Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update Some #847

Merged
merged 2 commits into from
Feb 23, 2021
Merged

Update Some #847

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
519abd5
add dygraph fleet
wuyefeilin Feb 22, 2021
bc02429
fix padding to symmetry
wuyefeilin Feb 23, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
33 changes: 21 additions & 12 deletions paddleseg/core/train.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -96,14 +96,19 @@ def train(model,
os.remove(save_dir)
os.makedirs(save_dir)

# if nranks > 1:
# # Initialize parallel environment if not done.
# if not paddle.distributed.parallel.parallel_helper._is_parallel_ctx_initialized(
# ):
# paddle.distributed.init_parallel_env()
# ddp_model = paddle.DataParallel(model)
# else:
# ddp_model = paddle.DataParallel(model)

if nranks > 1:
# Initialize parallel environment if not done.
if not paddle.distributed.parallel.parallel_helper._is_parallel_ctx_initialized(
):
paddle.distributed.init_parallel_env()
ddp_model = paddle.DataParallel(model)
else:
ddp_model = paddle.DataParallel(model)
paddle.distributed.fleet.init(is_collective=True)
optimizer = paddle.distributed.fleet.distributed_optimizer(optimizer)
ddp_model = paddle.distributed.fleet.distributed_model(model)

batch_sampler = paddle.io.DistributedBatchSampler(
train_dataset, batch_size=batch_size, shuffle=True, drop_last=True)
Expand Down Expand Up @@ -159,8 +164,6 @@ def train(model,
losses=losses,
edges=edges)
loss = sum(loss_list)
# loss.backward()
# optimizer.step()

scaled = scaler.scale(loss) # scale the loss
scaled.backward() # do backward
Expand All @@ -180,9 +183,15 @@ def train(model,
optimizer.step()

lr = optimizer.get_lr()
if isinstance(optimizer._learning_rate,
paddle.optimizer.lr.LRScheduler):
optimizer._learning_rate.step()

# update lr
if isinstance(optimizer, paddle.distributed.fleet.Fleet):
lr_sche = optimizer.user_defined_optimizer._learning_rate
else:
lr_sche = optimizer._learning_rate
if isinstance(lr_sche, paddle.optimizer.lr.LRScheduler):
lr_sche.step()

model.clear_gradients()
avg_loss += loss.numpy()[0]
if not avg_loss_list:
Expand Down
23 changes: 9 additions & 14 deletions paddleseg/models/backbones/hrnet.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -94,15 +94,15 @@ def __init__(self,
out_channels=64,
kernel_size=3,
stride=2,
padding='same',
padding=1,
bias_attr=False)

self.conv_layer1_2 = layers.ConvBNReLU(
in_channels=64,
out_channels=64,
kernel_size=3,
stride=2,
padding='same',
padding=1,
bias_attr=False)

self.la1 = Layer1(
Expand Down Expand Up @@ -243,7 +243,7 @@ def __init__(self, in_channels, out_channels, name=None):
in_channels=in_channels[i],
out_channels=out_channels[i],
kernel_size=3,
padding='same',
padding=1,
bias_attr=False))
else:
residual = self.add_sublayer(
Expand All @@ -253,7 +253,7 @@ def __init__(self, in_channels, out_channels, name=None):
out_channels=out_channels[i],
kernel_size=3,
stride=2,
padding='same',
padding=1,
bias_attr=False))
self.conv_bn_func_list.append(residual)

Expand Down Expand Up @@ -322,30 +322,27 @@ def __init__(self,
in_channels=num_channels,
out_channels=num_filters,
kernel_size=1,
padding='same',
bias_attr=False)

self.conv2 = layers.ConvBNReLU(
in_channels=num_filters,
out_channels=num_filters,
kernel_size=3,
stride=stride,
padding='same',
padding=1,
bias_attr=False)

self.conv3 = layers.ConvBN(
in_channels=num_filters,
out_channels=num_filters * 4,
kernel_size=1,
padding='same',
bias_attr=False)

if self.downsample:
self.conv_down = layers.ConvBN(
in_channels=num_channels,
out_channels=num_filters * 4,
kernel_size=1,
padding='same',
bias_attr=False)

if self.has_se:
Expand Down Expand Up @@ -390,21 +387,20 @@ def __init__(self,
out_channels=num_filters,
kernel_size=3,
stride=stride,
padding='same',
padding=1,
bias_attr=False)
self.conv2 = layers.ConvBN(
in_channels=num_filters,
out_channels=num_filters,
kernel_size=3,
padding='same',
padding=1,
bias_attr=False)

if self.downsample:
self.conv_down = layers.ConvBNReLU(
in_channels=num_channels,
out_channels=num_filters,
kernel_size=1,
padding='same',
bias_attr=False)

if self.has_se:
Expand Down Expand Up @@ -567,7 +563,6 @@ def __init__(self,
in_channels=in_channels[j],
out_channels=out_channels[i],
kernel_size=1,
padding='same',
bias_attr=False))
self.residual_func_list.append(residual_func)
elif j < i:
Expand All @@ -582,7 +577,7 @@ def __init__(self,
out_channels=out_channels[i],
kernel_size=3,
stride=2,
padding='same',
padding=1,
bias_attr=False))
pre_num_filters = out_channels[i]
else:
Expand All @@ -594,7 +589,7 @@ def __init__(self,
out_channels=out_channels[j],
kernel_size=3,
stride=2,
padding='same',
padding=1,
bias_attr=False))
pre_num_filters = out_channels[j]
self.residual_func_list.append(residual_func)
Expand Down
2 changes: 0 additions & 2 deletions paddleseg/models/fcn.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -113,15 +113,13 @@ def __init__(self,
in_channels=backbone_channels[0],
out_channels=channels,
kernel_size=1,
padding='same',
stride=1,
bias_attr=bias)
self.cls = nn.Conv2D(
in_channels=channels,
out_channels=self.num_classes,
kernel_size=1,
stride=1,
padding=0,
bias_attr=bias)
self.init_weight()

Expand Down