forked from huawei/mindspore2022
131 lines
4.4 KiB
Python
131 lines
4.4 KiB
Python
# Copyright 2020 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 nn, context, Tensor
|
|
import mindspore.ops as ops
|
|
|
|
def set_context():
|
|
context.set_context(mode=context.PYNATIVE_MODE)
|
|
context.reset_auto_parallel_context()
|
|
context.set_auto_parallel_context(device_num=8, parallel_mode="auto_parallel", search_mode="sharding_propagation")
|
|
|
|
class NetMul(nn.Cell):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.mul = ops.Mul()
|
|
|
|
def construct(self, x, y):
|
|
return self.mul(x, y)
|
|
|
|
|
|
class NetMatMul(nn.Cell):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.matmul = ops.MatMul()
|
|
|
|
def construct(self, x, y):
|
|
return self.matmul(x, y)
|
|
|
|
class Net(nn.Cell):
|
|
def __init__(self, in_strategy, out_strategy):
|
|
super().__init__()
|
|
self.mul_net = NetMul()
|
|
self.matmul_net = NetMatMul()
|
|
self.mul_net.shard(in_strategy=in_strategy, out_strategy=out_strategy)
|
|
|
|
def construct(self, x, y):
|
|
out1 = self.matmul_net(x, y)
|
|
out2 = self.matmul_net(x, y)
|
|
return self.mul_net(out1, out2)
|
|
|
|
|
|
def cell_shard_execution(in_strategy, out_strategy, error_log):
|
|
|
|
net = Net(in_strategy, out_strategy)
|
|
x = Tensor(np.ones([128, 128]), dtype=ms.float32)
|
|
y = Tensor(np.ones([128, 128]), dtype=ms.float32)
|
|
|
|
with pytest.raises(Exception) as err:
|
|
_ = net(x, y)
|
|
assert error_log in str(err.value)
|
|
|
|
|
|
def test_in_strategy_numbers_check():
|
|
"""
|
|
Feature: shard function for cell
|
|
Description: inconsistent input number and in_strategy number
|
|
Expectation: throw an exception indicating inconsistent input number and in_strategy number
|
|
"""
|
|
set_context()
|
|
in_strategy = ((8, 1), None, (1, 8))
|
|
out_strategy = (None,)
|
|
error_log = "Input numbers: 2 is not equal to in_strategy numbers: 3"
|
|
cell_shard_execution(in_strategy, out_strategy, error_log)
|
|
|
|
|
|
def test_out_strategy_numbers_check():
|
|
"""
|
|
Feature: shard function for cell
|
|
Description: inconsistent output number and out_strategy number
|
|
Expectation: throw an exception indicating inconsistent output number and out_strategy number
|
|
"""
|
|
set_context()
|
|
in_strategy = ((8, 1), None)
|
|
out_strategy = (None, (8, 1))
|
|
error_log = "Output number: 1 is not equal to out_strategy number: 2"
|
|
cell_shard_execution(in_strategy, out_strategy, error_log)
|
|
|
|
|
|
def test_in_strategy_dimension_check():
|
|
"""
|
|
Feature: shard function for cell
|
|
Description: inconsistent input dimension and in_strategy dimension
|
|
Expectation: throw an exception indicating inconsistent input_dimension and in_strategy dimension
|
|
"""
|
|
set_context()
|
|
in_strategy = ((8, 1, 1), None)
|
|
out_strategy = (None, (8, 1))
|
|
error_log = "Input dimension: 2 is not equal to in_strategy dimension: 3 at index 0"
|
|
cell_shard_execution(in_strategy, out_strategy, error_log)
|
|
|
|
|
|
def test_out_strategy_dimension_check():
|
|
"""
|
|
Feature: shard function for cell
|
|
Description: inconsistent output dimension and out_strategy dimension
|
|
Expectation: throw an exception indicating inconsistent output_dimension and out_strategy dimension
|
|
"""
|
|
set_context()
|
|
in_strategy = ((8, 1), None)
|
|
out_strategy = ((8,),)
|
|
error_log = "Output dimension: 2 is not equal to out_strategy dimension: 1 at index 0"
|
|
cell_shard_execution(in_strategy, out_strategy, error_log)
|
|
|
|
|
|
def test_in_strategy_format_check():
|
|
"""
|
|
Feature: shard function for cell
|
|
Description: unsupported in_strategy format
|
|
Expectation: throw an exception indicating an supported in_strategy format
|
|
"""
|
|
set_context()
|
|
in_strategy = ([8, 1], None)
|
|
out_strategy = (None,)
|
|
error_log = "in_strategy should be a two-dimension tuple"
|
|
cell_shard_execution(in_strategy, out_strategy, error_log)
|