PEP 8 fixes

theano/scan_module/scan_op.py

@@ -334,14 +334,14 @@ class Scan(PureOp):
                                            inner_mitsots[ipos + k].type.ndim))
             ipos += len(itaps)
             if (inner_mitsot_out.type.dtype != outer_mitsot.type.dtype or
-                 inner_mitsot_out.ndim != outer_mitsot.ndim - 1):
-                    raise ValueError(err_msg2 %
-                                      (str(outer_mitsot),
-                                           argoffset + idx,
-                                           outer_mitsot.type.dtype,
-                                           outer_mitsot.type.ndim,
-                                           inner_mitsot_out.type.dtype,
-                                           inner_mitsot_out.type.ndim))
+                inner_mitsot_out.ndim != outer_mitsot.ndim - 1):
+                raise ValueError(err_msg2 %
+                                 (str(outer_mitsot),
+                                 argoffset + idx,
+                                 outer_mitsot.type.dtype,
+                                 outer_mitsot.type.ndim,
+                                 inner_mitsot_out.type.dtype,
+                                 inner_mitsot_out.type.ndim))
 
         argoffset += len(self.outer_mitsot(inputs))
         # Same checks as above but for outputs of type sit_sot
@@ -353,22 +353,22 @@ class Scan(PureOp):
                 inner_sitsot.ndim != outer_sitsot.ndim - 1):
                 raise ValueError(err_msg1 % ('initial state (outputs_info'
                                            ' in scan nomenclature) ',
-                                           str(outer_sitsot),
-                                           argoffset + idx,
-                                           outer_sitsot.type.dtype,
-                                           outer_sitsot.type.ndim,
-                                           str(inner_sitsot),
-                                           inner_sitsot.type.dtype,
-                                           inner_sitsot.type.ndim))
+                                str(outer_sitsot),
+                                argoffset + idx,
+                                outer_sitsot.type.dtype,
+                                outer_sitsot.type.ndim,
+                                str(inner_sitsot),
+                                inner_sitsot.type.dtype,
+                                inner_sitsot.type.ndim))
             if (inner_sitsot_out.type.dtype != outer_sitsot.type.dtype or
                 inner_sitsot_out.ndim != outer_sitsot.ndim - 1):
-                    raise ValueError(err_msg2 %
-                                      (str(outer_sitsot),
-                                           argoffset + idx,
-                                           outer_sitsot.type.dtype,
-                                           outer_sitsot.type.ndim,
-                                           inner_sitsot_out.type.dtype,
-                                           inner_sitsot_out.type.ndim))
+                raise ValueError(err_msg2 %
+                                (str(outer_sitsot),
+                                argoffset + idx,
+                                outer_sitsot.type.dtype,
+                                outer_sitsot.type.ndim,
+                                inner_sitsot_out.type.dtype,
+                                inner_sitsot_out.type.ndim))
 
         argoffset += len(self.outer_sitsot(inputs))
         # Check that the shared variable and their update rule have the same
@@ -1237,7 +1237,6 @@ class Scan(PureOp):
         else:
             return -1
 
-
     def get_output_slice_idx(self, output_index):
         ipos = 0
         opos = output_index
@@ -1287,6 +1286,7 @@ class Scan(PureOp):
         dC_dXts = []
         Xts = []
         for idx, Xt in enumerate(diff_outputs):
+
             # We are looking for x[t-1] for a given x[t]
             if idx >= self.n_mit_mot_outs:
                 Xt_placeholder = Xt.type()
@@ -1333,7 +1333,7 @@ class Scan(PureOp):
         # construct dX_dtm1
         dC_dXtm1s = [x.type() for x in dC_dinps_t[self.n_seqs:]]
         for dx, dC_dXtm1 in enumerate(dC_dXtm1s):
-            dC_dinps_t[dx+self.n_seqs] += dC_dXtm1
+            dC_dinps_t[dx + self.n_seqs] += dC_dXtm1
         # Construct scan op
         # Seqs
         outer_inp_seqs = [x[::-1] for x in inputs[1:1 + self.n_seqs]]
@@ -1399,7 +1399,7 @@ class Scan(PureOp):
                 inner_inp_mitmot.append(dC_dXtm1s[ins_pos - self.n_seqs])
                 inner_out_mitmot.append(dC_dinps_t[ins_pos])
                 if not disconnected_dC_dinps_t[ins_pos]:
-                    disconnected=False
+                    disconnected = False
                 for _sh in self.inner_shared(self_inputs):
                     if _sh in gof.graph.inputs([dC_dinps_t[ins_pos]]):
                         undefined = True
@@ -1429,11 +1429,11 @@ class Scan(PureOp):
             mitmot_inp_taps[idx + offset].append(0)
             for jdx in xrange(len(self.tap_array[idx_tap])):
                 inner_inp_mitmot.append(dC_dXtm1s[ins_pos - self.n_seqs])
+                inner_out_mitmot.append(dC_dinps_t[ins_pos])
                 mitmot_inp_taps[idx + offset].append(
                     -self.tap_array[idx_tap][jdx])
                 mitmot_out_taps[idx].append(
                     -self.tap_array[idx_tap][jdx])
-                inner_out_mitmot.append(dC_dinps_t[ins_pos])
                 if not disconnected_dC_dinps_t[ins_pos]:
                     disconnected = False
                 for _sh in self.inner_shared(self_inputs):
@@ -1459,7 +1459,7 @@ class Scan(PureOp):
             else:
                 outer_inp_mitmot.append(
                     tensor.zeros(outs[idx + offset].shape,
-                                 dtype = dC_dinps_t[ins_pos].dtype))
+                                 dtype=dC_dinps_t[ins_pos].dtype))
             inner_out_mitmot.append(dC_dinps_t[ins_pos])
             for _sh in self.inner_shared(self_inputs):
                 if _sh in gof.graph.inputs([dC_dinps_t[ins_pos]]):
@@ -1511,7 +1511,7 @@ class Scan(PureOp):
         outer_inp_sitsot = [
             tensor.zeros([grad_steps + 1] +
                          [x.shape[i] for i in xrange(x.ndim)],
-                         dtype = y.dtype)
+                         dtype=y.dtype)
             for y, x in zip(inner_inp_sitsot,
                             self.outer_non_seqs(inputs))]
 

theano/scan_module/scan_opt.py

@@ -23,7 +23,8 @@ from theano import gof
 from theano.gof.python25 import maxsize
 from theano.gof.opt import Optimizer
 from theano.gof import toolbox, DestroyHandler, InconsistencyError
-from theano.compile import deep_copy_op, optdb
+from theano.compile import optdb
+from theano.compile.function_module import deep_copy_op
 
 import scan_op
 import scan_utils
@@ -221,7 +222,7 @@ class PushOutNonSeqScan(gof.Optimizer):
                                  'to move some computation fron scan '
                                  'which is not allowed to move. Report '
                                  'this on theano-users list'), x)
-                    outside_ins = [x.type.filter_variable(y) for x,y in
+                    outside_ins = [x.type.filter_variable(y) for x, y in
                                    zip(nd.inputs, outside_ins)]
                     nw_outer_node = nd.op.make_node(*outside_ins)
                     # Step 2. Create variables for replacements
@@ -681,7 +682,10 @@ class ScanSaveMem(gof.Optimizer):
                         if (nw_inputs[offset + idx].owner and
                             isinstance(nw_inputs[offset + idx].owner.op,
                                        tensor.IncSubtensor) and
-                            isinstance(nw_inputs[offset+idx].owner.op.idx_list[0], slice)):
+                            isinstance(
+                                nw_inputs[offset + idx].owner.op.idx_list[0],
+                                slice)):
+
                             _nw_input = nw_inputs[offset + idx].owner.inputs[1]
                             cval = tensor.as_tensor_variable(val)
                             initl = tensor.as_tensor_variable(init_l[i])