我正在研究openface。Openface有未知分类python代码e。
我正在测试lfw-classification-unknown.py's
火车部分。它有训练使用
nolearn-DBN classifier
我安装了nolearn version 0.5
.
DBN classifier
有一个函数调用/usr/local/lib/python2.7/dist-packages/gnumpy.py
,我有错误
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 738, in as_numpy_array
if self.size==0: return numpy.zeros(self.shape, dtype)
AttributeError: 'garray' object has no attribute 'size'
如何修复错误?
整个错误是
Traceback (most recent call last):
File "/usr/lib/python2.7/pdb.py", line 1314, in main
pdb._runscript(mainpyfile)
File "/usr/lib/python2.7/pdb.py", line 1233, in _runscript
self.run(statement)
File "/usr/lib/python2.7/bdb.py", line 400, in run
exec cmd in globals, locals
File "<string>", line 1, in <module>
File "evaluation/lfw-classification-unknown.py", line 519, in <module>
train(args)
File "evaluation/lfw-classification-unknown.py", line 130, in train
clf.fit(embeddings, labelsNum)
File "/usr/local/lib/python2.7/dist-packages/nolearn/dbn.py", line 409, in fit
self.use_dropout,
File "/usr/local/lib/python2.7/dist-packages/gdbn/dbn.py", line 202, in fineTune
err, outMB = step(inpMB, targMB, self.learnRates, self.momentum, self.L2Costs, useDropout)
File "/usr/local/lib/python2.7/dist-packages/gdbn/dbn.py", line 296, in stepNesterov
targetBatch = targetBatch if isinstance(targetBatch, gnp.garray) else gnp.garray(targetBatch)
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 735, in __new__
def __new__(cls, *args, **kwarg): return object.__new__(cls)
File "/usr/lib/python2.7/bdb.py", line 53, in trace_dispatch
return self.dispatch_return(frame, arg)
File "/usr/lib/python2.7/bdb.py", line 88, in dispatch_return
self.user_return(frame, arg)
File "/usr/lib/python2.7/pdb.py", line 190, in user_return
self.interaction(frame, None)
File "/usr/lib/python2.7/pdb.py", line 209, in interaction
self.print_stack_entry(self.stack[self.curindex])
File "/usr/lib/python2.7/pdb.py", line 900, in print_stack_entry
prompt_prefix)
File "/usr/lib/python2.7/bdb.py", line 381, in format_stack_entry
s = s + repr.repr(rv)
File "/usr/lib/python2.7/repr.py", line 24, in repr
return self.repr1(x, self.maxlevel)
File "/usr/lib/python2.7/repr.py", line 34, in repr1
s = __builtin__.repr(x)
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 1133, in __repr__
def __repr__(self): return self.as_numpy_array().__repr__().replace('array(', 'garray(').replace('\n', '\n ').replace(', dtype=float32', '').replace(', dtype=float64', '') # 64 happens for empty arrays
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 738, in as_numpy_array
if self.size==0: return numpy.zeros(self.shape, dtype)
AttributeError: 'garray' object has no attribute 'size'
> Uncaught exception. Entering post mortem debugging
Running 'cont' or 'step' will restart the program
> /usr/local/lib/python2.7/dist-packages/gnumpy.py(738)as_numpy_array()
-> if self.size==0: return numpy.zeros(self.shape, dtype)
编辑:如果不在调试模式下,错误如下。
Traceback (most recent call last):
File "evaluation/lfw-classification-unknown.py", line 519, in <module>
train(args)
File "evaluation/lfw-classification-unknown.py", line 130, in train
clf.fit(embeddings, labelsNum)
File "/usr/local/lib/python2.7/dist-packages/nolearn/dbn.py", line 407, in fit
self.use_dropout,
File "/usr/local/lib/python2.7/dist-packages/gdbn/dbn.py", line 202, in fineTune
err, outMB = step(inpMB, targMB, self.learnRates, self.momentum, self.L2Costs, useDropout)
File "/usr/local/lib/python2.7/dist-packages/gdbn/dbn.py", line 303, in stepNesterov
errSignals, outputActs, error = self.fpropBprop(inputBatch, targetBatch, useDropout)
File "/usr/local/lib/python2.7/dist-packages/gdbn/dbn.py", line 262, in fpropBprop
outputErrSignal = -self.outputActFunct.dErrordNetInput(targetBatch, self.state[-1], outputActs)
File "/usr/local/lib/python2.7/dist-packages/gdbn/activationFunctions.py", line 138, in dErrordNetInput
return acts - targets
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 965, in __sub__
else: return self + -as_garray(other) # if i need to broadcast, making use of the row add and col add methods is probably faster
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 926, in __add__
def __add__(self, other): return _check_number_types(self._broadcastable_op(as_garray_or_scalar(other), 'add'))
File "/usr/local/lib/python2.7/dist-packages/gnumpy.py", line 614, in _broadcastable_op
if reduce(operator.or_, ( other.shape[i] not in (1, self.shape[i]) for i in range(self.ndim)), False): raise ValueError('shape mismatch: objects cannot be broadcast to a single shape')
ValueError: shape mismatch: objects cannot be broadcast to a single shape