I have never seen this error and I am unable to understand it. Any help
will be much appreciated.
Theano 0.9rc3 using the cuda backend.
storage_map=getattr(self.fn, 'storage_map', None))
File
"/Users/ragav/anaconda/lib/python2.7/site-packages/theano/gof/link.py",
line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File
"/Users/ragav/anaconda/lib/python2.7/site-packages/theano/compile/function_module.py",
line 884, in __call__
self.fn() if output_subset is None else\
AssertionError: Theano Assert failed!
Apply node that caused the error: Assert{msg='Theano Assert
failed!'}(GpuElemwise{Composite{tanh((i0 + i1))}}[(0, 0)].0,
TensorConstant{False})
Toposort index: 140
Inputs types: [CudaNdarrayType(float32, 4D), TensorType(bool, scalar)]
Inputs shapes: [(100, 1, 28, 28), ()]
Inputs strides: [(784, 0, 28, 1), ()]
Inputs values: ['not shown', array(False, dtype=bool)]
Inputs type_num: ['', 0]
Outputs clients: [[Assert{msg='Theano Assert failed!'}(Assert{msg='Theano
Assert failed!'}.0, TensorConstant{False})]]
Debugprint of the apply node:
Assert{msg='Theano Assert failed!'} [id A] <CudaNdarrayType(float32, 4D)>
''
|GpuElemwise{Composite{tanh((i0 + i1))}}[(0, 0)] [id B]
<CudaNdarrayType(float32, 4D)> ''
| |GpuDnnConvGradI{algo='none', inplace=True} [id C]
<CudaNdarrayType(float32, 4D)> ''
| | |GpuContiguous [id D] <CudaNdarrayType(float32, 4D)> ''
| | | |filterbank [id E] <CudaNdarrayType(float32, 4D)>
| | |GpuContiguous [id F] <CudaNdarrayType(float32, 4D)> ''
| | | |GpuReshape{4} [id G] <CudaNdarrayType(float32, 4D)> ''
| | | |GpuElemwise{Composite{(i0 * ((i1 + i2) + Abs((i1 + i2))))}}[(0,
1)] [id H] <CudaNdarrayType(float32, matrix)> ''
| | | | |CudaNdarrayConstant{[[ 0.5]]} [id I] <CudaNdarrayType(float32,
(True, True))>
| | | | |GpuDot22 [id J] <CudaNdarrayType(float32, matrix)> ''
| | | | | |GpuElemwise{Composite{(i0 * ((i1 + i2) + Abs((i1 +
i2))))}}[(0, 1)] [id K] <CudaNdarrayType(float32, matrix)> ''
| | | | | | |CudaNdarrayConstant{[[ 0.5]]} [id I]
<CudaNdarrayType(float32, (True, True))>
| | | | | | |GpuDot22 [id L] <CudaNdarrayType(float32, matrix)> ''
| | | | | | | |GpuReshape{2} [id M] <CudaNdarrayType(float32, matrix)>
''
| | | | | | | | |GpuJoin [id N] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | |TensorConstant{0} [id O] <TensorType(int8, scalar)>
| | | | | | | | | |GpuElemwise{Composite{(i0 * cos(i1))},no_inplace} [id
P] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | |GpuElemwise{Composite{sqrt((i0 *
log(i1)))},no_inplace} [id Q] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | | |CudaNdarrayConstant{[-2.]} [id R]
<CudaNdarrayType(float32, (True,))>
| | | | | | | | | | | |GpuSubtensor{:int64:} [id S]
<CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | | |GPU_mrg_uniform{CudaNdarrayType(float32,
vector),inplace}.1 [id T] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | | | |<CudaNdarrayType(float32, vector)> [id U]
<CudaNdarrayType(float32, vector)>
| | | | | | | | | | | | |TensorConstant{(1,) of 1000} [id V]
<TensorType(int64, (True,))>
| | | | | | | | | | | |Constant{500} [id W] <int64>
| | | | | | | | | | |GpuElemwise{Mul}[(0, 1)] [id X]
<CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | |CudaNdarrayConstant{[ 6.28318548]} [id Y]
<CudaNdarrayType(float32, (True,))>
| | | | | | | | | | |GpuSubtensor{int64::} [id Z]
<CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | |GPU_mrg_uniform{CudaNdarrayType(float32,
vector),inplace}.1 [id T] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | | |Constant{500} [id W] <int64>
| | | | | | | | | |GpuElemwise{Composite{(i0 * sin(i1))}}[(0, 0)] [id
BA] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | |GpuElemwise{Composite{sqrt((i0 *
log(i1)))},no_inplace} [id Q] <CudaNdarrayType(float32, vector)> ''
| | | | | | | | | |GpuElemwise{Mul}[(0, 1)] [id X]
<CudaNdarrayType(float32, vector)> ''
| | | | | | | | |TensorConstant{[100 10]} [id BB] <TensorType(int64,
vector)>
| | | | | | | |weights [id BC] <CudaNdarrayType(float32, matrix)>
| | | | | | |GpuDimShuffle{x,0} [id BD] <CudaNdarrayType(float32, row)>
''
| | | | | | |bias [id BE] <CudaNdarrayType(float32, vector)>
| | | | | |weights [id BF] <CudaNdarrayType(float32, matrix)>
| | | | |GpuDimShuffle{x,0} [id BG] <CudaNdarrayType(float32, row)> ''
| | | | |bias [id BH] <CudaNdarrayType(float32, vector)>
| | | |TensorConstant{[100 10 13 13]} [id BI] <TensorType(int64,
vector)>
| | |GpuAllocEmpty [id BJ] <CudaNdarrayType(float32, 4D)> ''
| | | |TensorConstant{100} [id BK] <TensorType(int64, scalar)>
| | | |Shape_i{1} [id BL] <TensorType(int64, scalar)> ''
| | | | |filterbank [id E] <CudaNdarrayType(float32, 4D)>
| | | |TensorConstant{28} [id BM] <TensorType(int64, scalar)>
| | | |TensorConstant{28} [id BN] <TensorType(int64, scalar)>
| | |GpuDnnConvDesc{border_mode='valid', subsample=(2, 2),
conv_mode='conv', precision='float32'} [id BO]
<CDataType{cudnnConvolutionDescriptor_t}> ''
| | | |MakeVector{dtype='int64'} [id BP] <TensorType(int64, vector)> ''
| | | | |TensorConstant{100} [id BK] <TensorType(int64, scalar)>
| | | | |Shape_i{1} [id BL] <TensorType(int64, scalar)> ''
| | | | |TensorConstant{28} [id BM] <TensorType(int64, scalar)>
| | | | |TensorConstant{28} [id BN] <TensorType(int64, scalar)>
| | | |MakeVector{dtype='int64'} [id BQ] <TensorType(int64, vector)> ''
| | | |Shape_i{0} [id BR] <TensorType(int64, scalar)> ''
| | | | |filterbank [id E] <CudaNdarrayType(float32, 4D)>
| | | |Shape_i{1} [id BL] <TensorType(int64, scalar)> ''
| | | |Shape_i{2} [id BS] <TensorType(int64, scalar)> ''
| | | | |filterbank [id E] <CudaNdarrayType(float32, 4D)>
| | | |Shape_i{3} [id BT] <TensorType(int64, scalar)> ''
| | | |filterbank [id E] <CudaNdarrayType(float32, 4D)>
| | |Constant{1.0} [id BU] <float32>
| | |Constant{0.0} [id BV] <float32>
| |GpuDimShuffle{x,0,x,x} [id BW] <CudaNdarrayType(float32, (True, False,
True, True))> ''
| |bias [id BX] <CudaNdarrayType(float32, vector)>
|TensorConstant{False} [id BY] <TensorType(bool, scalar)>
Storage map footprint:
- <CudaNdarrayType(float32, matrix)>, Shared Input, Shape: (50000, 784),
ElemSize: 4 Byte(s), TotalSize: 156800000 Byte(s)
- weights, Shared Input, Shape: (1200, 1690), ElemSize: 4 Byte(s),
TotalSize: 8112000 Byte(s)
- weights, Shared Input, Shape: (1250, 1200), ElemSize: 4 Byte(s),
TotalSize: 6000000 Byte(s)
- weights, Shared Input, Shape: (240, 1200), ElemSize: 4 Byte(s),
TotalSize: 1152000 Byte(s)
- GpuElemwise{Composite{tanh((i0 + i1))}}[(0, 0)].0, Shape: (100, 1, 28,
28), ElemSize: 4 Byte(s), TotalSize: 313600 Byte(s)
- <CudaNdarrayType(float32, vector)>, Shared Input, Shape: (50000,),
ElemSize: 4 Byte(s), TotalSize: 200000 Byte(s)
- weights, Shared Input, Shape: (10, 1200), ElemSize: 4 Byte(s),
TotalSize: 48000 Byte(s)
- filterbank, Shared Input, Shape: (50, 20, 3, 3), ElemSize: 4 Byte(s),
TotalSize: 36000 Byte(s)
- GpuContiguous.0, Shape: (50, 20, 3, 3), ElemSize: 4 Byte(s), TotalSize:
36000 Byte(s)
- bias, Shared Input, Shape: (1690,), ElemSize: 4 Byte(s), TotalSize: 6760
Byte(s)
- bias, Shared Input, Shape: (1200,), ElemSize: 4 Byte(s), TotalSize: 4800
Byte(s)
- bias, Shared Input, Shape: (1200,), ElemSize: 4 Byte(s), TotalSize: 4800
Byte(s)
- bias, Shared Input, Shape: (1200,), ElemSize: 4 Byte(s), TotalSize: 4800
Byte(s)
- GPU_mrg_uniform{CudaNdarrayType(float32, vector),inplace}.0, Shape:
(996,), ElemSize: 4 Byte(s), TotalSize: 3984 Byte(s)
- <CudaNdarrayType(float32, vector)>, Shared Input, Shape: (996,),
ElemSize: 4 Byte(s), TotalSize: 3984 Byte(s)
- filterbank, Shared Input, Shape: (20, 1, 5, 5), ElemSize: 4 Byte(s),
TotalSize: 2000 Byte(s)
- weights, Shared Input, Shape: (240, 1), ElemSize: 4 Byte(s), TotalSize:
960 Byte(s)
- filterbank, Shared Input, Shape: (10, 1, 3, 3), ElemSize: 4 Byte(s),
TotalSize: 360 Byte(s)
- bias, Shared Input, Shape: (50,), ElemSize: 4 Byte(s), TotalSize: 200
Byte(s)
- GpuDimShuffle{x,0,x,x}.0, Shape: (1, 50, 1, 1), ElemSize: 4 Byte(s),
TotalSize: 200 Byte(s)
- bias, Shared Input, Shape: (20,), ElemSize: 4 Byte(s), TotalSize: 80
Byte(s)
- GpuDimShuffle{x,0,x,x}.0, Shape: (1, 20, 1, 1), ElemSize: 4 Byte(s),
TotalSize: 80 Byte(s)
- MakeVector{dtype='int64'}.0, Shape: (6,), ElemSize: 8 Byte(s),
TotalSize: 48 Byte(s)
- Join.0, Shape: (4,), ElemSize: 8 Byte(s), TotalSize: 32 Byte(s)
- TensorConstant{[100 20 12 12]}, Shape: (4,), ElemSize: 8 Byte(s),
TotalSize: 32 Byte(s)
- TensorConstant{[100 1 28 28]}, Shape: (4,), ElemSize: 8 Byte(s),
TotalSize: 32 Byte(s)
- TensorConstant{[100 10 13 13]}, Shape: (4,), ElemSize: 8 Byte(s),
TotalSize: 32 Byte(s)
- TensorConstant{[100 28 28]}, Shape: (3,), ElemSize: 8 Byte(s),
TotalSize: 24 Byte(s)
- TensorConstant{(2,) of 0}, Shape: (2,), ElemSize: 8 Byte(s), TotalSize:
16 Byte(s)
- TensorConstant{[ 100 1250]}, Shape: (2,), ElemSize: 8 Byte(s),
TotalSize: 16 Byte(s)
- MakeVector{dtype='int64'}.0, Shape: (2,), ElemSize: 8 Byte(s),
TotalSize: 16 Byte(s)
- TensorConstant{[100 10]}, Shape: (2,), ElemSize: 8 Byte(s), TotalSize:
16 Byte(s)
- MakeVector{dtype='int64'}.0, Shape: (2,), ElemSize: 8 Byte(s),
TotalSize: 16 Byte(s)
- TensorConstant{(2,) of 2}, Shape: (2,), ElemSize: 8 Byte(s), TotalSize:
16 Byte(s)
- MakeVector{dtype='int64'}.0, Shape: (2,), ElemSize: 8 Byte(s),
TotalSize: 16 Byte(s)
- TensorConstant{[100 -1]}, Shape: (2,), ElemSize: 8 Byte(s), TotalSize:
16 Byte(s)
- Constant{3}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Shape_i{1}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Constant{2}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Shape_i{1}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{-1}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Subtensor{int64}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Constant{0}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Assert{msg='The convolution would produce an invalid shape (dim[1] <
0).'}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Elemwise{mul,no_inplace}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize:
8.0 Byte(s)
- index, Input, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Constant{4}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{28}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Assert{msg='The convolution would produce an invalid shape (dim[2] <=
0).'}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{12}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Shape_i{0}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Assert{msg='The convolution would produce an invalid shape (dim[3] <=
0).'}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{28}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Assert{msg='The convolution would produce an invalid shape (dim[1] <
0).'}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{(1,) of 1000}, Shape: (1,), ElemSize: 8 Byte(s),
TotalSize: 8 Byte(s)
- Assert{msg='The convolution would produce an invalid shape (dim[2] <=
0).'}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Assert{msg='The convolution would produce an invalid shape (dim[3] <=
0).'}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Constant{1}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{(1,) of 100}, Shape: (1,), ElemSize: 8 Byte(s),
TotalSize: 8 Byte(s)
- TensorConstant{5}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{100}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Constant{500}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{28}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- TensorConstant{28}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- Elemwise{Composite{(i0 + (((i1 + Composite{Switch(LT(i0, i1), i1,
i0)}(i2, i3)) - Switch(LT(Composite{Switch(LT(i0, i1), i1,
i0)}(Composite{Switch(GE(i0, i1), i1, i0)}(i4, i2), i3),
Composite{Switch(LT(i0, i1), i1, i0)}(i2, i3)), Composite{Switch(LT(i0,
i1), i1, i0)}(Composite{Switch(GE(i0, i1), i1, i0)}(i4, i2), i3),
Composite{Switch(LT(i0, i1), i1, i0)}(i2, i3))) // i5))}}[(0, 2)].0, Shape:
(), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- TensorConstant{1}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Subtensor{int64}.0, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0
Byte(s)
- TensorConstant{0}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- Constant{5}, Shape: (), ElemSize: 8 Byte(s), TotalSize: 8.0 Byte(s)
- GpuSubtensor{int64}.0, Shape: (), ElemSize: 4 Byte(s), TotalSize: 4.0
Byte(s)
- GpuCAReduce{add}{1,1}.0, Shape: (), ElemSize: 4 Byte(s), TotalSize: 4.0
Byte(s)
- Constant{1.0}, Shape: (), ElemSize: 4 Byte(s), TotalSize: 4.0 Byte(s)
- CudaNdarrayConstant{[-2.]}, Shape: (1,), ElemSize: 4 Byte(s), TotalSize:
4 Byte(s)
- GpuSubtensor{int64}.0, Shape: (), ElemSize: 4 Byte(s), TotalSize: 4.0
Byte(s)
- CudaNdarrayConstant{-0.5}, Shape: (), ElemSize: 4 Byte(s), TotalSize:
4.0 Byte(s)
- bias, Shared Input, Shape: (1,), ElemSize: 4 Byte(s), TotalSize: 4
Byte(s)
- CudaNdarrayConstant{[[ 0.5]]}, Shape: (1, 1), ElemSize: 4 Byte(s),
TotalSize: 4 Byte(s)
- CudaNdarrayConstant{0.5}, Shape: (), ElemSize: 4 Byte(s), TotalSize: 4.0
Byte(s)
- bias, Shared Input, Shape: (1,), ElemSize: 4 Byte(s), TotalSize: 4
Byte(s)
- CudaNdarrayConstant{[ 6.28318548]}, Shape: (1,), ElemSize: 4 Byte(s),
TotalSize: 4 Byte(s)
- CudaNdarrayConstant{[[[[ 0.5]]]]}, Shape: (1, 1, 1, 1), ElemSize: 4
Byte(s), TotalSize: 4 Byte(s)
- Constant{0.0}, Shape: (), ElemSize: 4 Byte(s), TotalSize: 4.0 Byte(s)
- TensorConstant{10}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0
Byte(s)
- TensorConstant{20}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0
Byte(s)
- TensorConstant{0}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0 Byte(s)
- TensorConstant{5}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0 Byte(s)
- TensorConstant{3}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0 Byte(s)
- TensorConstant{1}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0 Byte(s)
- Elemwise{eq,no_inplace}.0, Shape: (), ElemSize: 1 Byte(s), TotalSize:
1.0 Byte(s)
- TensorConstant{50}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0
Byte(s)
- Elemwise{eq,no_inplace}.0, Shape: (), ElemSize: 1 Byte(s), TotalSize:
1.0 Byte(s)
- Elemwise{eq,no_inplace}.0, Shape: (), ElemSize: 1 Byte(s), TotalSize:
1.0 Byte(s)
- Elemwise{eq,no_inplace}.0, Shape: (), ElemSize: 1 Byte(s), TotalSize:
1.0 Byte(s)
- TensorConstant{False}, Shape: (), ElemSize: 1 Byte(s), TotalSize: 1.0
Byte(s)
TotalSize: 172726976.0 Byte(s) 0.161 GB
TotalSize inputs: 172377152.0 Byte(s) 0.161 GB
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'.
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