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_base_ = [ |
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'../../_base_/default_runtime.py', |
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'../../_base_/recog_datasets/seg_toy_data.py', |
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'../../_base_/recog_models/seg.py', |
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'../../_base_/recog_pipelines/seg_pipeline.py', |
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] |
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train_list = {{_base_.train_list}} |
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test_list = {{_base_.test_list}} |
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|
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train_pipeline = {{_base_.train_pipeline}} |
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test_pipeline = {{_base_.test_pipeline}} |
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optimizer = dict(type='Adam', lr=1e-4) |
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optimizer_config = dict(grad_clip=None) |
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lr_config = dict(policy='step', step=[3, 4]) |
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total_epochs = 5 |
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data = dict( |
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samples_per_gpu=8, |
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workers_per_gpu=1, |
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train=dict( |
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type='UniformConcatDataset', |
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datasets=train_list, |
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pipeline=train_pipeline), |
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val=dict( |
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type='UniformConcatDataset', |
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datasets=test_list, |
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pipeline=test_pipeline), |
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test=dict( |
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type='UniformConcatDataset', |
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datasets=test_list, |
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pipeline=test_pipeline)) |
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evaluation = dict(interval=1, metric='acc') |
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|
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find_unused_parameters = True |
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