file theano/compile/tests/test_builders.py

theano/compile/tests/test_builders.py

 from __future__ import absolute_import, print_function, division
-import numpy
+import numpy as np
 
 from theano import config, shared
 
@@ -23,14 +23,14 @@ class T_OpFromGraph(unittest_tools.InferShapeTester):
         f = op(x, y, z) - op(y, z, x)
 
         fn = function([x, y, z], f)
-        xv = numpy.ones((2, 2), dtype=config.floatX)
-        yv = numpy.ones((2, 2), dtype=config.floatX) * 3
-        zv = numpy.ones((2, 2), dtype=config.floatX) * 5
+        xv = np.ones((2, 2), dtype=config.floatX)
+        yv = np.ones((2, 2), dtype=config.floatX) * 3
+        zv = np.ones((2, 2), dtype=config.floatX) * 5
         # print function, function.__module__
         # print fn.maker.fgraph.toposort()
         fn(xv, yv, zv)
-        assert numpy.all(8.0 == fn(xv, yv, zv))
-        assert numpy.all(8.0 == fn(xv, yv, zv))
+        assert np.all(8.0 == fn(xv, yv, zv))
+        assert np.all(8.0 == fn(xv, yv, zv))
 
     def test_size_changes(self):
         x, y, z = T.matrices('xyz')
@@ -38,15 +38,15 @@ class T_OpFromGraph(unittest_tools.InferShapeTester):
         op = OpFromGraph([x, y], [e])
         f = op(x, op(y, z))
         fn = function([x, y, z], f)
-        xv = numpy.ones((2, 3), dtype=config.floatX)
-        yv = numpy.ones((3, 4), dtype=config.floatX) * 3
-        zv = numpy.ones((4, 5), dtype=config.floatX) * 5
+        xv = np.ones((2, 3), dtype=config.floatX)
+        yv = np.ones((3, 4), dtype=config.floatX) * 3
+        zv = np.ones((4, 5), dtype=config.floatX) * 5
         res = fn(xv, yv, zv)
         assert res.shape == (2, 5)
-        assert numpy.all(180.0 == res)
+        assert np.all(180.0 == res)
         res = fn(xv, yv, zv)
         assert res.shape == (2, 5)
-        assert numpy.all(180.0 == res)
+        assert np.all(180.0 == res)
 
     def test_grad(self):
         x, y, z = T.matrices('xyz')
@@ -55,10 +55,10 @@ class T_OpFromGraph(unittest_tools.InferShapeTester):
         f = op(x, y, z)
         f = f - T.grad(T.sum(f), y)
         fn = function([x, y, z], f)
-        xv = numpy.ones((2, 2), dtype=config.floatX)
-        yv = numpy.ones((2, 2), dtype=config.floatX) * 3
-        zv = numpy.ones((2, 2), dtype=config.floatX) * 5
-        assert numpy.all(11.0 == fn(xv, yv, zv))
+        xv = np.ones((2, 2), dtype=config.floatX)
+        yv = np.ones((2, 2), dtype=config.floatX) * 3
+        zv = np.ones((2, 2), dtype=config.floatX) * 5
+        assert np.all(11.0 == fn(xv, yv, zv))
 
     def test_grad_grad(self):
         x, y, z = T.matrices('xyz')
@@ -68,46 +68,46 @@ class T_OpFromGraph(unittest_tools.InferShapeTester):
         f = f - T.grad(T.sum(f), y)
         f = f - T.grad(T.sum(f), y)
         fn = function([x, y, z], f)
-        xv = numpy.ones((2, 2), dtype=config.floatX)
-        yv = numpy.ones((2, 2), dtype=config.floatX) * 3
-        zv = numpy.ones((2, 2), dtype=config.floatX) * 5
-        assert numpy.allclose(6.0, fn(xv, yv, zv))
+        xv = np.ones((2, 2), dtype=config.floatX)
+        yv = np.ones((2, 2), dtype=config.floatX) * 3
+        zv = np.ones((2, 2), dtype=config.floatX) * 5
+        assert np.allclose(6.0, fn(xv, yv, zv))
 
     def test_shared(self):
         x, y, z = T.matrices('xyz')
-        s = shared(numpy.random.rand(2, 2).astype(config.floatX))
+        s = shared(np.random.rand(2, 2).astype(config.floatX))
         e = x + y * z + s
         op = OpFromGraph([x, y, z], [e])
         # (1+3*5=array of 16) - (3+1*5=array of 8)
         f = op(x, y, z) - op(y, z, x)
 
         fn = function([x, y, z], f)
-        xv = numpy.ones((2, 2), dtype=config.floatX)
-        yv = numpy.ones((2, 2), dtype=config.floatX) * 3
-        zv = numpy.ones((2, 2), dtype=config.floatX) * 5
+        xv = np.ones((2, 2), dtype=config.floatX)
+        yv = np.ones((2, 2), dtype=config.floatX) * 3
+        zv = np.ones((2, 2), dtype=config.floatX) * 5
         # print function, function.__module__
         # print fn.maker.fgraph.toposort()
-        assert numpy.allclose(8.0, fn(xv, yv, zv))
-        assert numpy.allclose(8.0, fn(xv, yv, zv))
+        assert np.allclose(8.0, fn(xv, yv, zv))
+        assert np.allclose(8.0, fn(xv, yv, zv))
 
     def test_shared_grad(self):
         x, y, z = T.matrices('xyz')
-        s = shared(numpy.random.rand(2, 2).astype(config.floatX))
+        s = shared(np.random.rand(2, 2).astype(config.floatX))
         e = x + y * z + s
         op = OpFromGraph([x, y, z], [e])
         f = op(x, y, z)
         f = f - T.grad(T.sum(f), y)
         fn = function([x, y, z], f)
-        xv = numpy.ones((2, 2), dtype=config.floatX)
-        yv = numpy.ones((2, 2), dtype=config.floatX) * 3
-        zv = numpy.ones((2, 2), dtype=config.floatX) * 5
-        assert numpy.allclose(11.0 + s.get_value(), fn(xv, yv, zv))
+        xv = np.ones((2, 2), dtype=config.floatX)
+        yv = np.ones((2, 2), dtype=config.floatX) * 3
+        zv = np.ones((2, 2), dtype=config.floatX) * 5
+        assert np.allclose(11.0 + s.get_value(), fn(xv, yv, zv))
 
         # grad again the shared variable
         f = op(x, y, z)
         f = f - T.grad(T.sum(f), s)
         fn = function([x, y, z], f)
-        assert numpy.allclose(15.0 + s.get_value(),
+        assert np.allclose(15.0 + s.get_value(),
                               fn(xv, yv, zv))
 
     def test_connection_pattern(self):
@@ -163,6 +163,6 @@ class T_OpFromGraph(unittest_tools.InferShapeTester):
         p = T.matrix('p')
         self._compile_and_check([q, p],
                                 op_graph(q, p),
-                                [numpy.ones([3, 4], dtype=config.floatX),
-                                 numpy.ones([3, 4], dtype=config.floatX)],
+                                [np.ones([3, 4], dtype=config.floatX),
+                                 np.ones([3, 4], dtype=config.floatX)],
                                 OpFromGraph)