merge no conflicts

theano/compile/pfunc.py

@@ -105,9 +105,9 @@ def rebuild_collect_shared( outputs
                                 , (v, v.type, v_update, v_update.type))
                         update_d[v] = v_update
                         update_expr.append((v, v_update))
-        if not copy_inputs_over and not isinstance(v, Constant):
+        if not copy_inputs_over or isinstance(v, Constant):
             ### Cloning shared variables implies copying their underlying
-            ### memory buffer ??
+            ### memory buffer ?? No.
             return clone_d.setdefault(v,v.clone())
         else:
             return clone_d.setdefault(v,v)

theano/scan_module/scan_opt.py

@@ -112,6 +112,152 @@ optdb.register( 'scanOp_remove_constants_and_unused_inputs'
                , 'fast_run'
                , 'scan')
 
+
+@gof.local_optimizer([None])
+def scan_pushout_non_seq_operation(node):
+    if not isinstance(node.op, scan_op.Scan):
+        return False
+    # this flag tells if there was any change during the last iterations
+    changed   = True
+    try:
+        clean_inputs, clean_outputs = scan_utils.reconstruct_graph(
+                        node.op.inputs, node.op.outputs)
+        local_env = gof.Env(clean_inputs, clean_outputs)
+    except:
+        import ipdb; ipdb.set_trace()
+
+    max_iterations = 2*len(local_env.toposort()) + 3
+    counts = 0
+    to_remove        = []
+    to_replace       = []
+    replace_with_in  = []
+    replace_with_out = []
+    op = node.op
+    # Construct the list of non_sequences to simplify a few things
+    st  = op.n_seqs
+    st += int(numpy.sum([len(x) for x in
+                         op.tap_array[:(op.n_mit_mot+op.n_mit_sot)] ]))
+    st += op.n_sit_sot
+    st += op.n_shared_outs
+    non_seqs = clean_inputs[st:]
+    st  = ( op.n_seqs +
+           op.n_mit_mot +
+           op.n_mit_sot +
+           op.n_sit_sot +
+           op.n_nit_sot +
+           op.n_shared_outs +1 )
+    outer_non_seqs = node.inputs[st:]
+
+    while changed and counts < max_iterations:
+        counts += 1
+        changed = False
+        for nd in local_env.toposort():
+            if (    numpy.all([ (x in non_seqs) or
+                                (x.owner in to_remove) or
+                                isinstance(x, tensor.Constant)
+                               for x in nd.inputs]) and
+                    # we can do this because the assumption is that a
+                    # viewOp or deepCopyOp will be just at the end of the
+                    # function and not somewhere in the middle ..
+                    not isinstance(nd.op,theano.compile.ViewOp) and
+                    not isinstance(nd.op,theano.compile.DeepCopyOp) and
+                    # and we didn't already looked at this node
+                    not nd in to_remove
+               ):
+
+                # We have a candidate node to removable
+                # Step 1. Reconstruct it on outside
+                to_remove += [nd]
+                outside_ins = []
+                for x in nd.inputs:
+                    if x in non_seqs:
+                        outside_ins +=[ outer_non_seqs[non_seqs.index(x)]]
+                    elif x in to_replace:
+                        outside_ins +=[replace_with_out[to_replace.index(x)]]
+                    elif isinstance(x, theano.Constant):
+                        outside_ins +=[x.clone()]
+                    else:
+                        raise Exception(
+                            ('Error in the `scan_pushout_non_seq_operations`'
+                             '. The optimization tries to move some '
+                             'computation fron scan which is not allowed '
+                             'to move. Report this on theano-users list'),x )
+                nw_outer_node = nd.op.make_node(*outside_ins)
+                # Step 2. Create variables for replacements
+                for idx,y in enumerate(nd.outputs):
+                    y_place_holder = scan_utils.safe_new(y,'_replace')
+                    to_replace       += [y]
+                    replace_with_in  += [y_place_holder]
+                    if (cuda.cuda_available and
+                        isinstance(nw_outer_node.outputs[idx],
+                                   CudaNdarrayType)):
+                        nw_out = nw_outer_node.outputs[idx]
+                        replace_with_out += [host_from_gpu(nw_out)]
+                    else:
+                        replace_with_out += [nw_outer_node.outputs[idx]]
+                changed = True
+
+    if counts >= max_iterations:
+        raise Exception( ('Error in the `scan_pushout_non_seq_operations`.'
+                          ' The optimization exhausted the maximal number '
+                          'of iterations allowed!'))
+    # We need to check all candidate replacements and choose those that
+    # make sense for us
+
+    # Step 1. which elements of `to_replace` are used by remaining
+    # components of the inner function
+    clean_to_replace       = []
+    clean_replace_with_in  = []
+    clean_replace_with_out = []
+    existent_nodes = [ nd for nd in local_env.toposort()
+                        if nd not in to_remove]
+    to_keep = []
+    for nd in existent_nodes:
+        to_keep += nd.inputs
+    for idx,out in enumerate(to_replace):
+        if out in to_keep and out.owner not in existent_nodes:
+            clean_to_replace += [out]
+            clean_replace_with_in  += [replace_with_in[idx]]
+            clean_replace_with_out += [replace_with_out[idx]]
+
+    if len(clean_to_replace) > 0:
+        # We can finally put an end to all this madness
+        givens = {}
+        nw_outer = []
+        nw_inner = []
+        for to_repl, repl_in, repl_out in zip( clean_to_replace,
+                                              clean_replace_with_in,
+                                              clean_replace_with_out):
+            if isinstance(repl_out, theano.Constant):
+                # Is this even possible !?
+                repl_in = repl_out.clone()
+            else:
+                nw_inner += [repl_in]
+                nw_outer += [repl_out]
+            givens[to_repl] = repl_in
+
+
+        _op_outs = scan_utils.clone(clean_outputs,
+                                    replace=givens)
+
+        _op_ins = clean_inputs + nw_inner
+        op_ins, op_outs = scan_utils.reconstruct_graph(_op_ins, _op_outs, '')
+        # Reconstruct node
+        nwScan = scan_op.Scan(op_ins, op_outs, op.info)
+        node = nwScan.make_node(* (node.inputs + nw_outer))
+        return node.outputs
+    else:
+        return False
+
+
+optdb.register('scanOp_pushout_nonseqs_ops',
+               opt.in2out( scan_pushout_non_seq_operation,
+                          ignore_newtrees=True),
+               1.90,
+               'fast_run',
+               'scan')
+
+
 @gof.local_optimizer([None])
 def scan_make_inplace(node):
     op = node.op

theano/scan_module/scan_utils.py

@@ -726,13 +726,15 @@ def flatten(l):
     return sum(l , [])
 
 
-def reconstruct_graph(inputs, outputs, tag):
+def reconstruct_graph(inputs, outputs, tag = None):
     """
     Different interface to clone, that allows you to pass inputs.
     Compared to clone, this method always replaces the inputs with
     new variables of the same type, and returns those ( in the same
     order as the original inputs).
     """
+    if tag is None:
+        tag = ''
     nw_inputs = [safe_new(x,tag) for x in inputs]
     givens = {}
     for nw_x, x in zip(nw_inputs, inputs):

theano/tensor/tests/test_rop.py

@@ -184,7 +184,7 @@ class test_RopLop(unittest.TestCase):
 
 
     def test_max_argmax(self):
-        self.check_map_rop_lop(TT.max(self.mx, axis=1),
+        self.check_mat_rop_lop(TT.max(self.mx, axis=1),
                                (self.mat_in_shape[0],))
 
     def test_max_argmax(self):