Renamed tinit to astensor

_test_elemwise.py

@@ -2,7 +2,7 @@
 import unittest
 import numpy
 
-from tensor import tinit, Tensor
+from tensor import astensor, Tensor
 import gof
 from gof import modes, Env
 
@@ -29,9 +29,9 @@ def inputs():
     l1 = [[1.0, 2.0], [3.0, 4.0]]
     l2 = [[3.0, 4.0], [1.0, 2.0]]
     l3 = numpy.ones((2, 3))
-    x = modes.build(tinit(l1, name = 'x'))
-    y = modes.build(tinit(l2, name = 'y'))
-    z = modes.build(tinit(l3, name = 'z'))
+    x = modes.build(astensor(l1, name = 'x'))
+    y = modes.build(astensor(l2, name = 'y'))
+    z = modes.build(astensor(l3, name = 'z'))
     return x, y, z
 
 def env(inputs, outputs, validate = True, features = []):

tensor.py

@@ -67,7 +67,7 @@ class Tensor(BaseTensor):
     def __getslice__(self, *args): return subtensor(self, slice(*args))
 
 # alternate Tensor constructor
-def tinit(data, broadcastable=None, role=None, name=None):
+def astensor(data, broadcastable=None, role=None, name=None):
     """Return a Tensor containing given data"""
     data = numpy.asarray(data)
     if broadcastable is None:
@@ -90,7 +90,7 @@ def _scalar_switch(normal_f, scalar_f, scalar_f_reverse = None):
             if isinstance(obj, Tensor):
                 return obj
             else:
-                return tinit(obj)
+                return astensor(obj)
         x, y = as_tensor(x), as_tensor(y)
         if 0 not in y.broadcastable:
             return scalar_f(x, y)
@@ -119,7 +119,7 @@ def _as_tensor(obj):
     if isinstance(obj, Tensor):
         return obj
     else:
-        return tinit(obj)
+        return astensor(obj)
 
 class _Op(BaseTensorOp):
     """A convenient base for the ops in this file"""