Add final latent slice checks to SD pipeline intermediate state tests (#731)

This is to ensure that the final latent slices stay somewhat consistent as more changes are introduced into the library.

Signed-off-by: James R T <[email protected]>

Signed-off-by: James R T <[email protected]>

Author: jamestiotio

tests/test_pipelines.py

@@ -1733,6 +1733,14 @@ def test_callback_fn(step: int, timestep: int, latents: torch.FloatTensor) -> No
                     [1.8285, 1.2857, -0.1024, 1.2406, -2.3068, 1.0747, -0.0818, -0.6520, -2.9506]
                 )
                 assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
+            elif step == 50:
+                latents = latents.detach().cpu().numpy()
+                assert latents.shape == (1, 4, 64, 64)
+                latents_slice = latents[0, -3:, -3:, -1]
+                expected_slice = np.array(
+                    [1.1078, 1.5803, 0.2773, -0.0589, -1.7928, -0.3665, -0.4695, -1.0727, -1.1601]
+                )
+                assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
 
         test_callback_fn.has_been_called = False
 
@@ -1773,6 +1781,12 @@ def test_callback_fn(step: int, timestep: int, latents: torch.FloatTensor) -> No
                 latents_slice = latents[0, -3:, -3:, -1]
                 expected_slice = np.array([0.9052, -0.0184, 0.4810, 0.2898, 0.5851, 1.4920, 0.5362, 1.9838, 0.0530])
                 assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
+            elif step == 37:
+                latents = latents.detach().cpu().numpy()
+                assert latents.shape == (1, 4, 64, 96)
+                latents_slice = latents[0, -3:, -3:, -1]
+                expected_slice = np.array([0.7071, 0.7831, 0.8300, 1.8140, 1.7840, 1.9402, 1.3651, 1.6590, 1.2828])
+                assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
 
         test_callback_fn.has_been_called = False
 
@@ -1823,6 +1837,12 @@ def test_callback_fn(step: int, timestep: int, latents: torch.FloatTensor) -> No
                     [-0.5472, 1.1218, -0.5505, -0.9390, -1.0794, 0.4063, 0.5158, 0.6429, -1.5246]
                 )
                 assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
+            elif step == 37:
+                latents = latents.detach().cpu().numpy()
+                assert latents.shape == (1, 4, 64, 64)
+                latents_slice = latents[0, -3:, -3:, -1]
+                expected_slice = np.array([0.4781, 1.1572, 0.6258, 0.2291, 0.2554, -0.1443, 0.7085, -0.1598, -0.5659])
+                assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
 
         test_callback_fn.has_been_called = False
 
@@ -1875,6 +1895,13 @@ def test_callback_fn(step: int, timestep: int, latents: np.ndarray) -> None:
                     [-0.5950, -0.3039, -1.1672, 0.1594, -1.1572, 0.6719, -1.9712, -0.0403, 0.9592]
                 )
                 assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
+            elif step == 5:
+                assert latents.shape == (1, 4, 64, 64)
+                latents_slice = latents[0, -3:, -3:, -1]
+                expected_slice = np.array(
+                    [-0.4776, -0.0119, -0.8519, -0.0275, -0.9764, 0.9820, -0.3843, 0.3788, 1.2264]
+                )
+                assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
 
         test_callback_fn.has_been_called = False