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import torch
import torch.nn as nn
from functools import reduce
from torch.autograd import Variable
def load_places_resnet152(weight_file):
model = OldResNet152()
state_dict = torch.load(weight_file)
model.load_state_dict(state_dict)
return model
class LambdaBase(nn.Sequential):
def __init__(self, fn, *args):
super(LambdaBase, self).__init__(*args)
self.lambda_func = fn
def forward_prepare(self, input):
output = []
for module in self._modules.values():
output.append(module(input))
return output if output else input
class Lambda(LambdaBase):
def forward(self, input):
return self.lambda_func(self.forward_prepare(input))
class LambdaMap(LambdaBase):
def forward(self, input):
return list(map(self.lambda_func,self.forward_prepare(input)))
class LambdaReduce(LambdaBase):
def forward(self, input):
return reduce(self.lambda_func,self.forward_prepare(input))
class OldResNet152(nn.Sequential):
def __init__(self):
children = [
# resnet152_places365 = nn.Sequential( # Sequential,
nn.Conv2d(3,64,(7, 7),(2, 2),(3, 3),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.MaxPool2d((3, 3),(2, 2),(1, 1)),
nn.Sequential( # Sequential,
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(64,64,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv2d(64,64,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv2d(64,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
),
nn.Sequential( # Sequential,
nn.Conv2d(64,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
),
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(256,64,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv2d(64,64,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv2d(64,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(256,64,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv2d(64,64,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(64),
nn.ReLU(),
nn.Conv2d(64,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
),
nn.Sequential( # Sequential,
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(256,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(2, 2),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
nn.Sequential( # Sequential,
nn.Conv2d(256,512,(1, 1),(2, 2),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,128,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,128,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(128),
nn.ReLU(),
nn.Conv2d(128,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
),
nn.Sequential( # Sequential,
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(512,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(2, 2),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
nn.Sequential( # Sequential,
nn.Conv2d(512,1024,(1, 1),(2, 2),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,256,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,256,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(256),
nn.ReLU(),
nn.Conv2d(256,1024,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(1024),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
),
nn.Sequential( # Sequential,
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(1024,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
nn.ReLU(),
nn.Conv2d(512,512,(3, 3),(2, 2),(1, 1),1,1,bias=False),
nn.BatchNorm2d(512),
nn.ReLU(),
nn.Conv2d(512,2048,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(2048),
),
nn.Sequential( # Sequential,
nn.Conv2d(1024,2048,(1, 1),(2, 2),(0, 0),1,1,bias=False),
nn.BatchNorm2d(2048),
),
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(2048,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
nn.ReLU(),
nn.Conv2d(512,512,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(512),
nn.ReLU(),
nn.Conv2d(512,2048,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(2048),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
nn.Sequential( # Sequential,
LambdaMap(lambda x: x, # ConcatTable,
nn.Sequential( # Sequential,
nn.Conv2d(2048,512,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(512),
nn.ReLU(),
nn.Conv2d(512,512,(3, 3),(1, 1),(1, 1),1,1,bias=False),
nn.BatchNorm2d(512),
nn.ReLU(),
nn.Conv2d(512,2048,(1, 1),(1, 1),(0, 0),1,1,bias=False),
nn.BatchNorm2d(2048),
),
Lambda(lambda x: x), # Identity,
),
LambdaReduce(lambda x,y: x+y), # CAddTable,
nn.ReLU(),
),
),
nn.AvgPool2d((7, 7),(1, 1)),
Lambda(lambda x: x.view(x.size(0),-1)), # View,
nn.Sequential(Lambda(lambda x: x.view(1,-1) if 1==len(x.size()) else x )
,nn.Linear(2048,365)), # Linear,
]
super(OldResNet152, self).__init__(*children)
|