Building model
 Loading data
   File 
"/opt/zebiao.zhou/anaconda2/lib/python2.7/site-packages/theano/gof/link.py", 
line 325, in raise_with_op
     reraise(exc_type, exc_value, exc_trace)
     reraise(exc_type, exc_value, exc_trace)
   File 
"/opt/zebiao.zhou/anaconda2/lib/python2.7/site-packages/theano/gof/link.py", 
line 325, in raise_with_op
     reraise(exc_type, exc_value, exc_trace)
 Building model
 Loading data
   File 
"/opt/zebiao.zhou/anaconda2/lib/python2.7/site-packages/theano/gof/link.py", 
line 325, in raise_with_op
     reraise(exc_type, exc_value, exc_trace)
     reraise(exc_type, exc_value, exc_trace)
   File "theano/scan_module/scan_perform.pyx", line 397, in 
theano.scan_module.scan_perform.perform 
(/opt/zebiao.zhou/.theano/compiledir_Linux-3.10-el7.x86_64-x86_64-with-centos-7.2.1511-Core-x86_64-2.7.13-64/scan_perform/mod.cpp:4490)
   File 
"/opt/zebiao.zhou/anaconda2/lib/python2.7/site-packages/theano/scan_module/scan_op.py",
 
line 989, in rval
     r = p(n, [x[0] for x in i], o)
   File 
"/opt/zebiao.zhou/anaconda2/lib/python2.7/site-packages/theano/scan_module/scan_op.py",
 
line 978, in p
     self, node)
   File "theano/scan_module/scan_perform.pyx", line 405, in 
theano.scan_module.scan_perform.perform 
(/opt/zebiao.zhou/.theano/compiledir_Linux-3.10-el7.x86_64-x86_64-with-centos-7.2.1511-Core-x86_64-2.7.13-64/scan_perform/mod.cpp:4606)
   File 
"/opt/zebiao.zhou/anaconda2/lib/python2.7/site-packages/theano/gof/link.py", 
line 325, in raise_with_op
     reraise(exc_type, exc_value, exc_trace)
   File "theano/scan_module/scan_perform.pyx", line 397, in 
theano.scan_module.scan_perform.perform 
(/opt/zebiao.zhou/.theano/compiledir_Linux-3.10-el7.x86_64-x86_64-with-centos-7.2.1511-Core-x86_64-2.7.13-64/scan_perform/mod.cpp:4490)
 ValueError: dimension mismatch in args to gemv (200,0)x(250)->(0)
 Apply node that caused the error: 
GpuGemv{no_inplace}(GpuSubtensor{int32:int32:}.0, TensorConstant{1.0}, 
GpuSubtensor{:int32:, int32:int32:}.0, GpuReshape{1}.0, TensorConstant{1.0})
 Toposort index: 27
 Inputs types: [CudaNdarrayType(float32, vector), TensorType(float32, 
scalar), CudaNdarrayType(float32, matrix), CudaNdarrayType(float32, 
vector), TensorType(float32, scalar)]
 Inputs shapes: [(0,), (), (200, 0), (250,), ()]
 Inputs strides: [(1,), (), (500, 1), (1,), ()]
 Inputs values: [CudaNdarray([]), array(1.0, dtype=float32), 
CudaNdarray([]), 'not shown', array(1.0, dtype=float32)]
 Outputs clients: [[GpuElemwise{Composite{(scalar_sigmoid(i0) * i1)}}[(0, 
0)](GpuGemv{no_inplace}.0, GpuReshape{1}.0)]]
 
 HINT: Re-running with most Theano optimization disabled could give you a 
back-trace of when this node was created. This can be done with by setting 
the Theano flag 'optimizer=fast_compile'. If that does not work, Theano 
optimizations can be disabled with 'optimizer=    None'.
 HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and 
storage map footprint of this apply node.
 Apply node that caused the error: 
for{gpu,scan_fn}(Elemwise{Composite{minimum(minimum(i0, i1), i2)}}.0, 
Elemwise{add,no_inplace}.0, Elemwise{add,no_inplace}.0, 
Subtensor{:int64:}.0, Subtensor{int64:int64:int8}.0, 
Subtensor{int64:int64:int8}.0, Elemwise{Composite{min    imum(minimum(i0, 
i1), i2)}}.0, ugW_copy[cuda], cW_copy[cuda], rgW_copy[cuda], 
rgb_copy[cuda], cb_copy[cuda], ugb_copy[cuda], <CudaNdarrayType(float32, 
3D)>)
 Toposort index: 24
 Inputs types: [TensorType(int64, scalar), TensorType(int32, vector), 
TensorType(int32, vector), TensorType(int64, vector), TensorType(int32, 
vector), TensorType(int32, vector), TensorType(int64, scalar), 
CudaNdarrayType(float32, matrix), CudaNdarrayType(float32, mat    rix), 
CudaNdarrayType(float32, matrix), CudaNdarrayType(float32, vector), 
CudaNdarrayType(float32, vector), CudaNdarrayType(float32, vector), 
CudaNdarrayType(float32, 3D)]
 Inputs shapes: [(), (256,), (256,), (256,), (256,), (256,), (), (250, 
700), (50, 500), (200, 500), (500,), (200,), (700,), (256, 6, 50)]
 Inputs strides: [(), (4,), (4,), (8,), (24,), (4,), (), (700, 1), (500, 
1), (500, 1), (1,), (1,), (1,), (300, 50, 1)]
 Inputs values: [array(256), 'not shown', 'not shown', 'not shown', 'not 
shown', 'not shown', array(256), 'not shown', 'not shown', 'not shown', 
'not shown', 'not shown', 'not shown', 'not shown']
 Outputs clients: [[GpuDot22(for{gpu,scan_fn}.0, lstmW_copy[cuda]), 
GpuGemv{inplace}(GpuCAReduce{add}{0,1}.0, TensorConstant{1.0}, 
for{gpu,scan_fn}.0, U_copy[cuda], TensorConstant{1.0}), 
GpuElemwise{Composite{(i0 * tanh((i1 + i2)))}}[(0, 1)](for{gpu,scan_fn}.0, 
GpuDo    t22.0, <CudaNdarrayType(float32, row)>)]]




who can help me~~i don‘t know how to solve it .

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