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https://github.com/open-mmlab/mmselfsup.git
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update places205 linear classification config
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parent
30c14b415e
commit
c3f7d6adf6
@ -46,7 +46,7 @@ test_pipeline = [
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]
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]
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data = dict(
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data = dict(
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imgs_per_gpu=32, # total 32x8=256
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imgs_per_gpu=32, # total 32x8=256
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workers_per_gpu=5,
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workers_per_gpu=4,
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train=dict(
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train=dict(
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type=dataset_type,
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type=dataset_type,
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data_source=dict(
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data_source=dict(
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@ -65,7 +65,7 @@ custom_hooks = [
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dataset=data['val'],
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dataset=data['val'],
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initial=True,
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initial=True,
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interval=10,
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interval=10,
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imgs_per_gpu=128,
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imgs_per_gpu=32,
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workers_per_gpu=4,
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workers_per_gpu=4,
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eval_param=dict(topk=(1, )))
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eval_param=dict(topk=(1, )))
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]
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]
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@ -78,7 +78,7 @@ optimizer = dict(
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paramwise_options=dict(norm_decay_mult=0.),
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paramwise_options=dict(norm_decay_mult=0.),
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nesterov=True)
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nesterov=True)
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# learning policy
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# learning policy
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lr_config = dict(policy='step', step=[30, 60, 90])
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lr_config = dict(policy='step', step=[7, 14, 21])
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checkpoint_config = dict(interval=10)
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checkpoint_config = dict(interval=10)
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# runtime settings
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# runtime settings
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total_epochs = 100
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total_epochs = 28
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@ -46,7 +46,7 @@ test_pipeline = [
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]
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]
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data = dict(
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data = dict(
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imgs_per_gpu=32, # total 32x8=256
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imgs_per_gpu=32, # total 32x8=256
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workers_per_gpu=5,
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workers_per_gpu=4,
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train=dict(
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train=dict(
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type=dataset_type,
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type=dataset_type,
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data_source=dict(
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data_source=dict(
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@ -65,7 +65,7 @@ custom_hooks = [
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dataset=data['val'],
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dataset=data['val'],
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initial=True,
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initial=True,
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interval=10,
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interval=10,
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imgs_per_gpu=128,
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imgs_per_gpu=32,
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workers_per_gpu=4,
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workers_per_gpu=4,
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eval_param=dict(topk=(1, )))
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eval_param=dict(topk=(1, )))
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]
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]
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@ -78,7 +78,7 @@ optimizer = dict(
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paramwise_options=dict(norm_decay_mult=0.),
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paramwise_options=dict(norm_decay_mult=0.),
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nesterov=True)
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nesterov=True)
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# learning policy
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# learning policy
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lr_config = dict(policy='step', step=[30, 60, 90])
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lr_config = dict(policy='step', step=[7, 14, 21])
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checkpoint_config = dict(interval=10)
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checkpoint_config = dict(interval=10)
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# runtime settings
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# runtime settings
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total_epochs = 100
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total_epochs = 28
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