merge

theano/compile/mode.py

@@ -233,7 +233,8 @@ predefined_modes = {'FAST_COMPILE': FAST_COMPILE,
                     'SANITY_CHECK': SANITY_CHECK}
 
 def get_mode(string):
-    if string is None: string = config.mode
+    if string is None:
+        return get_default_mode()
     if not isinstance(string, str): return string #it is hopefully already a mode...
     if not predefined_modes.has_key(string):
         raise Exception("No predefixed mode exist for string: %s"%string)

theano/tensor/blas.py

@@ -830,25 +830,8 @@ class Dot22Scalar(GemmRelated):
     def __str__(self):
         return "_dot22scalar"
 
-    setup_z_Nz_Sz = """
-        if ((NULL == %(_z)s)
-            || (%(_z)s->dimensions[0] != %(_x)s->dimensions[0])
-            || (%(_z)s->dimensions[1] != %(_y)s->dimensions[1]))
-        {
-            if (NULL != %(_z)s) Py_XDECREF(%(_z)s);
-            npy_intp dims[2];
-            dims[0] = %(_x)s->dimensions[0];
-            dims[1] = %(_y)s->dimensions[1];
-            %(_z)s = (PyArrayObject*)PyArray_SimpleNew(2, dims, type_num_%(_x)s);
-            if(!%(_z)s) {
-                PyErr_SetString(PyExc_MemoryError, "failed to alloc dot22scalar output");
-                %(fail)s
-            }
-        }
-        Nz = %(_z)s->dimensions;
-        Sz = %(_z)s->strides;
+    setup_z_Nz_Sz = Dot22.setup_z_Nz_Sz
 
-        """
     check_ab_double_or_float = """
         if ((%(_a)s->descr->type_num != PyArray_DOUBLE)
             && (%(_a)s->descr->type_num != PyArray_FLOAT))
@@ -871,13 +854,13 @@ class Dot22Scalar(GemmRelated):
         #undef REAL
         double b = 0.0;
         """
-    def c_code(self, node, name, (_x, _y, _a), (_z, ), sub): #DEBUG
+    def c_code(self, node, name, (_x, _y, _a), (_zout, ), sub): #DEBUG
         if len(self.c_libraries())<=0:
-            return super(Dot22Scalar, self).c_code(node, name, (_x, _y), (_z, ), sub)
+            return super(Dot22Scalar, self).c_code(node, name, (_x, _y), (_zout, ), sub)
         full_code = self.build_gemm_call() % dict(locals(), **sub)
         return full_code
     def c_code_cache_version(self):
-        return (1,) + self.build_gemm_version()
+        return (2,) + self.build_gemm_version()
 
 _dot22scalar = Dot22Scalar()
 

theano/tensor/opt.py

@@ -465,6 +465,33 @@ class ShapeOptimizer(Optimizer):
 # -1 should make it run right before the first merge
 theano.compile.mode.optdb.register('ShapeOpt', ShapeOptimizer(), -1, 'fast_run', 'fast_compile')
 
+#This is a bug fix as ShapeFeature should do this, but it don't in the deep teaching tutorial.
+@gof.local_optimizer([None, None])
+def local_shape_i_lift(node):
+    """
+    "Lifts" DimShuffle through Elemwise operations and merges
+    consecutive DimShuffles. Basically, applies the following
+    transformations on the whole graph:
+
+    DimShuffle(Elemwise(x, y)) => Elemwise(DimShuffle(x), DimShuffle(y))
+    DimShuffle(DimShuffle(x)) => DimShuffle(x)
+
+    After this transform, clusters of Elemwise operations are
+    void of DimShuffle operations.
+    """
+    op = node.op
+    if not isinstance(op, Shape_i):
+        return False
+
+    input = node.inputs[0]
+    inode = input.owner
+    if inode and isinstance(inode.op, Elemwise) and inode.op.scalar_op.nin==1:
+        return node.env.shape_feature.shape_of[input]
+
+
+register_canonicalize(local_shape_i_lift)
+register_specialize(local_shape_i_lift)
+
 @register_specialize
 @register_canonicalize
 @gof.local_optimizer([T.fill])