forked from huawei/mindspore2022
112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
# Copyright 2022 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 pytest
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import mindspore.common.dtype as mstype
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from mindspore import Tensor, context
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from mindspore.nn import Cell
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from mindspore.ops import operations as P
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from parallel.utils.utils import ParallelValidator, compile_net
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class Net(Cell):
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def __init__(self, strategy=None):
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super(Net, self).__init__()
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self.lin_space = P.LinSpace().shard(strategy)
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def construct(self, start, end, x):
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return self.lin_space(start, end, x)
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def test_lin_space_loss_auto_parallel():
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"""
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Feature: test LinSpace auto parallel
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Description: auto parallel
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0)
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start = Tensor(1, mstype.float32)
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end = Tensor(10, mstype.float32)
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x = 8
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net = Net()
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compile_net(net, start, end, x)
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def test_lin_space_parallel_with_repeated_cal():
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"""
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Feature: test LinSpace parallel
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Description: parallel with repeated_cal
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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start = Tensor(1, mstype.float32)
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end = Tensor(10, mstype.float32)
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x = 8
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strategy = ((4,),)
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net = Net(strategy)
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phase = compile_net(net, start, end, x)
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validator = ParallelValidator(net, phase)
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assert validator.check_node_inputs('LinSpace-0', ['Add-0', 'Add-1', 2])
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def test_lin_space_parallel_with_x_2():
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"""
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Feature: test LinSpace parallel
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Description: parallel with input x is 2
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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start = Tensor(1, mstype.float32)
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end = Tensor(10, mstype.float32)
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x = 2
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strategy = ((2,),)
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net = Net(strategy)
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phase = compile_net(net, start, end, x)
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validator = ParallelValidator(net, phase)
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assert validator.check_node_inputs('LinSpace-0', ['Add-0', 'Add-1', 1])
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def test_lin_space_data_parallel():
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"""
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Feature: test LinSpace data parallel
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Description: data parallel
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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start = Tensor(1, mstype.float32)
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end = Tensor(10, mstype.float32)
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x = 8
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net = Net()
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phase = compile_net(net, start, end, x)
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validator = ParallelValidator(net, phase)
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assert validator.check_node_inputs('LinSpace-0', ['Add-0', 'Add-1', 1])
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def test_lin_space_parallel_strategy_wrong():
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"""
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Feature: test LinSpace parallel with invalid strategy
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Description: invalid strategy
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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start = Tensor(1, mstype.float32)
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end = Tensor(10, mstype.float32)
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x = 6
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strategy = ((4,),)
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net = Net(strategy)
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with pytest.raises(RuntimeError):
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compile_net(net, start, end, x)
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