small code refactoring

theano/sandbox/cuda/dnn.py

@@ -1107,28 +1107,15 @@ if (%(mode)d == 1)
 
         # Validate the input and build the input variables.
         for input_idx, input_name in enumerate(self.softmax_inputs):
-            result += """
-if (!CudaNdarray_is_c_contiguous(%(ins)s)) {
-  PyErr_SetString(PyExc_ValueError, "Only contiguous inputs are supported.");
-  %(fail)s
-}
+            result += c_set_tensor4d(ins[input_idx], input_name + "_" + name,
+                                     "err" + name, sub['fail'])
 
-err%(name)s = cudnnSetTensor4dDescriptor(
-  %(input_name)s_%(name)s,
-  format%(name)s,
-  CUDNN_DATA_FLOAT,
-  CudaNdarray_HOST_DIMS(%(ins)s)[0],
-  CudaNdarray_HOST_DIMS(%(ins)s)[1],
-  CudaNdarray_HOST_DIMS(%(ins)s)[2],
-  CudaNdarray_HOST_DIMS(%(ins)s)[3]
-);
-if (err%(name)s != CUDNN_STATUS_SUCCESS) {
-  PyErr_Format(PyExc_RuntimeError, "could not set tensor4d descriptor: %%%%s",
-               cudnnGetErrorString(err%(name)s));
-  %(fail)s
-}
-""" % dict(name=name, input_name=input_name,
-           ins=ins[input_idx], fail=sub['fail'])
+        subs = dict(ins=ins[-1], outs=outs, fail=sub['fail'],
+                    name=name)
+
+        for idx, softmax_input in enumerate(self.softmax_inputs):
+            subs['name%d' % idx] = softmax_input
+            subs['ins%d' % idx] = inputs[idx]
 
         # Build and prepare the output variable.
         result += """
@@ -1136,34 +1123,15 @@ if (CudaNdarray_prep_output(&%(outs)s, 4, CudaNdarray_HOST_DIMS(%(ins)s)) != 0)
 {
   %(fail)s
 }
-
-err%(name)s = cudnnSetTensor4dDescriptor(
-  softmax_output_%(name)s,
-  format%(name)s,
-  CUDNN_DATA_FLOAT,
-  CudaNdarray_HOST_DIMS(%(outs)s)[0],
-  CudaNdarray_HOST_DIMS(%(outs)s)[1],
-  CudaNdarray_HOST_DIMS(%(outs)s)[2],
-  CudaNdarray_HOST_DIMS(%(outs)s)[3]
-);
-if (err%(name)s != CUDNN_STATUS_SUCCESS) {
-  PyErr_Format(PyExc_RuntimeError, "could not set out descriptor: %%%%s",
-               cudnnGetErrorString(err%(name)s));
-  %(fail)s
-}
-"""
+""" % subs
+        result += c_set_tensor4d(outs,
+                                 "softmax_output_" + name,
+                                 "err" + name, sub['fail'])
 
         # Add on a call to the method that does the actual work.
-        result += self.method()
+        result += self.method() % subs
 
-        subs = dict(ins=ins[-1], outs=outs, fail=sub['fail'],
-                    name=name)
-
-        for idx, softmax_input in enumerate(self.softmax_inputs):
-            subs['name%d' % idx] = softmax_input
-            subs['ins%d' % idx] = inputs[idx]
-
-        return result % subs
+        return result
 
     def c_code_cache_version(self):
         return (0, 6)