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Add small API changes and more test cases

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This commit is contained in:
blackfly
2020-04-11 14:28:22 +02:00
parent da3b0cc262
commit 1ec7bd261b
3 changed files with 144 additions and 55 deletions
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135
tests/test_modules.py
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@@ -16,19 +16,19 @@ class TestPrototypes(unittest.TestCase):
self.y = torch.tensor([0, 0, 1, 1])
self.gen = torch.manual_seed(42)
def test_addprototypes1d_init_without_input_dim(self):
def test_prototypes1d_init_without_input_dim(self):
with self.assertRaises(NameError):
_ = prototypes.AddPrototypes1D(nclasses=1)
_ = prototypes.Prototypes1D(nclasses=1)
def test_addprototypes1d_init_without_nclasses(self):
def test_prototypes1d_init_without_nclasses(self):
with self.assertRaises(NameError):
_ = prototypes.AddPrototypes1D(input_dim=1)
_ = prototypes.Prototypes1D(input_dim=1)
def test_addprototypes1d_init_without_pdist(self):
p1 = prototypes.AddPrototypes1D(input_dim=6,
nclasses=2,
prototypes_per_class=4,
prototype_initializer='ones')
def test_prototypes1d_init_without_pdist(self):
p1 = prototypes.Prototypes1D(input_dim=6,
nclasses=2,
prototypes_per_class=4,
prototype_initializer='ones')
protos = p1.prototypes
actual = protos.detach().numpy()
desired = torch.ones(8, 6)
@@ -37,11 +37,11 @@ class TestPrototypes(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
def test_addprototypes1d_init_without_data(self):
def test_prototypes1d_init_without_data(self):
pdist = [2, 2]
p1 = prototypes.AddPrototypes1D(input_dim=3,
prototype_distribution=pdist,
prototype_initializer='zeros')
p1 = prototypes.Prototypes1D(input_dim=3,
prototype_distribution=pdist,
prototype_initializer='zeros')
protos = p1.prototypes
actual = protos.detach().numpy()
desired = torch.zeros(4, 3)
@@ -50,23 +50,20 @@ class TestPrototypes(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
# def test_addprototypes1d_init_torch_pdist(self):
# pdist = torch.tensor([2, 2])
# p1 = prototypes.AddPrototypes1D(input_dim=3,
# prototype_distribution=pdist,
# prototype_initializer='zeros')
# protos = p1.prototypes
# actual = protos.detach().numpy()
# desired = torch.zeros(4, 3)
# mismatch = np.testing.assert_array_almost_equal(actual,
# desired,
# decimal=5)
# self.assertIsNone(mismatch)
def test_prototypes1d_proto_init_without_data(self):
with self.assertWarns(Warning):
_ = prototypes.Prototypes1D(
input_dim=3,
nclasses=2,
prototypes_per_class=1,
prototype_initializer='stratified_mean',
data=None)
def test_addprototypes1d_init_with_ppc(self):
p1 = prototypes.AddPrototypes1D(data=[self.x, self.y],
prototypes_per_class=2,
prototype_initializer='zeros')
def test_prototypes1d_init_torch_pdist(self):
pdist = torch.tensor([2, 2])
p1 = prototypes.Prototypes1D(input_dim=3,
prototype_distribution=pdist,
prototype_initializer='zeros')
protos = p1.prototypes
actual = protos.detach().numpy()
desired = torch.zeros(4, 3)
@@ -75,10 +72,68 @@ class TestPrototypes(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
def test_addprototypes1d_init_with_pdist(self):
p1 = prototypes.AddPrototypes1D(data=[self.x, self.y],
prototype_distribution=[6, 9],
prototype_initializer='zeros')
def test_prototypes1d_init_without_inputdim_with_data(self):
_ = prototypes.Prototypes1D(nclasses=1,
prototypes_per_class=1,
prototype_initializer='stratified_mean',
data=[[[1.]], [1]])
def test_prototypes1d_init_with_int_data(self):
_ = prototypes.Prototypes1D(nclasses=1,
prototypes_per_class=1,
prototype_initializer='stratified_mean',
data=[[[1]], [1]])
def test_prototypes1d_init_with_int_dtype(self):
with self.assertRaises(RuntimeError):
_ = prototypes.Prototypes1D(
nclasses=1,
prototypes_per_class=1,
prototype_initializer='stratified_mean',
data=[[[1]], [1]],
dtype=torch.int32)
def test_prototypes1d_inputndim_with_data(self):
with self.assertRaises(AssertionError):
_ = prototypes.Prototypes1D(input_dim=1,
nclasses=1,
prototypes_per_class=1,
data=[[1.], [1]])
def test_prototypes1d_inputdim_with_data(self):
with self.assertRaises(AssertionError):
_ = prototypes.Prototypes1D(
input_dim=2,
nclasses=1,
prototypes_per_class=1,
prototype_initializer='stratified_mean',
data=[[[1.]], [1]])
def test_prototypes1d_nclasses_with_data(self):
with self.assertRaises(AssertionError):
_ = prototypes.Prototypes1D(
input_dim=1,
nclasses=1,
prototypes_per_class=1,
prototype_initializer='stratified_mean',
data=[[[1.], [2.]], [1, 2]])
def test_prototypes1d_init_with_ppc(self):
p1 = prototypes.Prototypes1D(data=[self.x, self.y],
prototypes_per_class=2,
prototype_initializer='zeros')
protos = p1.prototypes
actual = protos.detach().numpy()
desired = torch.zeros(4, 3)
mismatch = np.testing.assert_array_almost_equal(actual,
desired,
decimal=5)
self.assertIsNone(mismatch)
def test_prototypes1d_init_with_pdist(self):
p1 = prototypes.Prototypes1D(data=[self.x, self.y],
prototype_distribution=[6, 9],
prototype_initializer='zeros')
protos = p1.prototypes
actual = protos.detach().numpy()
desired = torch.zeros(15, 3)
@@ -87,14 +142,14 @@ class TestPrototypes(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
def test_addprototypes1d_func_initializer(self):
def test_prototypes1d_func_initializer(self):
def my_initializer(*args, **kwargs):
return torch.full((2, 99), 99), torch.tensor([0, 1])
p1 = prototypes.AddPrototypes1D(input_dim=99,
nclasses=2,
prototypes_per_class=1,
prototype_initializer=my_initializer)
p1 = prototypes.Prototypes1D(input_dim=99,
nclasses=2,
prototypes_per_class=1,
prototype_initializer=my_initializer)
protos = p1.prototypes
actual = protos.detach().numpy()
desired = 99 * torch.ones(2, 99)
@@ -103,8 +158,8 @@ class TestPrototypes(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
def test_addprototypes1d_forward(self):
p1 = prototypes.AddPrototypes1D(data=[self.x, self.y])
def test_prototypes1d_forward(self):
p1 = prototypes.Prototypes1D(data=[self.x, self.y])
protos, _ = p1()
actual = protos.detach().numpy()
desired = torch.ones(2, 3)