Using cuDNN version 5110 on context None
Mapped name None to device cuda1: TITAN X (Pascal) (0000:04:00.0)
Disabling C code for Elemwise{mul,no_inplace} due to unsupported float16
Disabling C code for Elemwise{mul,no_inplace} due to unsupported float16
Disabling C code for Elemwise{Cast{float32}} due to unsupported float16
ERROR (theano.gof.opt): Optimization failure due to: local_gpu_elemwise_careduce
ERROR (theano.gof.opt): node: GpuCAReduceCuda{add}{0}(GpuElemwise{sqr,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/opt.py", line 2036, in process_node
    remove=remove)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error 
  Variable: id 140574082265808 GpuCAReduceCuda{pre=sqr,red=add}{0}.0
  Op GpuCAReduceCuda{pre=sqr,red=add}{0}(GpuElemwise{sub,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  local_gpu_elemwise_careduce. The type of the replacement must be the same.
  Old Graph:
  GpuCAReduceCuda{add}{0} [id A] <GpuArrayType<None>(float32, vector)> ''   
   |GpuElemwise{sqr,no_inplace} [id B] <GpuArrayType<None>(float16, matrix)> ''   
     |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   
       |GpuElemwise{add,no_inplace} [id D] <GpuArrayType<None>(float16, matrix)> ''   
       | |GpuDot22 [id E] <GpuArrayType<None>(float16, matrix)> ''   
       | | |GpuElemwise{add,no_inplace} [id F] <GpuArrayType<None>(float16, matrix)> ''   
       | | |W [id G] <GpuArrayType<None>(float16, matrix)>
       | |InplaceGpuDimShuffle{x,0} [id H] <GpuArrayType<None>(float16, row)> ''   
       |   |b [id I] <GpuArrayType<None>(float16, vector)>
       |GpuElemwise{Cast{float16}}[]<gpuarray> [id J] <GpuArrayType<None>(float16, row)> ''   
         |GpuElemwise{true_div,no_inplace} [id K] <GpuArrayType<None>(float32, row)> ''   
           |InplaceGpuDimShuffle{x,0} [id L] <GpuArrayType<None>(float32, row)> ''   
           |GpuFromHost<None> [id M] <GpuArrayType<None>(float32, (True, True))> ''   

  New Graph:
  GpuCAReduceCuda{pre=sqr,red=add}{0} [id N] <GpuArrayType<None>(float16, vector)> ''   
   |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   


Hint: relax the tolerance by setting tensor.cmp_sloppy=1
  or even tensor.cmp_sloppy=2 for less-strict comparison


ERROR (theano.gof.opt): Optimization failure due to: local_gpu_elemwise_careduce
ERROR (theano.gof.opt): node: GpuCAReduceCuda{add}{0}(GpuElemwise{sqr,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/opt.py", line 2036, in process_node
    remove=remove)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error 
  Variable: id 140574081521808 GpuCAReduceCuda{pre=sqr,red=add}{0}.0
  Op GpuCAReduceCuda{pre=sqr,red=add}{0}(GpuElemwise{sub,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  local_gpu_elemwise_careduce. The type of the replacement must be the same.
  Old Graph:
  GpuCAReduceCuda{add}{0} [id A] <GpuArrayType<None>(float32, vector)> ''   
   |GpuElemwise{sqr,no_inplace} [id B] <GpuArrayType<None>(float16, matrix)> ''   
     |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   
       |GpuElemwise{add,no_inplace} [id D] <GpuArrayType<None>(float16, matrix)> ''   
       | |GpuDot22 [id E] <GpuArrayType<None>(float16, matrix)> ''   
       | | |GpuFromHost<None> [id F] <GpuArrayType<None>(float16, matrix)> ''   
       | | |W [id G] <GpuArrayType<None>(float16, matrix)>
       | |InplaceGpuDimShuffle{x,0} [id H] <GpuArrayType<None>(float16, row)> ''   
       |   |b [id I] <GpuArrayType<None>(float16, vector)>
       |GpuElemwise{Cast{float16}}[]<gpuarray> [id J] <GpuArrayType<None>(float16, row)> ''   
         |GpuElemwise{true_div,no_inplace} [id K] <GpuArrayType<None>(float32, row)> ''   
           |InplaceGpuDimShuffle{x,0} [id L] <GpuArrayType<None>(float32, row)> ''   
           |GpuFromHost<None> [id M] <GpuArrayType<None>(float32, (True, True))> ''   

  New Graph:
  GpuCAReduceCuda{pre=sqr,red=add}{0} [id N] <GpuArrayType<None>(float16, vector)> ''   
   |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   


Hint: relax the tolerance by setting tensor.cmp_sloppy=1
  or even tensor.cmp_sloppy=2 for less-strict comparison


ERROR (theano.gof.opt): Optimization failure due to: local_gpu_elemwise_careduce
ERROR (theano.gof.opt): node: GpuCAReduceCuda{add}{0}(GpuElemwise{sqr,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/opt.py", line 2036, in process_node
    remove=remove)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error 
  Variable: id 140574081416464 GpuCAReduceCuda{pre=sqr,red=add}{0}.0
  Op GpuCAReduceCuda{pre=sqr,red=add}{0}(GpuElemwise{sub,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  local_gpu_elemwise_careduce. The type of the replacement must be the same.
  Old Graph:
  GpuCAReduceCuda{add}{0} [id A] <GpuArrayType<None>(float32, vector)> ''   
   |GpuElemwise{sqr,no_inplace} [id B] <GpuArrayType<None>(float16, matrix)> ''   
     |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   
       |GpuElemwise{add,no_inplace} [id D] <GpuArrayType<None>(float16, matrix)> ''   
       | |GpuDot22 [id E] <GpuArrayType<None>(float16, matrix)> ''   
       | | |GpuElemwise{add,no_inplace} [id F] <GpuArrayType<None>(float16, matrix)> ''   
       | | |W [id G] <GpuArrayType<None>(float16, matrix)>
       | |InplaceGpuDimShuffle{x,0} [id H] <GpuArrayType<None>(float16, row)> ''   
       |   |b [id I] <GpuArrayType<None>(float16, vector)>
       |GpuElemwise{Cast{float16}}[]<gpuarray> [id J] <GpuArrayType<None>(float16, row)> ''   
         |GpuElemwise{true_div,no_inplace} [id K] <GpuArrayType<None>(float32, row)> ''   
           |InplaceGpuDimShuffle{x,0} [id L] <GpuArrayType<None>(float32, row)> ''   
           |GpuFromHost<None> [id M] <GpuArrayType<None>(float32, (True, True))> ''   

  New Graph:
  GpuCAReduceCuda{pre=sqr,red=add}{0} [id N] <GpuArrayType<None>(float16, vector)> ''   
   |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   


Hint: relax the tolerance by setting tensor.cmp_sloppy=1
  or even tensor.cmp_sloppy=2 for less-strict comparison


ERROR (theano.gof.opt): Optimization failure due to: local_gpu_elemwise_careduce
ERROR (theano.gof.opt): node: GpuCAReduceCuda{add}{0}(GpuElemwise{sqr,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/opt.py", line 2036, in process_node
    remove=remove)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error 
  Variable: id 140574081490448 GpuCAReduceCuda{pre=sqr,red=add}{0}.0
  Op GpuCAReduceCuda{pre=sqr,red=add}{0}(GpuElemwise{sub,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  local_gpu_elemwise_careduce. The type of the replacement must be the same.
  Old Graph:
  GpuCAReduceCuda{add}{0} [id A] <GpuArrayType<None>(float32, vector)> ''   
   |GpuElemwise{sqr,no_inplace} [id B] <GpuArrayType<None>(float16, matrix)> ''   
     |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   
       |GpuElemwise{add,no_inplace} [id D] <GpuArrayType<None>(float16, matrix)> ''   
       | |GpuDot22 [id E] <GpuArrayType<None>(float16, matrix)> ''   
       | | |GpuFromHost<None> [id F] <GpuArrayType<None>(float16, matrix)> ''   
       | | |W [id G] <GpuArrayType<None>(float16, matrix)>
       | |InplaceGpuDimShuffle{x,0} [id H] <GpuArrayType<None>(float16, row)> ''   
       |   |b [id I] <GpuArrayType<None>(float16, vector)>
       |GpuElemwise{Cast{float16}}[]<gpuarray> [id J] <GpuArrayType<None>(float16, row)> ''   
         |GpuElemwise{true_div,no_inplace} [id K] <GpuArrayType<None>(float32, row)> ''   
           |InplaceGpuDimShuffle{x,0} [id L] <GpuArrayType<None>(float32, row)> ''   
           |GpuFromHost<None> [id M] <GpuArrayType<None>(float32, (True, True))> ''   

  New Graph:
  GpuCAReduceCuda{pre=sqr,red=add}{0} [id N] <GpuArrayType<None>(float16, vector)> ''   
   |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   


Hint: relax the tolerance by setting tensor.cmp_sloppy=1
  or even tensor.cmp_sloppy=2 for less-strict comparison


ERROR (theano.gof.opt): Optimization failure due to: local_gpu_elemwise_careduce
ERROR (theano.gof.opt): node: GpuCAReduceCuda{add}{0}(GpuElemwise{sqr,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/opt.py", line 2036, in process_node
    remove=remove)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error 
  Variable: id 140574081489936 GpuCAReduceCuda{pre=sqr,red=add}{0}.0
  Op GpuCAReduceCuda{pre=sqr,red=add}{0}(GpuElemwise{sub,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  local_gpu_elemwise_careduce. The type of the replacement must be the same.
  Old Graph:
  GpuCAReduceCuda{add}{0} [id A] <GpuArrayType<None>(float32, vector)> ''   
   |GpuElemwise{sqr,no_inplace} [id B] <GpuArrayType<None>(float16, matrix)> ''   
     |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   
       |GpuElemwise{add,no_inplace} [id D] <GpuArrayType<None>(float16, matrix)> ''   
       | |GpuDot22 [id E] <GpuArrayType<None>(float16, matrix)> ''   
       | | |GpuElemwise{add,no_inplace} [id F] <GpuArrayType<None>(float16, matrix)> ''   
       | | |W [id G] <GpuArrayType<None>(float16, matrix)>
       | |InplaceGpuDimShuffle{x,0} [id H] <GpuArrayType<None>(float16, row)> ''   
       |   |b [id I] <GpuArrayType<None>(float16, vector)>
       |GpuElemwise{Cast{float16}}[]<gpuarray> [id J] <GpuArrayType<None>(float16, row)> ''   
         |GpuElemwise{true_div,no_inplace} [id K] <GpuArrayType<None>(float32, row)> ''   
           |InplaceGpuDimShuffle{x,0} [id L] <GpuArrayType<None>(float32, row)> ''   
           |GpuFromHost<None> [id M] <GpuArrayType<None>(float32, (True, True))> ''   

  New Graph:
  GpuCAReduceCuda{pre=sqr,red=add}{0} [id N] <GpuArrayType<None>(float16, vector)> ''   
   |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   


Hint: relax the tolerance by setting tensor.cmp_sloppy=1
  or even tensor.cmp_sloppy=2 for less-strict comparison


ERROR (theano.gof.opt): Optimization failure due to: local_gpu_elemwise_careduce
ERROR (theano.gof.opt): node: GpuCAReduceCuda{add}{0}(GpuElemwise{sqr,no_inplace}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/opt.py", line 2036, in process_node
    remove=remove)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/fabian/deeplearning_venv/local/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error 
  Variable: id 140574081123920 GpuCAReduceCuda{pre=sqr,red=add}{0}.0
  Op GpuCAReduceCuda{pre=sqr,red=add}{0}(GpuElemwise{sub,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  local_gpu_elemwise_careduce. The type of the replacement must be the same.
  Old Graph:
  GpuCAReduceCuda{add}{0} [id A] <GpuArrayType<None>(float32, vector)> ''   
   |GpuElemwise{sqr,no_inplace} [id B] <GpuArrayType<None>(float16, matrix)> ''   
     |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   
       |GpuElemwise{add,no_inplace} [id D] <GpuArrayType<None>(float16, matrix)> ''   
       | |GpuDot22 [id E] <GpuArrayType<None>(float16, matrix)> ''   
       | | |GpuFromHost<None> [id F] <GpuArrayType<None>(float16, matrix)> ''   
       | | |W [id G] <GpuArrayType<None>(float16, matrix)>
       | |InplaceGpuDimShuffle{x,0} [id H] <GpuArrayType<None>(float16, row)> ''   
       |   |b [id I] <GpuArrayType<None>(float16, vector)>
       |GpuElemwise{Cast{float16}}[]<gpuarray> [id J] <GpuArrayType<None>(float16, row)> ''   
         |GpuElemwise{true_div,no_inplace} [id K] <GpuArrayType<None>(float32, row)> ''   
           |InplaceGpuDimShuffle{x,0} [id L] <GpuArrayType<None>(float32, row)> ''   
           |GpuFromHost<None> [id M] <GpuArrayType<None>(float32, (True, True))> ''   

  New Graph:
  GpuCAReduceCuda{pre=sqr,red=add}{0} [id N] <GpuArrayType<None>(float16, vector)> ''   
   |GpuElemwise{sub,no_inplace} [id C] <GpuArrayType<None>(float16, matrix)> ''   


Hint: relax the tolerance by setting tensor.cmp_sloppy=1
  or even tensor.cmp_sloppy=2 for less-strict comparison


Disabling C code for Elemwise{Add}[(0, 1)] due to unsupported float16
Disabling C code for Argmax due to unsupported float16
Disabling C code for Elemwise{mul,no_inplace} due to unsupported float16
Disabling C code for Elemwise{mul,no_inplace} due to unsupported float16
Disabling C code for Argmax due to unsupported float16
epoch 0: train loss: nan train acc 0.390000 test loss nan test acc 0.175000
epoch 1: train loss: nan train acc 0.375000 test loss nan test acc 0.215000
epoch 2: train loss: nan train acc 0.360000 test loss nan test acc 0.140000
epoch 3: train loss: nan train acc 0.390000 test loss nan test acc 0.240000
epoch 4: train loss: nan train acc 0.370000 test loss nan test acc 0.215000
epoch 5: train loss: nan train acc 0.390000 test loss nan test acc 0.190000
epoch 6: train loss: nan train acc 0.345000 test loss nan test acc 0.200000
epoch 7: train loss: nan train acc 0.345000 test loss nan test acc 0.230000
epoch 8: train loss: nan train acc 0.430000 test loss nan test acc 0.210000
epoch 9: train loss: nan train acc 0.375000 test loss nan test acc 0.190000
epoch 10: train loss: nan train acc 0.390000 test loss nan test acc 0.190000
epoch 11: train loss: nan train acc 0.340000 test loss nan test acc 0.160000
epoch 12: train loss: nan train acc 0.410000 test loss nan test acc 0.265000
epoch 13: train loss: nan train acc 0.360000 test loss nan test acc 0.225000
epoch 14: train loss: nan train acc 0.445000 test loss nan test acc 0.165000
epoch 15: train loss: nan train acc 0.350000 test loss nan test acc 0.245000
epoch 16: train loss: nan train acc 0.345000 test loss nan test acc 0.225000
epoch 17: train loss: nan train acc 0.410000 test loss nan test acc 0.185000
epoch 18: train loss: nan train acc 0.420000 test loss nan test acc 0.195000
epoch 19: train loss: nan train acc 0.335000 test loss nan test acc 0.185000
epoch 20: train loss: nan train acc 0.360000 test loss nan test acc 0.185000
epoch 21: train loss: nan train acc 0.335000 test loss nan test acc 0.265000
epoch 22: train loss: nan train acc 0.360000 test loss nan test acc 0.220000
epoch 23: train loss: nan train acc 0.345000 test loss nan test acc 0.175000
epoch 24: train loss: nan train acc 0.350000 test loss nan test acc 0.255000
epoch 25: train loss: nan train acc 0.355000 test loss nan test acc 0.235000
epoch 26: train loss: nan train acc 0.350000 test loss nan test acc 0.185000
epoch 27: train loss: nan train acc 0.370000 test loss nan test acc 0.165000
epoch 28: train loss: nan train acc 0.365000 test loss nan test acc 0.255000
epoch 29: train loss: nan train acc 0.420000 test loss nan test acc 0.160000