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69 lines
2.2 KiB
69 lines
2.2 KiB
5 years ago
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# Copyright 2019 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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from mindspore import context
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import mindspore.nn as nn
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from mindspore.ops import operations as P
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from mindspore import Tensor
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from tests.ut.python.ops.test_math_ops import VirtualLoss
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import mindspore as ms
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from mindspore.common.api import _executor
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from mindspore.ops import composite as C
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from mindspore.common.parameter import Parameter
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class NetWithLoss(nn.Cell):
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def __init__(self, network):
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super(NetWithLoss, self).__init__()
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self.loss = VirtualLoss()
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self.network = network
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def construct(self, x):
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predict = self.network(x)
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return self.loss(predict)
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class GradWrap(nn.Cell):
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def __init__(self, network):
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super(GradWrap, self).__init__()
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self.network = network
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def construct(self, x):
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return C.grad_all(self.network)(x)
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# core dump, step_auto_parallel should SetInputs for transpose axis
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def test_reshape_matmul():
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class Net(nn.Cell):
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def __init__(self):
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super().__init__()
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self.reshape = P.Reshape()
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self.matmul = P.MatMul()
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self.matmul_weight = Parameter(Tensor(np.ones([25088, 256]), dtype=ms.float32), name="weight")
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def construct(self, x):
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out = self.reshape(x, (256, 25088))
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out = self.matmul(out, self.matmul_weight)
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return out
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size = 8
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context.set_auto_parallel_context(device_num=size, global_rank=0)
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x = Tensor(np.ones([32*size, 512, 7, 7]), dtype=ms.float32)
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net = GradWrap(NetWithLoss(Net()))
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context.set_auto_parallel_context(parallel_mode="auto_parallel")
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_executor.compile(net, x)
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if __name__ == '__main__':
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test_reshape_matmul()
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