def test_get_absolute(self):
self.assertEqual(Path(".").get_absolute(Path("1.2")), Path("1.2"))
self.assertEqual(
Path(".x.y").get_absolute(Path("1.2")), Path("1.2.x.y"))
self.assertEqual(
Path("..x.y").get_absolute(Path("1.2")), Path("1.x.y"))
self.assertEqual(Path("...x.y").get_absolute(Path("1.2")), Path("x.y"))
with self.assertRaises(ValueError):
Path("....x.y").get_absolute(Path("1.2"))
def test_ancestors(self):
self.assertEqual(Path("").ancestors(), {Path("")})
self.assertEqual(Path("a").ancestors(), {Path(""), Path("a")})
self.assertEqual(Path("one.two.three").ancestors(), {Path(""), Path("one"), Path("one.two"), Path("one.two.three")})
def test_add_path(self):
self.assertEqual(str(Path("one").add_path(Path("2"))), "one.2")
self.assertEqual(str(Path("one").add_path(Path("2.3"))), "one.2.3")
self.assertEqual(str(Path("").add_path(Path("2.3"))), "2.3")
self.assertEqual(str(Path("one.2").add_path(Path(""))), "one.2")
self.assertEqual(str(Path("").add_path(Path(""))), "")
self.assertEqual(str(Path(".").add_path(Path(""))), ".")
self.assertEqual(str(Path(".").add_path(Path("one.two"))), ".one.two")
self.assertEqual(str(Path(".xy").add_path(Path("one.two"))),
".xy.one.two")
with self.assertRaises(NotImplementedError):
Path("one").add_path(Path(".2.3"))
def test_set(self):
s = set([Path("one.2"), Path("one.1.3"), Path("one.1.3")])
self.assertIn(Path("one.2"), s)
self.assertEqual(len(s), 2)
def test_str(self):
self.assertEqual(str(Path("one.2")), "one.2")
self.assertEqual(str(Path("")), "")
def test_eq(self):
self.assertEqual(Path(""), Path(""))
self.assertEqual(Path(".."), Path(".."))
self.assertEqual(Path("one.2"), Path("one.2"))
self.assertEqual(Path("one.2"), Path("one.2.3").parent())
self.assertNotEqual(Path("one.2"), Path("one.2.3"))
self.assertNotEqual(Path(""), Path("."))
def __init__(
self,
layers: numbers.Integral = 1,
input_dim: numbers.Integral = Ref("exp_global.default_layer_dim"),
hidden_dim: numbers.Integral = Ref("exp_global.default_layer_dim"),
dropout: numbers.Real = Ref("exp_global.dropout", default=0.0),
weightnoise_std: numbers.Real = Ref("exp_global.weight_noise",
default=0.0),
param_init: param_initializers.ParamInitializer = Ref(
"exp_global.param_init",
default=bare(param_initializers.GlorotInitializer)),
bias_init: param_initializers.ParamInitializer = Ref(
"exp_global.bias_init",
default=bare(param_initializers.ZeroInitializer)),
yaml_path: Path = Path(),
decoder_input_dim: Optional[numbers.Integral] = Ref(
"exp_global.default_layer_dim", default=None),
decoder_input_feeding: bool = True) -> None:
self.num_layers = layers
model = param_collections.ParamManager.my_params(self)
if yaml_path is not None and "decoder" in yaml_path:
if decoder_input_feeding:
input_dim += decoder_input_dim
self.hidden_dim = hidden_dim
self.dropout_rate = dropout
self.weightnoise_std = weightnoise_std
self.input_dim = input_dim
if not isinstance(param_init, collections.abc.Sequence):
param_init = [param_init] * layers
if not isinstance(bias_init, collections.abc.Sequence):
bias_init = [bias_init] * layers
# [i; f; o; g]
self.p_Wx = [
model.add_parameters(dim=(hidden_dim * 4, input_dim),
init=param_init[0].initializer(
(hidden_dim * 4, input_dim),
num_shared=4))
]
self.p_Wx += [
model.add_parameters(dim=(hidden_dim * 4, hidden_dim),
init=param_init[i].initializer(
(hidden_dim * 4, hidden_dim),
num_shared=4)) for i in range(1, layers)
]
self.p_Wh = [
model.add_parameters(dim=(hidden_dim * 4, hidden_dim),
init=param_init[i].initializer(
(hidden_dim * 4, hidden_dim),
num_shared=4)) for i in range(layers)
]
self.p_b = [
model.add_parameters(dim=(hidden_dim * 4, ),
init=bias_init[i].initializer(
(hidden_dim * 4, ), num_shared=4))
for i in range(layers)
]
self.dropout_mask_x = None
self.dropout_mask_h = None
