mindspore2022/tests/ut/python/parallel/test_neighborexchangev2.py

742 lines
29 KiB
Python

# Copyright 2021 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 pytest
import numpy as np
import mindspore as ms
import mindspore.context as context
from mindspore import Tensor
import mindspore.nn as nn
from mindspore.common.api import _cell_graph_executor
from mindspore.nn import TrainOneStepCell, Momentum
from mindspore.ops.operations.comm_ops import NeighborExchangeV2
_x1 = Tensor(np.ones([1, 1, 32, 16]), dtype=ms.float32)
_x2 = Tensor(np.ones([1, 1, 33, 16]), dtype=ms.float32)
def compile_net(net, x1, x2):
context.set_context(mode=context.GRAPH_MODE)
optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
train_net = TrainOneStepCell(net, optimizer)
train_net.set_train()
_cell_graph_executor.compile(train_net, x1, x2)
def test_neighborexchangev2_single_input_success():
"""
Feature: NeighborExchangeV2
Description: one inputs and one outputs, with valid arguments
Expectation: success
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.linear = nn.Dense(16, 16)
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0], data_format="NCHW")
def construct(self, x1, x2):
y = self.linear(x1)
y = self.neighborexchangev2(y)
y = y + x2
return y
net = Net()
compile_net(net, _x1, _x2)
def test_neighborexchangev2_send_lens_equal_to_input_shape_success():
"""
Feature: NeighborExchangeV2
Description: send_lens is equal to input shape
Expectation: success
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.linear = nn.Dense(16, 16)
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 32, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0], data_format="NCHW")
def construct(self, x1, x2):
y = self.linear(x1)
y = self.neighborexchangev2(y)
y = y + x2
return y
net = Net()
compile_net(net, _x1, _x2)
def test_neighborexchangev2_empty_send_success():
"""
Feature: NeighborExchangeV2
Description: empty inputs, with valid arguments
Expectation: success
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.linear = nn.Dense(16, 16)
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, -1, -1, -1, -1],
send_lens=[1, 2, 3, 4],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x1, x2):
y = self.linear(x1)
y = self.neighborexchangev2(y)
y = y + x2
return y
net = Net()
compile_net(net, _x1, _x2)
def test_neighborexchangev2_empty_recv_success():
"""
Feature: NeighborExchangeV2
Description: empty outputs, with valid arguments
Expectation: success
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.linear = nn.Dense(16, 16)
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, -1, -1, -1, -1],
recv_lens=[1, 2, 3, 4],
data_format="NCHW")
def construct(self, x1, x2):
y = self.linear(x1)
y = self.neighborexchangev2(y)
y = y + x2
return y
net = Net()
compile_net(net, _x1, _x1)
def test_neighborexchangev2_empty_send_empty_recv_success():
"""
Feature: NeighborExchangeV2
Description: empty inputs and empty outputs, with valid arguments
Expectation: success
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, -1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, -1, -1, -1, -1],
recv_lens=[1, 2, 3, 4],
data_format="NCHW")
def construct(self, x1):
y = self.neighborexchangev2(x1)
return y
net = Net()
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_invalid_dataformat_failed():
"""
Feature: NeighborExchangeV2
Description: data_format should be NCHW, but gives NHWC
Expectation: throw ValueError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NHWC")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_invalid_send_rank_ids_size_failed():
"""
Feature: NeighborExchangeV2
Description: send_rank_ids size should be 8, but gives 5
Expectation: throw ValueError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_invalid_recv_rank_ids_size_failed():
"""
Feature: NeighborExchangeV2
Description: recv_rank_ids size should be 8, but gives 5
Expectation: throw ValueError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_invalid_send_lens_size_failed():
"""
Feature: NeighborExchangeV2
Description: send_lens size should be 4, but gives 5
Expectation: throw ValueError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0, 2],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_invalid_recv_lens_size_failed():
"""
Feature: NeighborExchangeV2
Description: recv_lens size should be 4, but gives 5
Expectation: throw ValueError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0, 2],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_invalid_input_size_failed():
"""
Feature: NeighborExchangeV2
Description: input should be one tensor, but gives 2
Expectation: throw ValueError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x1, x2):
out = self.neighborexchangev2(x1, x2)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1, _x2)
def test_neighborexchangev2_recv_rank_ids_invalid_value_failed():
"""
Feature: NeighborExchangeV2
Description: recv_rank_ids should can be concat, recv_rank_ids[3] and [4] is 1, [5] is -1 given
Expectation: throw Exception
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, 1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_send_rank_ids_is_tuple_failed():
"""
Feature: NeighborExchangeV2
Description: send_rank_ids should be list, but a tuple is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=(-1, -1, -1, -1, 1, -1, -1, -1),
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_send_lens_is_tuple_failed():
"""
Feature: NeighborExchangeV2
Description: send_lens should be list, but a tuple is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=(0, 1, 0, 0),
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_recv_rank_ids_is_tuple_failed():
"""
Feature: NeighborExchangeV2
Description: recv_rank_ids should be list, but a tuple is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=(-1, -1, -1, -1, 1, -1, -1, -1),
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_recv_lens_is_tuple_failed():
"""
Feature: NeighborExchangeV2
Description: recv_lens should be list, but a tuple is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=(0, 1, 0, 0),
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_send_rank_ids_is_float_failed():
"""
Feature: NeighborExchangeV2
Description: send_rank_ids should be int, but float is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1.0, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_send_lens_is_float_failed():
"""
Feature: NeighborExchangeV2
Description: send_lens should be int, but float is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1.0, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_recv_rank_ids_is_float_failed():
"""
Feature: NeighborExchangeV2
Description: send_rank_ids should be int, but float is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1.0, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_attr_check_recv_lens_is_float_failed():
"""
Feature: NeighborExchangeV2
Description: ids in send_rank_ids should be int, but float is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1.0, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_group_is_tuple_failed():
"""
Feature: NeighborExchangeV2
Description: group should be a string, but tuple given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW", group=("str",))
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(TypeError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_send_lens_larger_than_input_shape_failed():
"""
Feature: NeighborExchangeV2
Description: send_lens should be <= input_shape, but a larger one given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 35, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_send_rank_ids_value_invalid_failed():
"""
Feature: NeighborExchangeV2
Description: send_rank_ids should be >=0 or -1, but -3 is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -3, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_recv_rank_ids_value_invalid_failed():
"""
Feature: NeighborExchangeV2
Description: recv_rank_ids should be >=0 or -1, but -3 is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -3, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_send_lens_value_invalid_failed():
"""
Feature: NeighborExchangeV2
Description: send_lens should be >=0, but -3 is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, -3, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_recv_lens_value_invalid_failed():
"""
Feature: NeighborExchangeV2
Description: recv_lens should be >=0, but -3 is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, -3, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_send_rank_ids_repeat_failed():
"""
Feature: NeighborExchangeV2
Description: send_rank_ids cannot be repeated, but two 1 is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)
def test_neighborexchangev2_recv_rank_ids_repeat_failed():
"""
Feature: NeighborExchangeV2
Description: recv_rank_ids cannot be repeated, but two 1 is given
Expectation: throw TypeError
"""
context.set_auto_parallel_context(device_num=8, global_rank=0)
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.neighborexchangev2 = NeighborExchangeV2(send_rank_ids=[-1, -1, -1, -1, 1, -1, -1, -1],
send_lens=[0, 1, 0, 0],
recv_rank_ids=[1, -1, -1, -1, 1, -1, -1, -1],
recv_lens=[0, 1, 0, 0],
data_format="NCHW")
def construct(self, x):
out = self.neighborexchangev2(x)
return out[0]
net = Net()
with pytest.raises(ValueError):
_cell_graph_executor.compile(net, _x1)