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| """
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| @Author : Peike Li
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| @Contact : peike.li@yahoo.com
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| @File : kl_loss.py
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| @Time : 7/23/19 4:02 PM
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| @Desc :
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| @License : This source code is licensed under the license found in the
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| LICENSE file in the root directory of this source tree.
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| """
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| import torch
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| import torch.nn.functional as F
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| from torch import nn
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| from datasets.target_generation import generate_edge_tensor
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| class ConsistencyLoss(nn.Module):
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| def __init__(self, ignore_index=255):
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| super(ConsistencyLoss, self).__init__()
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| self.ignore_index=ignore_index
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| def forward(self, parsing, edge, label):
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| parsing_pre = torch.argmax(parsing, dim=1)
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| parsing_pre[label==self.ignore_index]=self.ignore_index
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| generated_edge = generate_edge_tensor(parsing_pre)
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| edge_pre = torch.argmax(edge, dim=1)
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| v_generate_edge = generated_edge[label!=255]
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| v_edge_pre = edge_pre[label!=255]
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| v_edge_pre = v_edge_pre.type(torch.cuda.FloatTensor)
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| positive_union = (v_generate_edge==1)&(v_edge_pre==1)
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| return F.smooth_l1_loss(v_generate_edge[positive_union].squeeze(0), v_edge_pre[positive_union].squeeze(0))
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