Merge pull request #5532 from nouiz/interface_cleanup

theano/gradient.py

@@ -1339,7 +1339,7 @@ def _float_ones_like(x):
     if dtype not in tensor.float_dtypes:
         dtype = theano.config.floatX
 
-    return tensor.ones_like(x, dtype=dtype)
+    return x.ones_like(dtype=dtype)
 
 
 class numeric_grad(object):

theano/scalar/basic.py

@@ -790,6 +790,12 @@ class _scalar_py_operators:
             dtype = str(self.type.dtype)
         return second(self, ScalarConstant(get_scalar_type(dtype), 0))
 
+    def ones_like(self, dtype=None):
+        # The second is needed for Elemwise ops to work right
+        if dtype is None:
+            dtype = str(self.type.dtype)
+        return second(self, ScalarConstant(get_scalar_type(dtype), 1))
+
     def astype(self, dtype):
         return cast(self, dtype)
 

theano/scan_module/scan_opt.py

@@ -1822,8 +1822,7 @@ class ScanMerge(gof.Optimizer):
                 len(rep.inputs) != len(node.inputs) or
                 len(rep.outputs) != len(node.outputs) or
                 node.op.truncate_gradient != rep.op.truncate_gradient or
-                node.op.mode != rep.op.mode or
-                rep.op.as_while != node.op.as_while):
+                node.op.mode != rep.op.mode):
             return False
 
         nsteps = node.inputs[0]

theano/tensor/var.py

@@ -731,6 +731,9 @@ class _tensor_py_operators(object):
     def zeros_like(model, dtype=None):
         return theano.tensor.basic.zeros_like(model, dtype=dtype)
 
+    def ones_like(model, dtype=None):
+        return theano.tensor.basic.ones_like(model, dtype=dtype)
+
     def cumsum(self, axis=None):
         return theano.tensor.extra_ops.cumsum(self, axis)