Removed depricated refrences to other_ignore arguments (they were not used

theano/scan_module/__init__.py

@@ -646,7 +646,7 @@ if cuda.cuda_available:
                      + thescan.n_shared_outs)
                 nw_ins += [safe_to_gpu(x) for x in inputs[1:e] ]
                 b = e
-                e = e + thescan.n_nit_sot + thescan.n_other_ignore
+                e = e + thescan.n_nit_sot
                 nw_ins += inputs[b:e]
                 nw_ins += [safe_to_gpu(x) for x in inputs[e:] ]
                 scan_ins = [ tensor_to_cuda(x) for x in thescan.inputs]
@@ -678,7 +678,7 @@ if cuda.cuda_available:
                      + thescan.n_shared_outs)
                 nw_ins += [safe_to_gpu(x) for x in inputs[1:e] ]
                 b = e
-                e = e + thescan.n_nit_sot + thescan.n_other_ignore
+                e = e + thescan.n_nit_sot
                 nw_ins += inputs[b:e]
                 nw_ins += [safe_to_gpu(x) for x in inputs[e:] ]
 

theano/scan_module/scan.py

@@ -759,23 +759,14 @@ def scan( fn
             nit_sot_rightOrder.append( i )
             n_nit_sot += 1
 
-    ## Step 5.5 Sequences with no taps used
-    n_other_ignore    = 0
-    ignore_scan_seqs  = []
-    ignore_inner_seqs = []
-    for i,seq in enumerate(seqs):
-        if not 'taps' in seq:
-            ignore_scan_seqs.append(seq['input'])
-            n_other_ignore += 1
-
-    ## Step 5.6 all other arguments including extra inputs
+    ## Step 5.5 all other arguments including extra inputs
     other_scan_args  = []
     other_inner_args = []
 
     other_scan_args  += [ arg for arg in non_seqs
                         if not isinstance(arg, SharedVariable) ]
 
-    ## Step 5.8 all shared variables with no update rules
+    ## Step 5.6 all shared variables with no update rules
     def new_variable( v ):
         new_v = safe_new(v)
         if v.name:
@@ -805,7 +796,6 @@ def scan( fn
                     mit_sot_inner_inputs    +
                     sit_sot_inner_inputs    +
                     shared_inner_inputs     +
-                    ignore_inner_seqs       +
                     other_shared_inner_args +
                     other_inner_args        )
 
@@ -850,7 +840,6 @@ def scan( fn
     info['n_sit_sot']          = n_sit_sot
     info['n_shared_outs']      = n_shared_outs
     info['n_nit_sot']          = n_nit_sot
-    info['n_other_ignore']     = n_other_ignore
     info['truncate_gradient']  = truncate_gradient
     info['name']               = name
     info['mode']               = mode
@@ -876,7 +865,6 @@ def scan( fn
                    sit_sot_scan_inputs                           +
                    shared_scan_inputs                            +
                    [ actual_n_steps for x in xrange(n_nit_sot) ] +
-                   ignore_scan_seqs                              +
                    other_shared_scan_args                        +
                    other_scan_args                               )
 

theano/scan_module/scan_op.py

@@ -427,7 +427,7 @@ class Scan(Op):
                 outs[idx][0] = args[self.seqs_arg_offset + idx].copy()
 
 
-        offset = self.nit_sot_arg_offset + self.n_nit_sot + self.n_other_ignore
+        offset = self.nit_sot_arg_offset + self.n_nit_sot
         other_args = args[offset:]
         zipped_outs = [(outs[idx], self.vector_outs[idx], tap,
                        store_steps[idx], idx) for idx in xrange(self.n_outs)
@@ -595,7 +595,7 @@ class Scan(Op):
             outs_shape += [ input_shapes[idx+offset] ]
 
         # non_sequences
-        offset += self.n_nit_sot + self.n_other_ignore + self.n_shared_outs
+        offset += self.n_nit_sot + self.n_shared_outs
         inner_ins_shapes = seqs_shape + outs_shape + input_shapes[offset:]
         assert len(inner_ins_shapes) == len(self.inputs)
 
@@ -940,10 +940,8 @@ class Scan(Op):
             info['name'] = None
         info['mode']                     = self.mode
         info['inplace']                  = False
-        info['n_other_ignore']           = 0
         n_mit_sot           = 0
         n_sit_sot           = 0
-        n_other_ignore_seqs = 0
         if self.truncate_gradient != -1 :
             do_steps = tensor.minimum(args[0], self.truncate_gradient)
         else:
@@ -955,8 +953,7 @@ class Scan(Op):
                   + self.n_mit_sot
                   + self.n_sit_sot
                   + self.n_nit_sot
-                  + self.n_shared_outs
-                  + self.n_other_ignore )
+                  + self.n_shared_outs )
 
         scan_inputs = ( [do_steps]                            +
                        scan_seqs                              +
@@ -999,7 +996,6 @@ class Scan(Op):
         gradients += [ x[::-1] for x in outputs[:end]]
         gradients += [ None for x in xrange(self.n_shared_outs)]
         gradients += [ None for x in xrange(self.n_nit_sot) ]
-        gradients += [ None for x in xrange(self.n_other_ignore) ]
         begin = end + self.n_seqs
 
         end   = begin + n_shared_outs

theano/scan_module/scan_utils.py

@@ -754,7 +754,6 @@ def compress_outs(op, not_required, inputs):
     info['n_sit_sot']          = 0
     info['n_shared_outs']      = 0
     info['n_nit_sot']          = 0
-    info['n_other_ignore']     = op.info['n_other_ignore']
     info['truncate_gradient']  = op.info['truncate_gradient']
     info['name']               = op.info['name']
     info['inplace']            = op.info['inplace']