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Add bias to Classify() (#1601)

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Glenn Jocher authored and GitHub committed 2020-12-04 15:06:33 +01:00
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models/common.py
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@@ -1,7 +1,6 @@
# This file contains modules common to various models # This file contains modules common to various models
import math import math
import numpy as np import numpy as np
import torch import torch
import torch.nn as nn import torch.nn as nn
@@ -244,7 +243,7 @@ class Classify(nn.Module):
def __init__(self, c1, c2, k=1, s=1, p=None, g=1): # ch_in, ch_out, kernel, stride, padding, groups def __init__(self, c1, c2, k=1, s=1, p=None, g=1): # ch_in, ch_out, kernel, stride, padding, groups
super(Classify, self).__init__() super(Classify, self).__init__()
self.aap = nn.AdaptiveAvgPool2d(1) # to x(b,c1,1,1) self.aap = nn.AdaptiveAvgPool2d(1) # to x(b,c1,1,1)
self.conv = nn.Conv2d(c1, c2, k, s, autopad(k, p), groups=g, bias=False) # to x(b,c2,1,1) self.conv = nn.Conv2d(c1, c2, k, s, autopad(k, p), groups=g) # to x(b,c2,1,1)
self.flat = Flatten() self.flat = Flatten()
def forward(self, x): def forward(self, x):