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!10050 GPU update init nccl in dataset 

From: @VectorSL
Reviewed-by: @limingqi107,@cristoval
Signed-off-by: @cristoval
This commit is contained in:
mindspore-ci-bot 2020-12-17 09:23:14 +08:00 committed by Gitee
parent 3f9e90a0a8 3bcbfa1806
commit ed763748de
2 changed files with 38 additions and 14 deletions
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50
model_zoo/official/cv/resnet/src/dataset.py
View File

@ -23,7 +23,7 @@ import mindspore.dataset.transforms.c_transforms as C2
from mindspore.communication.management import init, get_rank, get_group_size
def create_dataset1(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend"):
def create_dataset1(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend", distribute=False):
"""
create a train or evaluate cifar10 dataset for resnet50
Args:
@ -32,6 +32,7 @@ def create_dataset1(dataset_path, do_train, repeat_num=1, batch_size=32, target=
repeat_num(int): the repeat times of dataset. Default: 1
batch_size(int): the batch size of dataset. Default: 32
target(str): the device target. Default: Ascend
distribute(bool): data for distribute or not. Default: False
Returns:
dataset
@ -39,10 +40,12 @@ def create_dataset1(dataset_path, do_train, repeat_num=1, batch_size=32, target=
if target == "Ascend":
device_num, rank_id = _get_rank_info()
else:
init()
rank_id = get_rank()
device_num = get_group_size()
if distribute:
init()
rank_id = get_rank()
device_num = get_group_size()
else:
device_num = 1
if device_num == 1:
ds = de.Cifar10Dataset(dataset_path, num_parallel_workers=8, shuffle=True)
else:
@ -77,7 +80,7 @@ def create_dataset1(dataset_path, do_train, repeat_num=1, batch_size=32, target=
return ds
def create_dataset2(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend"):
def create_dataset2(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend", distribute=False):
"""
create a train or eval imagenet2012 dataset for resnet50
@ -87,6 +90,7 @@ def create_dataset2(dataset_path, do_train, repeat_num=1, batch_size=32, target=
repeat_num(int): the repeat times of dataset. Default: 1
batch_size(int): the batch size of dataset. Default: 32
target(str): the device target. Default: Ascend
distribute(bool): data for distribute or not. Default: False
Returns:
dataset
@ -94,9 +98,12 @@ def create_dataset2(dataset_path, do_train, repeat_num=1, batch_size=32, target=
if target == "Ascend":
device_num, rank_id = _get_rank_info()
else:
init()
rank_id = get_rank()
device_num = get_group_size()
if distribute:
init()
rank_id = get_rank()
device_num = get_group_size()
else:
device_num = 1
if device_num == 1:
ds = de.ImageFolderDataset(dataset_path, num_parallel_workers=8, shuffle=True)
@ -139,7 +146,7 @@ def create_dataset2(dataset_path, do_train, repeat_num=1, batch_size=32, target=
return ds
def create_dataset3(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend"):
def create_dataset3(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend", distribute=False):
"""
create a train or eval imagenet2012 dataset for resnet101
Args:
@ -147,12 +154,21 @@ def create_dataset3(dataset_path, do_train, repeat_num=1, batch_size=32, target=
do_train(bool): whether dataset is used for train or eval.
repeat_num(int): the repeat times of dataset. Default: 1
batch_size(int): the batch size of dataset. Default: 32
target(str): the device target. Default: Ascend
distribute(bool): data for distribute or not. Default: False
Returns:
dataset
"""
device_num, rank_id = _get_rank_info()
if target == "Ascend":
device_num, rank_id = _get_rank_info()
else:
if distribute:
init()
rank_id = get_rank()
device_num = get_group_size()
else:
device_num = 1
if device_num == 1:
ds = de.ImageFolderDataset(dataset_path, num_parallel_workers=8, shuffle=True)
else:
@ -192,7 +208,7 @@ def create_dataset3(dataset_path, do_train, repeat_num=1, batch_size=32, target=
return ds
def create_dataset4(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend"):
def create_dataset4(dataset_path, do_train, repeat_num=1, batch_size=32, target="Ascend", distribute=False):
"""
create a train or eval imagenet2012 dataset for se-resnet50
@ -202,12 +218,20 @@ def create_dataset4(dataset_path, do_train, repeat_num=1, batch_size=32, target=
repeat_num(int): the repeat times of dataset. Default: 1
batch_size(int): the batch size of dataset. Default: 32
target(str): the device target. Default: Ascend
distribute(bool): data for distribute or not. Default: False
Returns:
dataset
"""
if target == "Ascend":
device_num, rank_id = _get_rank_info()
else:
if distribute:
init()
rank_id = get_rank()
device_num = get_group_size()
else:
device_num = 1
if device_num == 1:
ds = de.ImageFolderDataset(dataset_path, num_parallel_workers=12, shuffle=True)
else:

2
model_zoo/official/cv/resnet/train.py
View File

@ -94,7 +94,7 @@ if __name__ == '__main__':
# create dataset
dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=True, repeat_num=1,
batch_size=config.batch_size, target=target)
batch_size=config.batch_size, target=target, distribute=args_opt.run_distribute)
step_size = dataset.get_dataset_size()
# define net