22 lines
692 B
Python
22 lines
692 B
Python
import torch
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from torch.cuda.amp import autocast
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from models.flownet2.networks.resample2d_package.resample2d import Resample2d
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from models.steps.injectors import Injector
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def create_stereoscopic_injector(opt, env):
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type = opt['type']
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if type == 'stereoscopic_resample':
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return ResampleInjector(opt, env)
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return None
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class ResampleInjector(Injector):
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def __init__(self, opt, env):
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super(ResampleInjector, self).__init__(opt, env)
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self.resample = Resample2d()
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self.flow = opt['flowfield']
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def forward(self, state):
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with autocast(enabled=False):
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return {self.output: self.resample(state[self.input], state[self.flow])} |