def test_fluid_tf_equality(self):
tf.reset_default_graph()
_sess = tf.InteractiveSession()
for domain in [
Domain([8, 6], boundaries=OPEN),
Domain([8, 6], boundaries=STICKY),
Domain([8, 6], boundaries=SLIPPERY),
Domain([8, 6], boundaries=PERIODIC),
Domain([8, 6], boundaries=[PERIODIC, [OPEN, STICKY]])
]:
print('Comparing on domain %s' % (domain.boundaries, ))
np_fluid = Fluid(domain,
density=Noise(),
velocity=Noise(),
batch_size=10)
tf_fluid = constant(np_fluid)
physics = IncompressibleFlow(conserve_density=False)
for _ in range(3):
np_fluid = physics.step(np_fluid, 1.0)
tf_fluid = physics.step(tf_fluid, 1.0)
for np_tensor, tf_tensor in zip(struct.flatten(np_fluid),
struct.flatten(tf_fluid)):
tf_eval = tf_tensor.eval()
numpy.testing.assert_almost_equal(np_tensor,
tf_eval,
decimal=5)
def test_precision_16(self):
try:
math.set_precision(16)
fluid = Fluid(Domain([16, 16]), density=math.maximum(0, Noise()))
fluid = variable(fluid)
self.assertEqual(fluid.density.data.dtype.as_numpy_dtype,
numpy.float16)
self.assertEqual(
fluid.velocity.unstack()[0].data.dtype.as_numpy_dtype,
numpy.float16)
fluid = IncompressibleFlow().step(fluid, dt=1.0)
self.assertEqual(fluid.density.data.dtype.as_numpy_dtype,
numpy.float16)
self.assertEqual(
fluid.velocity.unstack()[0].data.dtype.as_numpy_dtype,
numpy.float16)
finally:
math.set_precision(32) # Reset environment