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Fix name bug. (open-mmlab#47)
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kennymckormick authored Jul 23, 2020
1 parent 7dc99cf commit 133dce6
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Showing 12 changed files with 13 additions and 13 deletions.
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Expand Up @@ -105,7 +105,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 180
checkpoint_config = dict(interval=5)
evaluation = dict(
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Expand Up @@ -105,7 +105,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 180
checkpoint_config = dict(interval=5)
evaluation = dict(
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Expand Up @@ -116,7 +116,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 180
checkpoint_config = dict(interval=5)
evaluation = dict(
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Expand Up @@ -111,7 +111,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 256
checkpoint_config = dict(interval=4)
workflow = [('train', 1)]
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Expand Up @@ -111,7 +111,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 256
checkpoint_config = dict(interval=4)
workflow = [('train', 1)]
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Expand Up @@ -121,7 +121,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 256
checkpoint_config = dict(interval=4)
workflow = [('train', 1)]
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Expand Up @@ -102,7 +102,7 @@
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(
policy='CosineAnealing',
policy='CosineAnnealing',
min_lr=0,
warmup='linear',
warmup_by_epoch=True,
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Expand Up @@ -94,7 +94,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 256
checkpoint_config = dict(interval=4)
workflow = [('train', 1)]
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Original file line number Diff line number Diff line change
Expand Up @@ -102,7 +102,7 @@
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(
policy='CosineAnealing',
policy='CosineAnnealing',
min_lr=0,
warmup='linear',
warmup_by_epoch=True,
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Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 256
checkpoint_config = dict(interval=4)
workflow = [('train', 1)]
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Expand Up @@ -104,7 +104,7 @@
weight_decay=0.0001) # this lr is used for 8 gpus
optimizer_config = dict(grad_clip=dict(max_norm=40, norm_type=2))
# learning policy
lr_config = dict(policy='CosineAnealing', min_lr=0)
lr_config = dict(policy='CosineAnnealing', min_lr=0)
total_epochs = 256
checkpoint_config = dict(interval=4)
workflow = [('train', 1)]
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4 changes: 2 additions & 2 deletions docs/config.md
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Expand Up @@ -158,7 +158,7 @@ optimizer_config = dict( # Config used to build the optimizer hook
grad_clip=None) # Most of the methods do not use gradient clip
# learning policy
lr_config = dict( # Learning rate scheduler config used to register LrUpdater hook
policy='step', # Policy of scheduler, also support CosineAnealing, Cyclic, etc. Refer to details of supported LrUpdater from https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/lr_updater.py#L9
policy='step', # Policy of scheduler, also support CosineAnnealing, Cyclic, etc. Refer to details of supported LrUpdater from https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/lr_updater.py#L9
step=7) # Steps to decay the learning rate

total_epochs = 9 # Total epochs to train the model
Expand Down Expand Up @@ -364,7 +364,7 @@ optimizer_config = dict( # Config used to build the optimizer hook
grad_clip=dict(max_norm=40, norm_type=2)) # Use gradient clip
# learning policy
lr_config = dict( # Learning rate scheduler config used to register LrUpdater hook
policy='step', # Policy of scheduler, also support CosineAnealing, Cyclic, etc. Refer to details of supported LrUpdater from https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/lr_updater.py#L9
policy='step', # Policy of scheduler, also support CosineAnnealing, Cyclic, etc. Refer to details of supported LrUpdater from https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/lr_updater.py#L9
step=[40, 80]) # Steps to decay the learning rate
total_epochs = 100 # Total epochs to train the model
checkpoint_config = dict( # Config to set the checkpoint hook, Refer to https://github.com/open-mmlab/mmcv/blob/master/mmcv/runner/hooks/checkpoint.py for implementation
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