added a whole bunch of supported dtypes in base_tensor

_test_elemwise.py

@@ -2,7 +2,7 @@
 import unittest
 import numpy
 
-from tensor import tensor, Tensor
+from tensor import tinit, Tensor
 import gof
 from gof import modes, Env
 
@@ -10,6 +10,10 @@ from elemwise import *
 
 
 class ElemwiseAdd(Elemwise):
+
+    def __init__(self, x, y):
+        self.inputs = (x, y)
+        self.outputs = [Tensor(dtype = x.dtype, broadcastable = x.broadcastable)]
     
     def var_desc(self):
         return [('x', 1), ('y', 1)], [('z', 1)]
@@ -25,9 +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(tensor(l1, name = 'x'))
-    y = modes.build(tensor(l2, name = 'y'))
-    z = modes.build(tensor(l3, name = 'z'))
+    x = modes.build(tinit(l1, name = 'x'))
+    y = modes.build(tinit(l2, name = 'y'))
+    z = modes.build(tinit(l3, name = 'z'))
     return x, y, z
 
 def env(inputs, outputs, validate = True, features = []):
@@ -47,6 +51,17 @@ class _test_Elemwise(unittest.TestCase):
         fn()
         assert (e.data == numpy.array([[4, 6, 4, 6]])).all()
 
+#     def test_1(self):
+#         x, y, z = inputs()
+#         e = ElemwiseAdd(x, y).out
+#         fn, i, o = gof.CLinker(env([x, y], [e])).make_thunk(True)
+#         fn()
+#         assert (e.data == numpy.array([[4, 6], [4, 6]])).all()
+#         x.data.resize((1, 4))
+#         y.data.resize((1, 4))
+#         fn()
+#         assert (e.data == numpy.array([[4, 6, 4, 6]])).all()
+
 
 
 if __name__ == '__main__':

base_tensor.py

@@ -80,7 +80,12 @@ class BaseTensor(ResultBase):
         #TODO: add more type correspondances for e.g. int32, int64, float32,
         #complex64, etc.
         try:
-            return {'float64': (float, 'double', 'NPY_DOUBLE')}[self.dtype]
+            return {'float32': (float, 'npy_float32', 'NPY_FLOAT32'),
+                    'float64': (float, 'npy_float64', 'NPY_FLOAT64'),
+                    'int8': (int, 'npy_int8', 'NPY_INT8'),
+                    'int16': (int, 'npy_int16', 'NPY_INT16'),
+                    'int32': (int, 'npy_int32', 'NPY_INT32'),
+                    'int64': (int, 'npy_int64', 'NPY_INT64')}[self.dtype]
         except KeyError:
             raise TypeError("Unsupported dtype for BaseTensor: %s" % self.dtype)