http://caffecn.cn/?/question/509
使用end2end的方法训练py-faster-rcnn， 把 TRAIN.IMS_PER_BATCH 设置为 2的时候会出错，显示data和label的batch size不一致。如下：
在源码lib/rpn/anchor_target_layer.py中可以看到，anchor_target_layer的top[0] 的batch size被写死为1了，
这应该就是为什么会出现data 和 label 的batch size不一致错误的原因吧吧吧？
但是，为什么anchor_target_layer.py里面的batch size只能是0呢？ 好像官方给的experiments\cfgs\
faster_rcnn_end2end.yml 里面也是把 TRAIN.IMS_PER_BATCH设置为1 了。 是不是end2end训练的时候，TRAIN.IMS_PER_BATCH只能为1？为什么呢？？
可以怎样修改代码使得TRAIN.IMS_PER_BATCH 为任意值吗？
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Training with Mini-Batch size greater than 1 #267 https://github.com/rbgirshick/py-faster-rcnn/issues/267
how to change the batchsize when training the rpn model?#51 https://github.com/rbgirshick/py-faster-rcnn/issues/51
@rbgirshick:::::It's just not implemented. A reasonable workaround, which is already used, is to set iter_size: N in the solver, in which N is the batch size you want (currently 2 for end to end training). This may be slightly less efficient than batching, but since the inputs are spatially large operating on one image at a time isn't too bad (plus if you use more than one image there's some wasted computation where padding is introduced to fill the 4D tensor).
Batch size of faster rcnn #487 https://github.com/rbgirshick/py-faster-rcnn/issues/487