def test_cant_serialize():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
prng = rng()
s = initialize(defn, data, prng)
s.serialize()
def test_cant_serialize():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
prng = rng()
s = initialize(defn, data, prng)
s.serialize()
def test_multi_dish_initialization():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng, initial_dishes=V)
assert_true(s.ntopics() > 1)
def test_single_dish_initialization():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng, initial_dishes=1)
assert_equals(s.ntopics(), 0) # Only dummy topic
def test_simple():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng)
assert_equals(s.nentities(), len(data))
def test_single_dish_initialization():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng, initial_dishes=1)
assert_equals(s.ntopics(), 0) # Only dummy topic
def test_multi_dish_initialization():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng, initial_dishes=V)
assert_true(s.ntopics() > 1)
def test_simple():
N, V = 10, 100
defn = model_definition(N, V)
data = toy_dataset(defn)
view = numpy_dataview(data)
R = rng()
s = initialize(defn, view, R)
assert_equals(s.nentities(), len(data))
def test_simple():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng)
assert_equals(s.nentities(), len(data))
def test_simple():
N, V = 10, 100
defn = model_definition(N, V)
data = toy_dataset(defn)
view = numpy_dataview(data)
R = rng()
s = initialize(defn, view, R)
assert_equals(s.nentities(), len(data))
def test_runner_specify_basic_kernel():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
latent = model.initialize(defn, view, prng)
r = runner.runner(defn, view, latent, ["crf"])
r.run(prng, 1)
def test_runner_simple():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
latent = model.initialize(defn, view, prng)
r = runner.runner(defn, view, latent)
r.run(prng, 1)
def test_runner_simple():
N, V = 10, 100
defn = model_definition(N, V)
data = toy_dataset(defn)
view = numpy_dataview(data)
prng = rng()
latent = model.initialize(defn, view, prng)
kc = runner.default_kernel_config(defn)
r = runner.runner(defn, view, latent, kc)
r.run(prng, 1)
def test_serialize_simple():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng)
m = s.serialize()
s2 = deserialize(defn, m)
assert s2.__class__ == s.__class__
def test_runner_specify_hp_kernels():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
latent = model.initialize(defn, view, prng)
kernels = ['crf'] + \
runner.second_dp_hp_kernel_config(defn) + \
runner.base_dp_hp_kernel_config(defn)
r = runner.runner(defn, view, latent, kernels)
r.run(prng, 1)
def test_runner_second_dp_valid():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
prng = rng()
latent = model.initialize(defn, data, prng)
old_beta = latent.beta
old_gamma = latent.gamma
kernels = ['crf'] + \
runner.second_dp_hp_kernel_config(defn)
r = runner.runner(defn, data, latent, kernels)
r.run(prng, 10)
assert_almost_equals(latent.beta, old_beta)
assert_almost_equals(latent.gamma, old_gamma)
assert latent.alpha > 0
def test_serialize_pickle():
N, V = 10, 20
defn = model_definition(N, V)
data = toy_dataset(defn)
view = data
prng = rng()
s = initialize(defn, view, prng)
# Pickle
bstr = pickle.dumps(s)
s2 = pickle.loads(bstr)
assert s2.__class__ == s.__class__
# cPickle
bstr = cPickle.dumps(s)
s2 = cPickle.loads(bstr)
assert s2.__class__ == s.__class__
def test_explicit():
N, V = 5, 100
defn = model_definition(N, V)
data = toy_dataset(defn)
view = numpy_dataview(data)
R = rng()
table_assignments = [
np.random.randint(low=0, high=10, size=len(d)) for d in data]
dish_assignments = [
np.random.randint(low=0, high=len(t)) for t in table_assignments]
s = initialize(defn, view, R,
table_assignments=table_assignments,
dish_assignments=dish_assignments)
assert_equals(s.nentities(), len(data))
def test_explicit():
N, V = 5, 100
defn = model_definition(N, V)
data = toy_dataset(defn)
view = numpy_dataview(data)
R = rng()
table_assignments = [
np.random.randint(low=0, high=10, size=len(d)) for d in data
]
dish_assignments = [
np.random.randint(low=0, high=len(t)) for t in table_assignments
]
s = initialize(defn,
view,
R,
table_assignments=table_assignments,
dish_assignments=dish_assignments)
assert_equals(s.nentities(), len(data))
