fixed up some error messages

theano/sandbox/cuda/elemwise.py

@@ -864,7 +864,7 @@ nd_collapse_[i]=0;
             if ((!(broadcasts_%(iname)s[i] && CudaNdarray_HOST_DIMS(%(iname)s)[i] == 1))&& (dims[i] != CudaNdarray_HOST_DIMS(%(iname)s)[i]))
             {
                 //std::cerr << "C_CODE %(opname)s checking input %(iname)s failed\\n";
-                PyErr_Format(PyExc_ValueError, "GpuElemwise. Input dimension mis-match.[%%i] == %%i, where output has size %%i",
+                PyErr_Format(PyExc_ValueError, "GpuElemwise. Input dimension mis-match. One of your inputs has shape[%%i] == %%i, but the output's size on that axis is %%i.",
                     i,
                     CudaNdarray_HOST_DIMS(%(iname)s)[i],
                     dims[i]

theano/sandbox/cuda/opt.py

@@ -846,10 +846,10 @@ def local_gpu_join(node):
 # Try to make gpu gemm inplace
 # Also, need to make the gemm optimisation(step 70) happen before the fusion of
 # elemwise(step 71)
-optdb.register('InplaceGpuBlasOpt',
-        EquilibriumOptimizer([local_inplace_gemm], failure_callback=EquilibriumOptimizer.warn_inplace,
-            max_use_ratio=5),
-               70.0, 'fast_run', 'inplace')
+#optdb.register('InplaceGpuBlasOpt',
+#        EquilibriumOptimizer([local_inplace_gemm], failure_callback=EquilibriumOptimizer.warn_inplace,
+#            max_use_ratio=5),
+#               70.0, 'fast_run', 'inplace')
 
 def get_device_type_sizes():
     if hasattr(get_device_type_sizes, 'rval'):

theano/tensor/basic.py

@@ -4450,6 +4450,9 @@ class Dot(Op):
                 else:            #y is a scalar
                     bz = bx
         else:
+            if len(inputs) != 2:
+                raise TypeError('theanor.tensor.Dot: 2 arguments required, %d given ' % len(inputs))
+
             x, y = inputs
             nx = x.type.ndim
             ny = y.type.ndim