ResourceExhaustedErrorTraceback (most recent call last)
<ipython-input-8-cb1025b61acf> in <module>()
----> 1 history = model.fit_generator(train_generator,steps_per_epoch=100,epochs=30,validation_data=validation_generator,validation_steps=50)
/usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.pyc in wrapper(*args,**kwargs)
89 warnings.warn('Update your `' + object_name +
90 '` call to the Keras 2 API: ' + signature,stacklevel=2)
---> 91 return func(*args,**kwargs)
92 wrapper._original_function = func
93 return wrapper
/usr/local/lib/python2.7/dist-packages/keras/models.pyc in fit_generator(self,generator,steps_per_epoch,epochs,verbose,callbacks,validation_data,validation_steps,class_weight,max_queue_size,workers,use_multiprocessing,shuffle,initial_epoch)
1251 use_multiprocessing=use_multiprocessing,1252 shuffle=shuffle,-> 1253 initial_epoch=initial_epoch)
1254
1255 @interfaces.legacy_generator_methods_support
/usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.pyc in wrapper(*args,**kwargs)
92 wrapper._original_function = func
93 return wrapper
/usr/local/lib/python2.7/dist-packages/keras/engine/training.pyc in fit_generator(self,initial_epoch)
2242 outs = self.train_on_batch(x,y,2243 sample_weight=sample_weight,-> 2244 class_weight=class_weight)
2245
2246 if not isinstance(outs,list):
/usr/local/lib/python2.7/dist-packages/keras/engine/training.pyc in train_on_batch(self,x,sample_weight,class_weight)
1888 ins = x + y + sample_weights
1889 self._make_train_function()
-> 1890 outputs = self.train_function(ins)
1891 if len(outputs) == 1:
1892 return outputs[0]
/usr/local/lib/python2.7/dist-packages/keras/backend/tensorflow_backend.pyc in __call__(self,inputs)
2473 session = get_session()
2474 updated = session.run(fetches=fetches,feed_dict=feed_dict,-> 2475 **self.session_kwargs)
2476 return updated[:len(self.outputs)]
2477
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in run(self,fetches,feed_dict,options,run_metadata)
893 try:
894 result = self._run(None,options_ptr,--> 895 run_metadata_ptr)
896 if run_metadata:
897 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _run(self,handle,run_metadata)
1126 if final_fetches or final_targets or (handle and feed_dict_tensor):
1127 results = self._do_run(handle,final_targets,final_fetches,-> 1128 feed_dict_tensor,run_metadata)
1129 else:
1130 results = []
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_run(self,target_list,fetch_list,run_metadata)
1342 if handle is None:
1343 return self._do_call(_run_fn,self._session,feeds,targets,-> 1344 options,run_metadata)
1345 else:
1346 return self._do_call(_prun_fn,fetches)
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_call(self,fn,*args)
1361 except KeyError:
1362 pass
-> 1363 raise type(e)(node_def,op,message)
1364
1365 def _extend_graph(self):
ResourceExhaustedError: OOM when allocating tensor with shape[6272,512] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: training/RMSprop/mul_24 = Mul[T=DT_FLOAT,_device="/job:localhost/replica:0/task:0/device:GPU:0"](RMSprop/rho/read,training/RMSprop/Variable_8/read)]]
Hint: If you want to see a list of allocated tensors when OOM happens,add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
[[Node: metrics/acc/Mean_1/_109 = _Recv[client_terminated=false,recv_device="/job:localhost/replica:0/task:0/device:CPU:0",send_device="/job:localhost/replica:0/task:0/device:GPU:0",send_device_incarnation=1,tensor_name="edge_774_metrics/acc/Mean_1",tensor_type=DT_FLOAT,_device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Hint: If you want to see a list of allocated tensors when OOM happens,add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
Caused by op u'training/RMSprop/mul_24',defined at:
File "/usr/lib/python2.7/runpy.py",line 174,in _run_module_as_main
"__main__",fname,loader,pkg_name)
File "/usr/lib/python2.7/runpy.py",line 72,in _run_code
exec code in run_globals
File "/usr/local/lib/python2.7/dist-packages/ipykernel_launcher.py",line 16,in <module>
app.launch_new_instance()
File "/usr/local/lib/python2.7/dist-packages/traitlets/config/application.py",line 658,in launch_instance
app.start()
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelapp.py",line 486,in start
self.io_loop.start()
File "/usr/local/lib/python2.7/dist-packages/tornado/ioloop.py",line 888,in start
handler_func(fd_obj,events)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py",line 277,in null_wrapper
return fn(*args,**kwargs)
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py",line 450,in _handle_events
self._handle_recv()
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py",line 480,in _handle_recv
self._run_callback(callback,msg)
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py",line 432,in _run_callback
callback(*args,**kwargs)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py",**kwargs)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py",line 283,in dispatcher
return self.dispatch_shell(stream,msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py",line 233,in dispatch_shell
handler(stream,idents,line 399,in execute_request
user_expressions,allow_stdin)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/ipkernel.py",line 208,in do_execute
res = shell.run_cell(code,store_history=store_history,silent=silent)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/zmqshell.py",line 537,in run_cell
return super(ZMQInteractiveShell,self).run_cell(*args,**kwargs)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py",line 2718,in run_cell
interactivity=interactivity,compiler=compiler,result=result)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py",line 2822,in run_ast_nodes
if self.run_code(code,result):
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py",line 2882,in run_code
exec(code_obj,self.user_global_ns,self.user_ns)
File "<ipython-input-8-cb1025b61acf>",line 1,in <module>
history = model.fit_generator(train_generator,validation_steps=50)
File "/usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.py",line 91,in wrapper
return func(*args,**kwargs)
File "/usr/local/lib/python2.7/dist-packages/keras/models.py",line 1253,in fit_generator
initial_epoch=initial_epoch)
File "/usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.py",**kwargs)
File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py",line 2088,in fit_generator
self._make_train_function()
File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py",line 990,in _make_train_function
loss=self.total_loss)
File "/usr/local/lib/python2.7/dist-packages/keras/legacy/interfaces.py",**kwargs)
File "/usr/local/lib/python2.7/dist-packages/keras/optimizers.py",line 251,in get_updates
new_a = self.rho * a + (1. - self.rho) * K.square(g)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py",line 775,in _run_op
return getattr(ops.Tensor,operator)(a._AsTensor(),*args)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/math_ops.py",line 907,in binary_op_wrapper
return func(x,name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/math_ops.py",line 1131,in _mul_dispatch
return gen_math_ops._mul(x,name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_math_ops.py",line 2798,in _mul
"Mul",x=x,y=y,name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py",line 787,in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py",line 3160,in create_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py",line 1625,in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[6272,add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
我正在尝试使用Docker安装Keras，以使用GPU进行深度学习。我在Keras github（https://github.com/keras-team/keras/tree/master/docker）上，我不知道该怎么做。我是Docker的新手，我能够获取的Docker映像全部都使用了'docker pull'命令。但是我看不到Docker pull命令来获取keras。我不理解所提供的“制作”说明。
我一直在想让Keras与我的linux计算机一起运行。最初，我尝试将CUDA，TF和所有文件直接安装到我的计算机上，但是在放弃与所有软件的版本兼容性方面遇到了很多问题，因此我一直在尝试使用docker对其进行简化，但这并没有也很容易。我尝试了多个docker映像，包括ermaker / keras-jupyter和gw000 / keras-full，但都无法使它们工作。
使用gw000 / keras-full，我尝试使用Keras深度学习书中的cat分类器运行简单的神经网络，但收到一个错误消息，指出内存已被完全填满。我不知道为什么会收到该错误，这是一个简单的分类器，比我可以在旧笔记本电脑上运行的原因还要多，由于某种原因，它与我的RTX 2080TI一起爆炸了。
对于通过docker获得keras的工作版本的任何帮助，将不胜感激。
这是使用gw000 / keras-full的代码。我用它来启动带有GPU的Docker：
docker run -d $(ls /dev/nvidia* | xargs -I{} echo '--device={}') $(ls /usr/lib/*-linux-gnu/{libcuda,libnvidia}* | xargs -I{} echo '-v {}:{}:ro') -p 8888:8888 -v /home/name/Desktop:/srv gw000/keras-full
当我尝试运行模型训练时，这发生在第一个时期。我在错误中看到它正在尝试运行python 2，这可能是一个问题，因为它可能是用python 3编写的，但我不知道这是否是问题，以及如何更改为使用python 3。如前所述，该代码完全来自Keras深度学习书，并且在我的旧笔记本电脑上可以完美地工作。我一辈子都无法弄清楚为什么我的PC上无法运行任何东西。
Epoch 1/30
*SEE THE ATTACHED CODE snIP FOR THE ERROR I GET*