Add test for discriminator

This commit is contained in:
ebuehrle
2021-09-14 07:17:43 +02:00
parent 7eae74a7d8
commit deaef45943

View File

@@ -9,6 +9,37 @@ def test_image_concatenation():
a = torch.tensor([[0.5]]) a = torch.tensor([[0.5]])
sa = disc._concatenate(s, a) sa = disc._concatenate(s, a)
assert s.shape == (1, 5, 200, 200)
assert a.shape == (1, 1)
assert sa.shape == (1, 6, 200, 200) assert sa.shape == (1, 6, 200, 200)
assert torch.allclose(sa[:, :5], 1.0 * s) assert torch.allclose(sa[:, :5], 1.0 * s)
assert (sa[:, 5] == a).all() assert (sa[:, 5] == a.unsqueeze(-1)).all()
def test_image_concatenation3():
env = NRasterized()
disc = CnnDiscriminator(env)
s1 = env.reset()
a1 = 0.15
s2, _, _, _ = env.step(0.9)
a2 = 0.25
s3, _, _, _ = env.step(-0.9)
a3 = 0.35
s = torch.stack([
torch.tensor(s1),
torch.tensor(s2),
torch.tensor(s3)
], axis=0)
a = torch.tensor([
[a1],
[a2],
[a3],
])
sa = disc._concatenate(s, a)
assert s.shape == (3, 5, 200, 200)
assert a.shape == (3, 1)
assert sa.shape == (3, 6, 200, 200)
assert torch.allclose(sa[:, :5], 1.0 * s)
assert (sa[:, 5] == a.unsqueeze(-1)).all()