def test_vector_arguments(self):
m = Module()
m.random = RandomStreams(utt.fetch_seed())
low = tensor.vector()
out = m.random.uniform(low=low, high=1)
assert out.ndim == 1
m.f = Method([low], out)
high = tensor.vector()
outb = m.random.uniform(low=low, high=high)
assert outb.ndim == 1
m.fb = Method([low, high], outb)
size = tensor.lvector()
outc = m.random.uniform(low=low, high=high, size=size, ndim=1)
m.fc = Method([low, high, size], outc)
made = m.make()
made.random.initialize()
seed_gen = numpy.random.RandomState(utt.fetch_seed())
numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
low_val0 = numpy.asarray([-5, .5, 0, 1], dtype=config.floatX)
low_val1 = numpy.asarray([.9], dtype=config.floatX)
val0 = made.f(low_val0)
val1 = made.f(low_val1)
numpy_val0 = numpy_rng.uniform(low=low_val0, high=1)
numpy_val1 = numpy_rng.uniform(low=low_val1, high=1)
assert numpy.allclose(val0, numpy_val0)
assert numpy.allclose(val1, numpy_val1)
numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
val0b = made.fb([-4., -2], [-1, 0])
val1b = made.fb([-4.], [-1])
numpy_val0b = numpy_rng.uniform(low=[-4., -2], high=[-1, 0])
numpy_val1b = numpy_rng.uniform(low=[-4.], high=[-1])
assert numpy.allclose(val0b, numpy_val0b)
assert numpy.allclose(val1b, numpy_val1b)
self.assertRaises(ValueError, made.fb, [-4., -2], [-1, 0, 1])
#TODO: do we want that?
#self.assertRaises(ValueError, made.fb, [-4., -2], [-1])
numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
val0c = made.fc([-4., -2], [-1, 0], [2])
val1c = made.fc([-4.], [-1], [1])
numpy_val0c = numpy_rng.uniform(low=[-4., -2], high=[-1, 0])
numpy_val1c = numpy_rng.uniform(low=[-4.], high=[-1])
assert numpy.allclose(val0c, numpy_val0c)
assert numpy.allclose(val1c, numpy_val1c)
self.assertRaises(ValueError, made.fc, [-4., -2], [-1, 0], [1])
self.assertRaises(ValueError, made.fc, [-4., -2], [-1, 0], [1, 2])
self.assertRaises(ValueError, made.fc, [-4., -2], [-1, 0], [2, 1])
self.assertRaises(ValueError, made.fc, [-4., -2], [-1], [1])
def test_vector_arguments(self):
m = Module()
m.random = RandomStreams(utt.fetch_seed())
low = tensor.vector()
out = m.random.uniform(low=low, high=1)
assert out.ndim == 1
m.f = Method([low], out)
high = tensor.vector()
outb = m.random.uniform(low=low, high=high)
assert outb.ndim == 1
m.fb = Method([low, high], outb)
size = tensor.lvector()
outc = m.random.uniform(low=low, high=high, size=size, ndim=1)
m.fc = Method([low, high, size], outc)
made = m.make()
made.random.initialize()
seed_gen = numpy.random.RandomState(utt.fetch_seed())
numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
low_val0 = numpy.asarray([-5, .5, 0, 1], dtype=config.floatX)
low_val1 = numpy.asarray([.9], dtype=config.floatX)
val0 = made.f(low_val0)
val1 = made.f(low_val1)
numpy_val0 = numpy_rng.uniform(low=low_val0, high=1)
numpy_val1 = numpy_rng.uniform(low=low_val1, high=1)
assert numpy.allclose(val0, numpy_val0)
assert numpy.allclose(val1, numpy_val1)
numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
val0b = made.fb([-4., -2], [-1, 0])
val1b = made.fb([-4.], [-1])
numpy_val0b = numpy_rng.uniform(low=[-4., -2], high=[-1, 0])
numpy_val1b = numpy_rng.uniform(low=[-4.], high=[-1])
assert numpy.allclose(val0b, numpy_val0b)
assert numpy.allclose(val1b, numpy_val1b)
self.assertRaises(ValueError, made.fb, [-4., -2], [-1, 0, 1])
#TODO: do we want that?
#self.assertRaises(ValueError, made.fb, [-4., -2], [-1])
numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
val0c = made.fc([-4., -2], [-1, 0], [2])
val1c = made.fc([-4.], [-1], [1])
numpy_val0c = numpy_rng.uniform(low=[-4., -2], high=[-1, 0])
numpy_val1c = numpy_rng.uniform(low=[-4.], high=[-1])
assert numpy.allclose(val0c, numpy_val0c)
assert numpy.allclose(val1c, numpy_val1c)
self.assertRaises(ValueError, made.fc, [-4., -2], [-1, 0], [1])
self.assertRaises(ValueError, made.fc, [-4., -2], [-1, 0], [1,2])
self.assertRaises(ValueError, made.fc, [-4., -2], [-1, 0], [2,1])
self.assertRaises(ValueError, made.fc, [-4., -2], [-1], [1])
