forked from mindspore-Ecosystem/mindspore
61 lines
2.3 KiB
Python
61 lines
2.3 KiB
Python
# 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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import mindspore as ms
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import mindspore.common.api as me
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import mindspore.nn as nn
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from mindspore import Tensor, Parameter
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from mindspore import context
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from mindspore.ops import operations as P
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def test_get_parameter_layout():
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class Net(nn.Cell):
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def __init__(self, strategy1, strategy2, weight):
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super().__init__()
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self.weight = Parameter(weight, "w1")
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self.matmul = P.MatMul(transpose_a=False, transpose_b=True).set_strategy(strategy1)
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self.relu = P.ReLU().set_strategy(strategy2)
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def construct(self, x):
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out = self.matmul(x, self.weight)
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out = self.relu(out)
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return out
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context.reset_auto_parallel_context()
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context.set_auto_parallel_context(device_num=8, global_rank=0)
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel")
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strategy1 = ((2, 1), (4, 1))
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strategy2 = ((2, 4),)
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context.set_context(mode=context.GRAPH_MODE)
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x = Tensor(np.ones([32, 32]), dtype=ms.float32)
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weight = Tensor(np.ones([64, 32]), dtype=ms.float32)
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net = Net(strategy1, strategy2, weight)
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net.set_auto_parallel()
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exe = me._executor
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exe.compile(net, x, phase='train', auto_parallel_mode=True)
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x_layout = [[2, 4], [1, -1], [16, 32], [0], [1]] # device_arrangement = [2, 4], tensor_map = [1, -1]
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weight_layout = [[2, 4], [0, -1], [16, 32], [0], [1]] # device_arrangement = [2, 4], tensor_map = [0, -1]
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expect_dict = {'x': x_layout, 'w1': weight_layout}
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# to be resovled: static local variable count_p is used in step_parallel.cc, it needs to be reset between each ut
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assert net.parameter_layout_dict == expect_dict
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if __name__ == '__main__':
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test_get_parameter_layout()
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