!23027 recitify improper import of ParallelMode

Merge pull request !23027 from gengdongjie/fix_issues

model_zoo/official/cv/Deepsort/generater-detection.py

@@ -21,7 +21,7 @@ import matplotlib
 import numpy as np
 import cv2
 
-from mindspore.train.model import ParallelMode
+from mindspore.context import ParallelMode
 from mindspore.communication.management import init
 from mindspore import context
 from src.deep.feature_extractor import Extractor

model_zoo/official/cv/Deepsort/src/deep/train.py

@@ -24,7 +24,8 @@ import mindspore.nn as nn
 from mindspore import Tensor, context
 from mindspore.communication.management import init
 from mindspore.train.callback import CheckpointConfig, ModelCheckpoint, LossMonitor, TimeMonitor
-from mindspore.train.model import Model, ParallelMode
+from mindspore.train.model import Model
+from mindspore.context import ParallelMode
 from mindspore.common import set_seed
 from original_model import Net
 set_seed(1234)

model_zoo/official/cv/cnn_direction_model/train.py

@@ -28,8 +28,9 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
 from mindspore.nn.metrics import Accuracy
 from mindspore.nn.optim.adam import Adam
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
-from mindspore.train.model import Model, ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
+from mindspore.context import ParallelMode
 from src.cnn_direction_model import CNNDirectionModel
 from src.dataset import create_dataset_train
 from src.model_utils.config import config

model_zoo/official/cv/efficientnet/train.py

@@ -22,10 +22,11 @@ import mindspore
 from mindspore import Tensor, context
 from mindspore.communication.management import get_group_size, get_rank, init
 from mindspore.nn import SGD, RMSProp
+from mindspore.context import ParallelMode
 from mindspore.train.callback import (CheckpointConfig, LossMonitor,
                                       ModelCheckpoint, TimeMonitor)
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
-from mindspore.train.model import Model, ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from src.config import basic_config, dataset_config
 from src.dataset import create_dataset

model_zoo/official/cv/inceptionv4/train.py

@@ -34,8 +34,8 @@ from mindspore.nn import RMSProp
 from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
-from mindspore.train.model import ParallelMode
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
+from mindspore.context import ParallelMode
 
 
 os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'python'

model_zoo/official/cv/shufflenetv1/train.py

@@ -19,7 +19,8 @@ from mindspore import context
 from mindspore import Tensor
 from mindspore.common import set_seed
 from mindspore.nn.optim.momentum import Momentum
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.communication.management import init, get_rank, get_group_size

model_zoo/official/cv/srcnn/train.py

@@ -25,7 +25,7 @@ from mindspore.common import set_seed
 from mindspore.train.model import Model
 from mindspore.train.callback import TimeMonitor, LossMonitor, CheckpointConfig, ModelCheckpoint
 from mindspore.communication.management import init, get_rank, get_group_size
-from mindspore.train.model import ParallelMode
+from mindspore.context import ParallelMode
 
 from src.config import srcnn_cfg as config
 from src.dataset import create_train_dataset

model_zoo/official/cv/xception/train.py

@@ -19,7 +19,8 @@ import time
 from mindspore import context
 from mindspore import Tensor
 from mindspore.nn.optim.momentum import Momentum
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.communication.management import init

model_zoo/research/cv/LightCNN/train.py

@@ -22,7 +22,7 @@ from mindspore.train import Model
 from mindspore.common import set_seed
 from mindspore import context, Tensor
 import mindspore.common.dtype as mstype
-from mindspore.train.model import ParallelMode
+from mindspore.context import ParallelMode
 from mindspore.communication.management import init, get_rank, get_group_size
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor

model_zoo/research/cv/arcface/train.py

@@ -22,7 +22,8 @@ import numpy as np
 import mindspore.nn as nn
 from mindspore import context, Tensor
 import mindspore.ops as ops
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore import dtype as mstype
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
 from mindspore.communication.management import init

model_zoo/research/cv/efficientnet-b0/train.py

@@ -20,7 +20,8 @@ import argparse
 from mindspore import context
 from mindspore import Tensor
 from mindspore.nn import SGD, RMSProp
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.communication.management import init

model_zoo/research/cv/glore_res200/train.py

@@ -24,7 +24,8 @@ import numpy as np
 from mindspore import Tensor
 from mindspore import context
 from mindspore import dataset as de
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
 from mindspore.train.serialization import load_checkpoint, load_param_into_net

model_zoo/research/cv/glore_res50/train.py

@@ -30,7 +30,8 @@ from mindspore.nn.metrics import Accuracy
 from mindspore.communication.management import init
 import mindspore.common.initializer as weight_init
 from mindspore.nn.optim.momentum import Momentum
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor

model_zoo/research/cv/hardnet/train.py

@@ -21,7 +21,8 @@ import argparse
 import ast
 from mindspore import context
 from mindspore import Tensor
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
 from mindspore.train.serialization import load_checkpoint, load_param_into_net

model_zoo/research/cv/ibnnet/train.py

@@ -20,7 +20,8 @@ import os
 
 import mindspore.nn as nn
 from mindspore import context
-from mindspore.train.model import Model, ParallelMode
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor, Callback
 from mindspore.nn.metrics import Accuracy

model_zoo/research/cv/inception_resnet_v2/train.py

@@ -20,8 +20,8 @@ import numpy as np
 
 from mindspore.communication import init, get_rank
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor
-from mindspore.train.model import ParallelMode
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
+from mindspore.context import ParallelMode
 from mindspore import Model
 from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
 from mindspore.nn import RMSProp

model_zoo/research/cv/mnasnet/train.py

@@ -20,7 +20,8 @@ import argparse
 from mindspore import context
 from mindspore import Tensor
 from mindspore.nn import SGD, RMSProp
-from mindspore.train.model import Model, ParallelMode
+from mindspore.train.model import Model
+from mindspore.context import ParallelMode
 from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.communication.management import init

model_zoo/research/cv/stgcn/test.py

@@ -29,7 +29,7 @@ from mindspore import context
 from mindspore import Tensor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.communication.management import init
-from mindspore.train.model import ParallelMode
+from mindspore.context import ParallelMode
 
 from src.model import models
 from src.config import stgcn_chebconv_45min_cfg, stgcn_chebconv_30min_cfg, stgcn_chebconv_15min_cfg, stgcn_gcnconv_45min_cfg, stgcn_gcnconv_30min_cfg, stgcn_gcnconv_15min_cfg

model_zoo/research/cv/stgcn/train.py

@@ -28,7 +28,8 @@ import mindspore.nn as nn
 from mindspore import context
 from mindspore import Tensor
 from mindspore.communication.management import init
-from mindspore.train.model import Model, ParallelMode
+from mindspore.train.model import Model
+from mindspore.context import ParallelMode
 from mindspore.train.callback import CheckpointConfig, LossMonitor, ModelCheckpoint, TimeMonitor
 from mindspore.common import set_seed
 

model_zoo/research/cv/tinynet/train.py

@@ -19,7 +19,8 @@ import argparse
 import copy
 
 from mindspore.communication.management import init, get_rank, get_group_size
-from mindspore.train.model import ParallelMode, Model
+from mindspore.context import ParallelMode
+from mindspore.train.model import Model
 from mindspore.train.callback import TimeMonitor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 from mindspore.train.loss_scale_manager import FixedLossScaleManager
@@ -101,18 +102,18 @@ parser.add_argument('--GPU', action='store_true', default=False,
                     help='Use GPU for training (default: False)')
 
 
-def main():
-    """Main entrance for training"""
+if __name__ == '__main__':
     args = parser.parse_args()
     print(sys.argv)
     devid, args.rank_id, args.rank_size = 0, 0, 1
 
     context.set_context(mode=context.GRAPH_MODE)
+    if args.GPU:
+        context.set_context(device_target='GPU')
 
     if args.distributed:
         if args.GPU:
             init("nccl")
-            context.set_context(device_target='GPU')
         else:
             init()
             devid = int(os.getenv('DEVICE_ID'))
@@ -125,15 +126,11 @@ def main():
         context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL,
                                           gradients_mean=True,
                                           device_num=args.rank_size)
-    else:
-        if args.GPU:
-            context.set_context(device_target='GPU')
 
     is_master = not args.distributed or (args.rank_id == 0)
 
     # parse model argument
-    assert args.model.startswith(
-        "tinynet"), "Only Tinynet models are supported."
+    assert args.model.startswith("tinynet"), "Only Tinynet models are supported."
     _, sub_name = args.model.split("_")
     net = tinynet(sub_model=sub_name,
                   num_classes=args.num_classes,
@@ -166,11 +163,9 @@ def main():
                                        input_size=input_size)
         batches_per_epoch = train_dataset.get_dataset_size()
 
-    loss = LabelSmoothingCrossEntropy(
-        smooth_factor=args.smoothing, num_classes=args.num_classes)
+    loss = LabelSmoothingCrossEntropy(smooth_factor=args.smoothing, num_classes=args.num_classes)
     time_cb = TimeMonitor(data_size=batches_per_epoch)
-    loss_scale_manager = FixedLossScaleManager(
-        args.loss_scale, drop_overflow_update=False)
+    loss_scale_manager = FixedLossScaleManager(args.loss_scale, drop_overflow_update=False)
 
     lr_array = get_lr(base_lr=args.lr,
                       total_epochs=args.epochs,
@@ -181,26 +176,18 @@ def main():
                       warmup_lr_init=args.warmup_lr,
                       global_epoch=0)
     lr = Tensor(lr_array)
-
-    loss_cb = LossMonitor(lr_array,
-                          args.epochs,
-                          per_print_times=args.per_print_times,
-                          start_epoch=0)
-
+    loss_cb = LossMonitor(lr_array, args.epochs, per_print_times=args.per_print_times, start_epoch=0)
     param_group = add_weight_decay(net, weight_decay=args.weight_decay)
 
+    if is_master:
+        print(f'Using {args.opt} optimizer')
     if args.opt == 'sgd':
-        if is_master:
-            print('Using SGD optimizer')
-        optimizer = SGD(param_group,
-                        learning_rate=lr,
+        optimizer = SGD(param_group, learning_rate=lr,
                         momentum=args.momentum,
                         weight_decay=args.weight_decay,
                         loss_scale=args.loss_scale)
 
     elif args.opt == 'rmsprop':
-        if is_master:
-            print('Using rmsprop optimizer')
         optimizer = RMSProp(param_group,
                             learning_rate=lr,
                             decay=0.9,
@@ -239,12 +226,5 @@ def main():
     callbacks = [loss_cb, ema_cb, time_cb] if is_master else []
 
     if is_master:
-        print("Training on " + args.model
-              + " with " + str(args.num_classes) + " classes")
-
-    model.train(args.epochs, train_dataset, callbacks=callbacks,
-                dataset_sink_mode=args.dataset_sink)
-
-
-if __name__ == '__main__':
-    main()
+        print("Training on " + args.model + " with " + str(args.num_classes) + " classes")
+    model.train(args.epochs, train_dataset, callbacks=callbacks, dataset_sink_mode=args.dataset_sink)

model_zoo/research/nlp/dscnn/train.py

@@ -18,7 +18,7 @@ import datetime
 import numpy as np
 from mindspore import context
 from mindspore import Tensor, Model
-from mindspore.train.model import ParallelMode
+from mindspore.context import ParallelMode
 from mindspore.nn.optim import Momentum
 from mindspore.common import dtype as mstype
 from mindspore.train.serialization import load_checkpoint