HP-Z840-Workstation:~/Data$ THEANO_FLAGS=''; python -c "import theano; theano.test()"

Theano version 1.0.0

theano is installed in /home/bluegum1/Theano/theano
NumPy version 1.13.3

NumPy relaxed strides checking option: True
NumPy is installed in /home/bluegum1/.local/lib/python2.7/site-packages/numpy

Python version 2.7.12 (default, Nov 19 2016, 06:48:10) [GCC 5.4.0 20160609]

nose version 1.3.7

Using cuDNN version 6021 on context None

Mapped name None to device cuda: Quadro M4000 (0000:04:00.0)

..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)

ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "/home/bluegum1/Theano/theano/gof/opt.py", line 2059, in process_node
    remove=remove)
  File "/home/bluegum1/Theano/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
    chk = fgraph.replace_all_validate(replacements, reason)
  File "/home/bluegum1/Theano/theano/gof/toolbox.py", line 518, in replace_all_validate
    fgraph.replace(r, new_r, reason=reason, verbose=False)
  File "/home/bluegum1/Theano/theano/gof/fg.py", line 486, in replace
    ". The type of the replacement must be the same.", old, new)

BadOptimization: BadOptimization Error 
  Variable: id 140331434464144 Elemwise{Cast{float32}}.0
  Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
  Value Type: <type 'NoneType'>
  Old Value:  None
  New Value:  None
  Reason:  insert_bad_dtype. The type of the replacement must be the same.
  Old Graph:
  Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''   
   |<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
   |<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>

 
New Graph:
  Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''   
   |Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''   



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


......................................S............................./home/bluegum1/Theano/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
  return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/home/bluegum1/Theano/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
  return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))

............................................../home/bluegum1/Theano/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
  'CVM does not support memory profile, using Stack VM.')
............/home/bluegum1/Theano/theano/compile/profiling.py:283: UserWarning: You are running the Theano profiler with CUDA enabled. Theano GPU ops execution is asynchronous by default. So by default, the profile is useless. You must set the environment variable CUDA_LAUNCH_BLOCKING to 1 to tell the CUDA driver to synchronize the execution to get a meaningful profile.
  warnings.warn(msg)

....................0.0581646137166

0.0581646137166

0.0581646137166

0.0581646137166

.................................................................................................................................................................../home/bluegum1/Theano/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
  'LoopGC does not support partial evaluation, '
..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................Violación de segmento (`core' generado)