Theano error message

ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{border_mode='half', subsample=(1, 1), filter_flip=True, imshp=(None, None, None, None), kshp=(32, 3, 3, 3)}(DimShuffle{0,3,1,2}.0, DimShuffle{3,2,0,1}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
  File "C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py", line 1772, in process_node
    replacements = lopt.transform(node)
  File "C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\tensor\nnet\opt.py", line 402, in local_abstractconv_check
    node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against?

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-5-19331022925d> in <module>()
      6               nb_epoch=nb_epoch,
      7               validation_data=(X_test, Y_test),
----> 8               shuffle=True)
      9 else:
     10     print('Using real-time data augmentation.')

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\models.py in fit(self, x, y, batch_size, nb_epoch, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, **kwargs)
    618                               shuffle=shuffle,
    619                               class_weight=class_weight,
--> 620                               sample_weight=sample_weight)
    621
    622     def evaluate(self, x, y, batch_size=32, verbose=1,

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\engine\training.py in fit(self, x, y, batch_size, nb_epoch, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight)
   1047                                                                            check_batch_dim=False,
   1048                                                                            batch_size=batch_size)
-> 1049             self._make_test_function()
   1050             val_f = self.test_function
   1051             if self.uses_learning_phase and type(K.learning_phase()) is not int:

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\engine\training.py in _make_test_function(self)
    716                                             [self.total_loss] + self.metrics_tensors,
    717                                             updates=self.state_updates,
--> 718                                             **self._function_kwargs)
    719
    720     def _make_predict_function(self):

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\backend\theano_backend.py in function(inputs, outputs, updates, **kwargs)
    725                 msg = "Invalid argument '%s' passed to K.function" % key
    726                 raise ValueError(msg)
--> 727     return Function(inputs, outputs, updates=updates, **kwargs)
    728
    729

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\backend\theano_backend.py in __init__(self, inputs, outputs, updates, **kwargs)
    711                                         allow_input_downcast=True,
    712                                         on_unused_input='ignore',
--> 713                                         **kwargs)
    714
    715     def __call__(self, inputs):

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\compile\function.py in function(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)
    318                    on_unused_input=on_unused_input,
    319                    profile=profile,
--> 320                    output_keys=output_keys)
    321     # We need to add the flag check_aliased inputs if we have any mutable or
    322     # borrowed used defined inputs

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\compile\pfunc.py in pfunc(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input, output_keys)
    477                          accept_inplace=accept_inplace, name=name,
    478                          profile=profile, on_unused_input=on_unused_input,
--> 479                          output_keys=output_keys)
    480
    481

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\compile\function_module.py in orig_function(inputs, outputs, mode, accept_inplace, name, profile, on_unused_input, output_keys)
   1774                    profile=profile,
   1775                    on_unused_input=on_unused_input,
-> 1776                    output_keys=output_keys).create(
   1777             defaults)
   1778

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\compile\function_module.py in __init__(self, inputs, outputs, mode, accept_inplace, function_builder, profile, on_unused_input, fgraph, output_keys)
   1454                         optimizer, inputs, outputs)
   1455                 else:
-> 1456                     optimizer_profile = optimizer(fgraph)
   1457
   1458                 end_optimizer = time.time()

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in __call__(self, fgraph)
     99
    100         """
--> 101         return self.optimize(fgraph)
    102
    103     def add_requirements(self, fgraph):

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in optimize(self, fgraph, *args, **kwargs)
     87             orig = theano.tensor.basic.constant.enable
     88             theano.tensor.basic.constant.enable = False
---> 89             ret = self.apply(fgraph, *args, **kwargs)
     90         finally:
     91             theano.tensor.basic.constant.enable = orig

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in apply(self, fgraph)
    228             try:
    229                 t0 = time.time()
--> 230                 sub_prof = optimizer.optimize(fgraph)
    231                 l.append(float(time.time() - t0))
    232                 sub_profs.append(sub_prof)

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in optimize(self, fgraph, *args, **kwargs)
     87             orig = theano.tensor.basic.constant.enable
     88             theano.tensor.basic.constant.enable = False
---> 89             ret = self.apply(fgraph, *args, **kwargs)
     90         finally:
     91             theano.tensor.basic.constant.enable = orig

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in apply(self, fgraph, start_from)
   1877                     node = q.popleft()
   1878                 current_node = node
-> 1879                 nb += self.process_node(fgraph, node)
   1880             loop_t = time.time() - t0
   1881         except Exception:

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in process_node(self, fgraph, node, lopt)
   1775                 self.failure_callback(e, self,
   1776                                       [(x, None) for x in node.outputs],
-> 1777                                       lopt, node)
   1778                 return False
   1779             else:

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in warn_inplace(exc, nav, repl_pairs, local_opt, node)
   1671         if isinstance(exc, InconsistencyError):
   1672             return
-> 1673         return NavigatorOptimizer.warn(exc, nav, repl_pairs, local_opt, node)
   1674
   1675     @staticmethod

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in warn(exc, nav, repl_pairs, local_opt, node)
   1657             # We always crash on AssertionError because something may be
   1658             # seriously wrong if such an exception is raised.
-> 1659             raise exc
   1660
   1661     @staticmethod

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\gof\opt.py in process_node(self, fgraph, node, lopt)
   1770         lopt = lopt or self.local_opt
   1771         try:
-> 1772             replacements = lopt.transform(node)
   1773         except Exception as e:
   1774             if self.failure_callback is not None:

C:\Users\212590884\AppData\Local\Continuum\Anaconda3\lib\site-packages\theano\tensor\nnet\opt.py in local_abstractconv_check(node)
    400             'is cuDNN available and does the GPU support it? If on CPU, '
    401             'do you have a BLAS library installed Theano can link against?' %
--> 402             node.op.__class__.__name__)
    403
    404 optdb.register('AbstractConvCheck',

AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against?