change group conv dtype in gpu resnext50

model_zoo/official/cv/resnext50/src/utils/auto_mixed_precision.py

@@ -44,9 +44,6 @@ def auto_mixed_precision(network):
         elif name == 'fc':
             network.insert_child_to_cell(name, OutputTo(subcell, mstype.float32))
             change = True
-        elif name == 'conv2':
-            subcell.to_float(mstype.float32)
-            change = True
         elif isinstance(subcell, (nn.BatchNorm2d, nn.BatchNorm1d)):
             network.insert_child_to_cell(name, OutputTo(subcell.to_float(mstype.float32), mstype.float16))
             change = True

model_zoo/official/cv/resnext50/train.py

@@ -36,7 +36,6 @@ from src.warmup_cosine_annealing_lr import warmup_cosine_annealing_lr
 from src.utils.logging import get_logger
 from src.utils.optimizers__init__ import get_param_groups
 from src.image_classification import get_network
-from src.utils.auto_mixed_precision import auto_mixed_precision
 from src.config import config
 
 
@@ -273,8 +272,8 @@ def train(cloud_args=None):
         model = Model(network, loss_fn=loss, optimizer=opt, loss_scale_manager=loss_scale_manager,
                       metrics={'acc'}, amp_level="O3")
     else:
-        auto_mixed_precision(network)
-        model = Model(network, loss_fn=loss, optimizer=opt, loss_scale_manager=loss_scale_manager, metrics={'acc'})
+        model = Model(network, loss_fn=loss, optimizer=opt, loss_scale_manager=loss_scale_manager,
+                      metrics={'acc'}, amp_level="O2")
 
     # checkpoint save
     progress_cb = ProgressMonitor(args)