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# Common training-related configs that are designed for "tools/lazyconfig_train_net.py"
# You can use your own instead, together with your own train_net.py
train = dict(
output_dir="./output",
init_checkpoint="",
max_iter=90000,
amp=dict(enabled=False), # options for Automatic Mixed Precision
ddp=dict( # options for DistributedDataParallel
broadcast_buffers=False,
find_unused_parameters=False,
fp16_compression=False,
),
checkpointer=dict(period=5000, max_to_keep=100), # options for PeriodicCheckpointer
eval_period=5000,
log_period=20,
device="cuda"
# ...
)
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