removed with_stack_trace and other small changes

theano/gof/opt.py

@@ -2903,7 +2903,7 @@ def pre_greedy_local_optimizer(list_optimizations, out):
 def copy_stack_trace(from_var, to_var):
     """
     Copies the stack trace from one or more tensor variables to
-    one or more tensor variables.
+    one or more tensor variables and returns the destination variables.
 
     Parameters
     ----------
@@ -2947,34 +2947,6 @@ def copy_stack_trace(from_var, to_var):
         # Copy over stack traces from from_var to each variable to
         # to_var, including the stack_trace of the to_var before
         to_var.tag.trace = getattr(to_var.tag, 'trace', []) + tr
-
-
-def with_stack_trace(from_var, to_var):
-    """
-    Copies the stack trace from one or more tensor variables to
-    one or more tensor variables and returns the destination variables.
-
-    Parameters
-    ----------
-    from_var
-        Tensor variable or list of tensor variables to copy stack traces from.
-    to_var
-        Tensor variable or list of tensor variables to copy stack traces to.
-
-    Returns
-    -------
-    tensor variable or list of tensor variables
-        `to_var`, augmented with the stack traces from `from_var`.
-
-    Notes
-    -----
-    The stacktrace is assumed to be of the form of a list of lists
-    of tuples. Each tuple contains the filename, line number, function name
-    and so on. Each list of tuples contains the truples belonging to a
-    particular variable.
-
-    """
-    copy_stack_trace(from_var, to_var)
     return to_var
 
 

theano/gpuarray/basic_ops.py

@@ -15,7 +15,7 @@ from theano.tensor.basic import (
 
 from theano.gof import HideC, COp, ParamsType
 from theano.gof.utils import MethodNotDefined
-from theano.gof.opt import with_stack_trace
+from theano.gof.opt import copy_stack_trace
 
 from collections import deque
 
@@ -76,11 +76,11 @@ def as_gpuarray_variable(x, context_name):
 
         # If we couldn't deal with transfers, then maybe it's a tensor
         if isinstance(x.type, tensor.TensorType):
-            return with_stack_trace(x, GpuFromHost(context_name)(x))
+            return copy_stack_trace(x, GpuFromHost(context_name)(x))
 
     # Try _as_GpuArrayVariable if possible
     if hasattr(x, '_as_GpuArrayVariable'):
-        return with_stack_trace(x, x._as_GpuArrayVariable(context_name))
+        return copy_stack_trace(x, x._as_GpuArrayVariable(context_name))
 
     # If it didn't work try for a constant
     ctx = get_context(context_name)

theano/gpuarray/blas.py

@@ -1831,20 +1831,17 @@ class GpuCorr3dMM_gradInputs(BaseGpuCorr3dMM):
 
 @inplace_allocempty(GpuGemv, 0)
 def local_inplace_gpuagemv(node, inputs):
-    with inherit_stack_trace(node.outputs):
-        return [gpugemv_inplace(*inputs)]
+    return [gpugemv_inplace(*inputs)]
 
 
 @inplace_allocempty(GpuGemm, 0)
 def local_inplace_gpuagemm(node, inputs):
-    with inherit_stack_trace(node.outputs):
-        return [gpugemm_inplace(*inputs)]
+    return [gpugemm_inplace(*inputs)]
 
 
 @inplace_allocempty(GpuGer, 0)
 def local_inplace_gpuager(node, inputs):
-    with inherit_stack_trace(node.outputs):
-        return [gpuger_inplace(*inputs)]
+    return [gpuger_inplace(*inputs)]
 
 
 @inplace_allocempty(GpuGemmBatch, 0)

theano/gpuarray/opt.py

@@ -16,7 +16,7 @@ from theano.gof import (local_optimizer, EquilibriumDB, TopoOptimizer,
                         LocalGroupDB,
                         SequenceDB, Optimizer, DB, toolbox, graph)
 from theano.gof.opt import (LocalMetaOptimizer, copy_stack_trace,
-                            with_stack_trace, inherit_stack_trace)
+                            inherit_stack_trace)
 from theano.ifelse import IfElse
 from theano.misc.ordered_set import OrderedSet
 
@@ -468,7 +468,7 @@ class GraphToGPU(Optimizer):
                         new_o.owner.inputs[0].type == o.type):
                     new_o = new_o.owner.inputs[0]
                 else:
-                    new_o = with_stack_trace(o, safe_to_cpu(new_o))
+                    new_o = copy_stack_trace(o, safe_to_cpu(new_o))
             new_nodes.append(new_o)
         fgraph.replace_all_validate(zip(fgraph.outputs, new_nodes),
                                     reason=self.__class__.__name__)

theano/tensor/opt_uncanonicalize.py

@@ -43,7 +43,7 @@ from theano.tensor import DimShuffle, Subtensor
 
 from theano.tensor.opt import register_uncanonicalize
 from theano import scalar as scal
-from theano.gof.opt import copy_stack_trace, with_stack_trace
+from theano.gof.opt import copy_stack_trace
 
 _logger = logging.getLogger('theano.tensor.opt')
 
@@ -89,7 +89,7 @@ def local_max_to_min(node):
             neg = max.owner.inputs[0]
             if neg.owner and neg.owner.op == T.neg:
                 new = CAReduce(scal.minimum, max.owner.op.axis)(neg.owner.inputs[0])
-                return [with_stack_trace(node.outputs[0], new)]
+                return [copy_stack_trace(node.outputs[0], new)]
 
     return False