Traceback (most recent call last):


 "prune.py", line 389, in <module>

opt.perlayer_ratio,


 "prune.py", line 160, in test

m = getattr(module, 'batch_norm_%d' % i) # batch_norm layer


 "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 591, in __getattr__

type(self).__name__, name))
AttributeError: 'Sequential' object has no attribute 'batch_norm_0'
Traceback (most recent call last):


 "train_cosine_iterations_distributed.py", line 420, in <module>

optimizer.backward(loss)


 "/home/ycg/anaconda3/lib/python3.6/site-packages/apex-0.1-py3.6-linux-x86_64.egg/apex/fp16_utils/fp16_optimizer.py", line 482, in backward

self.loss_scaler.backward(loss.float())


 "/home/ycg/anaconda3/lib/python3.6/site-packages/apex-0.1-py3.6-linux-x86_64.egg/apex/fp16_utils/loss_scaler.py", line 45, in backward

scaled_loss.backward()


 "/home/ycg/anaconda3/lib/python3.6/site-packages/torch/tensor.py", line 102, in backward

torch.autograd.backward(self, gradient, retain_graph, create_graph)


 "/home/ycg/anaconda3/lib/python3.6/site-packages/torch/autograd/__init__.py", line 90, in backward

allow_unreachable=True)
# allow_unreachable flag


 "/home/ycg/anaconda3/lib/python3.6/site-packages/apex-0.1-py3.6-linux-x86_64.egg/apex/parallel/distributed.py", line 340, in allreduce_hook

if not self.callback_queued:


 "/home/ycg/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 535, in __getattr__

type(self).__name__, name))
AttributeError: 'DistributedDataParallel' object has no attribute 'callback_queued'
