Use direct imports from theano.gof in theano.scalar.basic

theano/scalar/basic.py

@@ -20,11 +20,12 @@ from textwrap import dedent
 import numpy as np
 
 import theano
-from theano import gof, printing
+from theano import printing
 from theano.configdefaults import config
 from theano.gof.fg import FunctionGraph
-from theano.gof.graph import Apply, Constant, Variable
+from theano.gof.graph import Apply, Constant, Variable, clone, list_of_nodes
 from theano.gof.op import COp
+from theano.gof.opt import MergeOptimizer
 from theano.gof.type import Type
 from theano.gof.utils import (
     MetaObject,
@@ -118,7 +119,7 @@ get_scalar_type.cache = {}
 def as_scalar(x, name=None):
     from ..tensor import TensorType, scalar_from_tensor
 
-    if isinstance(x, gof.Apply):
+    if isinstance(x, Apply):
         if len(x.outputs) != 1:
             raise ValueError(
                 "It is ambiguous which output of a multi-output"
@@ -4123,7 +4124,7 @@ class Composite(ScalarOp):
         # the fgraph to be set to the variable as we need to pickle
         # them for the cache of c module to work.
         fgraph = FunctionGraph(self.inputs, self.outputs)
-        gof.MergeOptimizer().optimize(fgraph)
+        MergeOptimizer().optimize(fgraph)
         for node in fgraph.apply_nodes:
             if not isinstance(node.op, ScalarOp):
                 raise ValueError(
@@ -4148,7 +4149,7 @@ class Composite(ScalarOp):
             [isinstance(var.owner.op, Composite) for var in outputs]
         ):
             # No inner Composite
-            inputs, outputs = gof.graph.clone(inputs, outputs)
+            inputs, outputs = clone(inputs, outputs)
         else:
             # Inner Composite that we need to flatten
             assert len(outputs) == 1
@@ -4170,7 +4171,7 @@ class Composite(ScalarOp):
             inputs, outputs = res[0], res2[1]
             # Next assert comment just for speed
             # assert not any([isinstance(node.op, Composite) for node in
-            #                theano.gof.graph.ops(inputs, outputs)])
+            #                ops(inputs, outputs)])
 
         self.inputs = copy(inputs)
         self.outputs = copy(outputs)
@@ -4188,7 +4189,7 @@ class Composite(ScalarOp):
         if impl == "py":
             self.init_py_impls()  # self._impls
         if impl not in self.prepare_node_called:
-            for n in theano.gof.graph.list_of_nodes(self.inputs, self.outputs):
+            for n in list_of_nodes(self.inputs, self.outputs):
                 n.op.prepare_node(n, None, None, impl)
             self.prepare_node_called.add(impl)