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basic_ops.py
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basic_ops.py
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import torch
import math
class Identity(torch.nn.Module):
def forward(self, input):
return input
class SegmentConsensus(torch.autograd.Function):
def __init__(self, consensus_type, dim=1):
self.consensus_type = consensus_type
self.dim = dim
self.shape = None
def forward(self, input_tensor):
self.shape = input_tensor.size()
if self.consensus_type == 'avg':
output = input_tensor.mean(dim=self.dim, keepdim=True)
elif self.consensus_type == 'identity':
output = input_tensor
else:
output = None
return output
def backward(self, grad_output):
if self.consensus_type == 'avg':
grad_in = grad_output.expand(self.shape) / float(self.shape[self.dim])
elif self.consensus_type == 'identity':
grad_in = grad_output
else:
grad_in = None
return grad_in
class ConsensusModule(torch.nn.Module):
def __init__(self, consensus_type, dim=1):
super(ConsensusModule, self).__init__()
self.consensus_type = consensus_type if consensus_type != 'rnn' else 'identity'
self.dim = dim
def forward(self, input):
return SegmentConsensus(self.consensus_type, self.dim)(input)