def forward(self, x):
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[0])
x = self.features(x)
x = x.view(-1, self.last_channel)
x = self.classifier(x)
x = BFPFullyConnet.transform_fc_offline(x, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[-1])
return x
def forward(self, x):
x = self.res3d(x)
logits = self.linear(x)
logits = BFPFullyConnet.transform_fc_offline(logits, self.exp_bit,
self.mantisa_bit,
self.opt_exp_act_list[-1])
return logits
def forward(self, x):
x = BFPActivation.transform_activation_offline(
x, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[0])
x = self.features(x)
x = self.logits(x)
x = BFPFullyConnet.transform_fc_offline(x, self.exp_bit,
self.mantisa_bit,
self.opt_exp_act_list[-1])
return x
def forward(self, x):
x = BFPActivation.transform_activation_offline(
x, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[0])
x = self.conv1(x)
#x = self.bn1(x) #Fused BN
x = BFPActivation.transform_activation_offline(
x, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[1])
x = self.relu(x)
x = self.maxpool(x)
x = self.layer1(x)
x = self.layer2(x)
x = self.layer3(x)
x = self.layer4(x)
x = self.avgpool(x)
x = x.view(x.size(0), -1)
x = self.fc(x)
x = BFPFullyConnet.transform_fc_offline(x, self.exp_bit,
self.mantisa_bit,
self.opt_exp_act_list[-1])
return x
def forward(self, x):
x = F.linear(x, self.weight, self.bias)
x = BFPFullyConnet.transform_fc_offline(
x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[self.start_exp_ind])
return x
def forward(self, x):
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[0], is_3d=True)
#x = self.bn1(self.conv1(x))
x = self.conv1(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[1], is_3d=True)
x = self.relu(x)
x = self.pool1(x)
#x = self.bn2(self.conv2(x))
x = self.conv2(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[2], is_3d=True)
x = self.relu(x)
x = self.pool2(x)
#x = self.bn3a(self.conv3a(x))
x = self.conv3a(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[3], is_3d=True)
x = self.relu(x)
#x = self.bn3b(self.conv3b(x))
x = self.conv3b(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[4], is_3d=True)
x = self.relu(x)
x = self.pool3(x)
#x = self.bn4a(self.conv4a(x))
x = self.conv4a(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[5], is_3d=True)
x = self.relu(x)
#x = self.bn4b(self.conv4b(x))
x = self.conv4b(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[6], is_3d=True)
x = self.relu(x)
x = self.pool4(x)
#x = self.bn5a(self.conv5a(x))
x = self.conv5a(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[7], is_3d=True)
x = self.relu(x)
#x = self.bn5b(self.conv5b(x))
x = self.conv5b(x)
x = BFPActivation.transform_activation_offline(x, self.exp_bit, self.mantisa_bit,
self.opt_exp_act_list[8], is_3d=True)
x = self.relu(x)
x = self.pool5(x)
x = x.view(-1, 8192)
x = self.fc6(x)
x = BFPFullyConnet.transform_fc_offline(x, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[9])
x = self.relu(x)
x = self.dropout(x)
x = self.fc7(x)
x = BFPFullyConnet.transform_fc_offline(x, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[10])
x = self.relu(x)
x = self.dropout(x)
logits = self.fc8(x)
#print (logits.shape)
x = BFPFullyConnet.transform_fc_offline(logits, self.exp_bit, self.mantisa_bit, self.opt_exp_act_list[11])
return logits