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from ..dataloader import load_batch
from ..dataset_configs import FLYING_CHAIRS_DATASET_CONFIG
from ..training_schedules import LONG_SCHEDULE
from .flownet_cs import FlowNetCS
# Create a new network
net = FlowNetCS()
# Load a batch of data
input_a, input_b, flow = load_batch(FLYING_CHAIRS_DATASET_CONFIG, 'sample', net.global_step)
# Train on the data
net.train(
log_dir='./logs/flownet_cs',
training_schedule=LONG_SCHEDULE,
input_a=input_a,
input_b=input_b,
flow=flow,
# Load trained weights for C part of network
checkpoints={'./checkpoints/FlowNetC/flownet-C.ckpt-0': ('FlowNetCS/FlowNetC', 'FlowNetCS')}
)
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