.compile(net, x)
if __name__ == '__main__':
test_reshape_matmul()