GpuElemwise - removed ExternAlgo dead code

theano/sandbox/cuda/elemwise.py

@@ -906,90 +906,3 @@ nd_collapse_[i]=0;
         #define INTMOD_POW2(a, b) (a & ((1<<b)-1))
         """
 
-
-
-class ExternAlgo(object):
-    def externalgo_c_support_code_apply(self, node, nodename):
-        nd = node.outputs[0].type.ndim
-        n_inputs = len(node.inputs)
-        n_outputs = len(node.outputs)
-        id_self = id(self)
-        d = dict()
-        #input_params and output_params go into the function declaration/definition
-        input_params = ", ".join("const float * i%i_data, const int * i%i_str"%(ipos, ipos) 
-                for ipos in xrange(len(node.inputs)))
-        output_params = ", ".join("float * o%i_data, const int * o%i_str"%(ipos, ipos) 
-                for ipos in xrange(len(node.outputs)))
-
-        #input_args and output_args go into the recursive call.
-        input_args = ", ".join("i%i_data, i%i_str"%(ipos, ipos) 
-                for ipos in xrange(len(node.inputs)))
-        output_args = ", ".join("o%i_data, o%i_str"%(ipos, ipos) 
-                for ipos in xrange(len(node.outputs)))
-
-        prod_dims = '*'.join("dims[%i]"%di for di in xrange(nd))
-
-        scalar_op=self.scalar_op.__class__.__name__
-
-        apply_task_code = self.scalar_op.c_code(
-                Apply(self.scalar_op,
-                    [scalar.Scalar(dtype = input.type.dtype)() for input in node.inputs],
-                    [scalar.Scalar(dtype = output.type.dtype)() for output in node.outputs])
-                , nodename + '_scalar_'
-                , ['x[%i][0]'%ipos for ipos, i in enumerate(node.inputs)] 
-                , ['z[%i][0]'%ipos for ipos, i in enumerate(node.outputs)] 
-                , sub=dict(fail='return;')) #TODO: set a failure code somehow!!!
-
-        ### NOTE WELL: log2_dims is not initialized on input to this function... it is meant as
-        ### storage space where the log2_dims *could* be computed and stored.
-        sio = StringIO.StringIO()
-        print >> sio, """
-        #include "elemwise.cuh"
-
-        template <int nx, typename Tx, int nz, typename Tz>
-        class ElemwiseFn_%(scalar_op)s
-        {
-        public:
-            static __device__ void apply(const Tx**x, Tz**z)
-            {
-                %(apply_task_code)s
-            }  
-        };
-
-        static void callkernel_%(nodename)s(unsigned int numEls, const int d,
-            const int * dims, const int * log2_dims,
-            %(input_params)s,
-            %(output_params)s)
-        {
-            const float * inputs[%(n_inputs)s];
-            float * outputs[%(n_outputs)s];
-            const int * input_strides[%(n_inputs)s];
-            const int * output_strides[%(n_inputs)s];
-            
-        """ %locals()
-        for ipos, i in enumerate(node.inputs):
-            print >> sio, """
-            inputs[%(ipos)s] = i%(ipos)s_data;
-            input_strides[%(ipos)s] = i%(ipos)s_str;
-            """ %locals()
-        for ipos, i in enumerate(node.outputs):
-            print >> sio, """
-            outputs[%(ipos)s] = o%(ipos)s_data;
-            output_strides[%(ipos)s] = o%(ipos)s_str;
-            """ %locals()
-        print >> sio, """
-            cnda_elemwise<float, float, 
-                    ElemwiseFn_%(scalar_op)s<%(n_inputs)s, typeof(i0_data[0]), %(n_outputs)s, typeof(o0_data[0])>
-                    , %(n_inputs)s, %(n_outputs)s, %(nd)s> (
-                 dims,
-                 inputs,
-                 input_strides,
-                 outputs,
-                 output_strides
-            );
-        }
-        """ %locals()
-        print sio.getvalue()
-        return sio.getvalue()
-
-