add more tests

theano/tensor/tests/test_2nd_order_grads.py

@@ -8,17 +8,130 @@ import theano
 from theano import tensor
 import numpy
 
+utt.seed_rng()
 
-def test_jacobian():
+def test001_jacobian_vector():
     x = tensor.vector()
     y = x * 2
+    rng = numpy.random.RandomState(seed=utt.fetch_seed())
+
+    # test when the jacobian is called with a tensor as wrt
     Jx = tensor.jacobian(y, x)
     f = theano.function([x], Jx, allow_input_downcast=True)
-    vx = numpy.arange(10).astype(theano.config.floatX)
+    vx = rng.uniform(size=(10,)).astype(theano.config.floatX)
+    assert numpy.allclose(f(vx), numpy.eye(10) * 2)
+
+    # test when the jacobian is called with a tuple as wrt
+    Jx = tensor.jacobian(y, (x,))
+    assert isinstance(Jx, tuple)
+    f = theano.function([x], Jx[0], allow_input_downcast=True)
+    vx = rng.uniform(size=(10,)).astype(theano.config.floatX)
+    assert numpy.allclose(f(vx), numpy.eye(10) * 2)
+
+    # test when the jacobian is called with a list as wrt
+    Jx = tensor.jacobian(y, [x])
+    f = theano.function([x], Jx[0], allow_input_downcast=True)
+    vx = rng.uniform(size=(10,)).astype(theano.config.floatX)
     assert numpy.allclose(f(vx), numpy.eye(10) * 2)
 
+    # test when the jacobian is called wit a list of two elements
+    z = tensor.vector()
+    y = x * z
+    Js = tensor.jacobian(y, [x, z])
+    f = theano.function([x, z], Js, allow_input_downcast=True)
+    vx = rng.uniform(size=(10,)).astype(theano.config.floatX)
+    vz = rng.uniform(size=(10,)).astype(theano.config.floatX)
+    vJs = f(vx, vz)
+    evx = numpy.zeros((10,10))
+    evz = numpy.zeros((10,10))
+    for dx in xrange(10):
+        evx[dx,dx] = vx[dx]
+        evz[dx,dx] = vz[dx]
+    assert numpy.allclose(vJs[0], evz)
+    assert numpy.allclose(vJs[1], evx)
+
+
+def test002_jacobian_matrix():
+    x = tensor.matrix()
+    y = 2 * x.sum(axis=0)
+    rng = numpy.random.RandomState(seed=utt.fetch_seed())
+    ev = numpy.zeros((10,10,10))
+    for dx in xrange(10):
+        ev[dx,:,dx] = 2.
+
+    # test when the jacobian is called with a tensor as wrt
+    Jx = tensor.jacobian(y, x)
+    f = theano.function([x], Jx, allow_input_downcast=True)
+    vx = rng.uniform(size=(10,10)).astype(theano.config.floatX)
+    assert numpy.allclose(f(vx), ev)
+
+    # test when the jacobian is called with a tuple as wrt
+    Jx = tensor.jacobian(y, (x,))
+    assert isinstance(Jx, tuple)
+    f = theano.function([x], Jx[0], allow_input_downcast=True)
+    vx = rng.uniform(size=(10,10)).astype(theano.config.floatX)
+    assert numpy.allclose(f(vx), ev)
+
+    # test when the jacobian is called with a list as wrt
+    Jx = tensor.jacobian(y, [x])
+    f = theano.function([x], Jx[0], allow_input_downcast=True)
+    vx = rng.uniform(size=(10,10)).astype(theano.config.floatX)
+    assert numpy.allclose(f(vx), ev)
+
+    # test when the jacobian is called wit a list of two elements
+    z = tensor.matrix()
+    y = (x * z).sum(axis=1)
+    Js = tensor.jacobian(y, [x, z])
+    f = theano.function([x, z], Js, allow_input_downcast=True)
+    vx = rng.uniform(size=(10,10)).astype(theano.config.floatX)
+    vz = rng.uniform(size=(10,10)).astype(theano.config.floatX)
+    vJs = f(vx, vz)
+    evx = numpy.zeros((10,10,10))
+    evz = numpy.zeros((10,10,10))
+    for dx in xrange(10):
+        evx[dx,dx,:] = vx[dx,:]
+        evz[dx,dx,:] = vz[dx,:]
+    assert numpy.allclose(vJs[0], evz)
+    assert numpy.allclose(vJs[1], evx)
+
+
+def test003_jacobian_scalar():
+    x = tensor.scalar()
+    y = x * 2
+    rng = numpy.random.RandomState(seed=utt.fetch_seed())
+
+    # test when the jacobian is called with a tensor as wrt
+    Jx = tensor.jacobian(y, x)
+    f = theano.function([x], Jx, allow_input_downcast=True)
+    vx = numpy.cast[theano.config.floatX](rng.uniform())
+    assert numpy.allclose(f(vx), 2)
+
+    # test when the jacobian is called with a tuple as wrt
+    Jx = tensor.jacobian(y, (x,))
+    assert isinstance(Jx, tuple)
+    f = theano.function([x], Jx[0], allow_input_downcast=True)
+    vx = numpy.cast[theano.config.floatX](rng.uniform())
+    assert numpy.allclose(f(vx), 2)
+
+    # test when the jacobian is called with a list as wrt
+    Jx = tensor.jacobian(y, [x])
+    f = theano.function([x], Jx[0], allow_input_downcast=True)
+    vx = numpy.cast[theano.config.floatX](rng.uniform())
+    assert numpy.allclose(f(vx), 2)
+
+    # test when the jacobian is called wit a list of two elements
+    z = tensor.scalar()
+    y = x * z
+    Jx = tensor.jacobian(y, [x, z])
+    f = theano.function([x, z], Jx, allow_input_downcast=True)
+    vx = numpy.cast[theano.config.floatX](rng.uniform())
+    vz = numpy.cast[theano.config.floatX](rng.uniform())
+    vJx = f(vx, vz)
+
+    assert numpy.allclose(vJx[0], vz)
+    assert numpy.allclose(vJx[1], vx)
 
-def test_hessian():
+def test004_hessian():
     x = tensor.vector()
     y = tensor.sum(x ** 2)
     Hx = tensor.hessian(y, x)