debug: cuda.opt local_cut_gpu_host_gpu

theano/sandbox/cuda/opt.py

@@ -2,7 +2,7 @@ import sys
 import theano
 import numpy
 from theano import scalar as scal
-from theano import tensor, compile
+from theano import tensor, compile, gof
 from theano.gof import local_optimizer, EquilibriumDB, SequenceDB, Optimizer, toolbox, DestroyHandler
 
 from theano.sandbox.cuda.basic_ops import *
@@ -62,10 +62,16 @@ gpu_seqopt.register('InputToGpuOptimizer', InputToGpuOptimizer(),
 
 @local_optimizer([])
 def local_cut_gpu_host_gpu(node):
+    copy_op=None
     if tensor.opt.opt.check_chain(node, gpu_from_host, host_from_gpu):
-        return [node.inputs[0].owner.inputs[0]]
+        copy_op = GpuElemwise(scal.identity, {})
     if tensor.opt.opt.check_chain(node, host_from_gpu, gpu_from_host):
-        return [node.inputs[0].owner.inputs[0]]
+        copy_op =tensor.copy
+    if copy_op:
+        #copy_op = lambda x:x
+        rval = copy_op(node.inputs[0].owner.inputs[0])
+        assert isinstance(rval, gof.Variable), "rval is not a variable"
+        return [rval]
     return False
 gpu_cut_copies.register('cut_gpu_host_transfers', local_cut_gpu_host_gpu, 
         'fast_run', 'inplace', 'gpu')

theano/tensor/opt.py

@@ -1063,11 +1063,18 @@ def local_fill_cut(node):
     If c.type == a.type.
     """
 
+    # this optimization is essentially for getting broadcasting to replace fill. 
+    # This is always possible when using a Compound Elemwise operation, 
+    # but it is not always possible without one (consider filling a large matrix with a scalar,
+    # and then adding another scalar.  The only numbers that count are the two scalars, but we
+    # can't ignore the large matrix because it gives the shape of the result.
+
     if not opt.check_chain(node, T.Elemwise):
         return False
     
     output = node.outputs[0]
     try:
+        #reference is some input with the same type as the input but that is not produced by a fill
         reference = [input
                      for input in node.inputs
                      if input.type == output.type and (not input.owner or input.owner.op != T.fill)][0]
@@ -1086,7 +1093,13 @@ def local_fill_cut(node):
 
     if new_inputs == node.inputs:
         return False
-    return node.op.make_node(*new_inputs).outputs
+
+    print 'NEW INPUTS', new_inputs
+    rval = node.op(*new_inputs)
+    if isinstance(rval, gof.Variable):
+        return rval.owner.outputs
+    else:
+        return rval[0].owner.outputs
 
 register_canonicalize(local_fill_cut)