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- # Copyright 2022 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
- import pytest
-
- import mindspore as ms
- from mindspore import context, Tensor, Parameter
- from mindspore.nn import Cell
- from mindspore.ops import operations as P
- from mindspore.train import Model
-
-
- class Net(Cell):
- def __init__(self, weight, strategy):
- super().__init__()
- self.check_valid = P.CheckValid().shard(strategy)
- self.mul = P.Mul()
- cast_strategy = None
- if strategy:
- cast_strategy = (strategy[0],)
- self.cast = P.Cast().shard(cast_strategy)
- self.relu = P.ReLU()
- self.weight = Parameter(weight, "w1")
-
- def construct(self, x, b):
- out = self.mul(x, self.weight)
- out = self.check_valid(out, b)
- out = self.cast(out, ms.float32)
- out = self.relu(out)
- return out
-
-
- _x = Tensor(np.ones([16, 4]), dtype=ms.float32)
- _w = Tensor(np.ones([16, 4]), dtype=ms.float32)
- _b = Tensor(np.ones([3]), dtype=ms.float32)
-
-
- def compile_net(net):
- model = Model(net)
- model.predict(_x, _b)
- context.reset_auto_parallel_context()
-
-
- def test_check_valid_data_parallel():
- """
- Feature: test check valid data parallel
- Description:
- Expectation: compile success
- """
- context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, full_batch=True)
- strategy = ((8, 1), (1,))
- net = Net(_w, strategy)
- compile_net(net)
-
-
- def test_check_valid_repeated_calc():
- """
- Feature: test check valid repeated calculation
- Description:
- Expectation: compile success
- """
- context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, full_batch=True)
- strategy = ((2, 1), (1,))
- net = Net(_w, strategy)
- compile_net(net)
-
-
- def test_check_valid_no_shard():
- """
- Feature: test check valid no shard
- Description:
- Expectation: compile success
- """
- context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, full_batch=True)
- strategy = ((1, 1), (1,))
- net = Net(_w, strategy)
- compile_net(net)
-
-
- def test_check_valid_strategy_none():
- """
- Feature: test check valid strategy none
- Description: generator batch parallel strategy
- Expectation: compile success
- """
- context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, full_batch=True)
- strategy = None
- net = Net(_w, strategy)
- compile_net(net)
-
-
- def test_check_valid_auto_parallel():
- """
- Feature: test check valid auto parallel
- Description:
- Expectation: compile success
- """
- context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, full_batch=True)
- strategy = None
- net = Net(_w, strategy)
- compile_net(net)
-
-
- def test_check_valid_shard_img():
- """
- Feature: test check valid shard img
- Description:
- Expectation: compile failed
- """
- context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, full_batch=True)
- strategy = ((2, 1), (4,))
- net = Net(_w, strategy)
- with pytest.raises(RuntimeError):
- compile_net(net)
-
-
- def test_check_valid_shard_bbox_second_dimension():
- """
- Feature: test check valid shard bbox second dimension
- Description:
- Expectation: compile failed
- """
- context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, full_batch=True)
- strategy = ((2, 2), (1,))
- net = Net(_w, strategy)
- with pytest.raises(RuntimeError):
- compile_net(net)
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