Small changes following code review

theano/gpuarray/dnn.py

@@ -3030,9 +3030,6 @@ def local_log_softmax_dnn(node):
             node.inputs[0].owner and
             isinstance(node.inputs[0].owner.op, GpuDnnSoftmax) and
             len(node.inputs[0].clients) == 1):
-        if version(raises=False) < 3000:
-            # No log-softmax before cudnn v3
-            return
         softmax_node = node.inputs[0].owner
         new_softmax = GpuDnnSoftmax('log', softmax_node.op.mode)
         return [new_softmax(softmax_node.inputs[0])]

theano/gpuarray/tests/config.py

@@ -22,6 +22,7 @@ if theano.config.mode == 'FAST_COMPILE':
 else:
     mode_with_gpu = theano.compile.mode.get_default_mode().including('gpuarray').excluding('gpu')
     mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpuarray')
+    mode_without_gpu.check_py_code = False
 
 
 # If using float16, cast reference input to float32

theano/gpuarray/tests/test_dnn.py

@@ -27,9 +27,8 @@ from .rnn_support import Model, GRU, LSTM, WrapperLayer
 from theano.configdefaults import SUPPORTED_DNN_CONV_ALGO_FWD
 
 mode_with_gpu = mode_with_gpu.including()
-mode_without_gpu = mode_without_gpu.including()
+# Globally disabled for mode_without_gpu
 mode_with_gpu.check_py_code = False
-mode_without_gpu.check_py_code = False
 
 
 # If using float16, set CUDNN precision to float32

theano/sandbox/cuda/dnn.py

@@ -3708,10 +3708,10 @@ def local_gpu_batch_norm_inference_inplace(node):
 def values_eq_approx_high_tol(a, b):
     """
     This fct is needed to don't have DebugMode raise useless
-    error due to ronding error.
+    errors due to rounding error.
 
-    This happen as We reduce on the two last dimensions, so this
-    can raise the absolute error if the number of element we
+    This happen as we reduce on the two last dimensions, so this
+    can raise the absolute error if the number of elements we
     reduce on is significant.
 
     """

theano/tensor/type.py

@@ -203,7 +203,8 @@ class TensorType(Type):
         """
         Convert a symbolic Variable into a TensorType, if compatible.
 
-        For the moment, only a TensorType or CudaNdarrayType will be
+        For the moment, only a TensorType, GpuArrayType and
+        CudaNdarrayType will be
         converted, provided they have the same number of dimensions and
         dtype and have "compatible" broadcastable pattern.