From 3dbd6a8f4d7f3f27df3e3433fc2ab9fe1e7a873d Mon Sep 17 00:00:00 2001 From: Patrick von Platen Date: Thu, 30 Jun 2022 14:54:31 +0000 Subject: [PATCH] up --- src/diffusers/models/resnet.py | 3 +++ tests/test_modeling_utils.py | 22 ++++++++++------------ 2 files changed, 13 insertions(+), 12 deletions(-) diff --git a/src/diffusers/models/resnet.py b/src/diffusers/models/resnet.py index 80ccdd77..58756283 100644 --- a/src/diffusers/models/resnet.py +++ b/src/diffusers/models/resnet.py @@ -207,6 +207,9 @@ class ResBlock(TimestepBlock): self.updown = up or down +# if self.updown: +# import ipdb; ipdb.set_trace() + if up: self.h_upd = Upsample(channels, use_conv=False, dims=dims) self.x_upd = Upsample(channels, use_conv=False, dims=dims) diff --git a/tests/test_modeling_utils.py b/tests/test_modeling_utils.py index 743bef0e..08d70ca5 100755 --- a/tests/test_modeling_utils.py +++ b/tests/test_modeling_utils.py @@ -259,7 +259,7 @@ class UnetModelTests(ModelTesterMixin, unittest.TestCase): # fmt: off expected_output_slice = torch.tensor([0.2891, -0.1899, 0.2595, -0.6214, 0.0968, -0.2622, 0.4688, 0.1311, 0.0053]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) class GlideSuperResUNetTests(ModelTesterMixin, unittest.TestCase): @@ -607,7 +607,7 @@ class UNetGradTTSModelTests(ModelTesterMixin, unittest.TestCase): expected_output_slice = torch.tensor([-0.0690, -0.0531, 0.0633, -0.0660, -0.0541, 0.0650, -0.0656, -0.0555, 0.0617]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) class TemporalUNetModelTests(ModelTesterMixin, unittest.TestCase): @@ -678,7 +678,7 @@ class TemporalUNetModelTests(ModelTesterMixin, unittest.TestCase): expected_output_slice = torch.tensor([-0.2714, 0.1042, -0.0794, -0.2820, 0.0803, -0.0811, -0.2345, 0.0580, -0.0584]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) class NCSNppModelTests(ModelTesterMixin, unittest.TestCase): @@ -753,7 +753,7 @@ class NCSNppModelTests(ModelTesterMixin, unittest.TestCase): expected_output_slice = torch.tensor([3.1909e-07, -8.5393e-08, 4.8460e-07, -4.5550e-07, -1.3205e-06, -6.3475e-07, 9.7837e-07, 2.9974e-07, 1.2345e-06]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) def test_output_pretrained_ve_large(self): model = NCSNpp.from_pretrained("fusing/ncsnpp-ffhq-ve-dummy") @@ -779,7 +779,7 @@ class NCSNppModelTests(ModelTesterMixin, unittest.TestCase): expected_output_slice = torch.tensor([-8.3299e-07, -9.0431e-07, 4.0585e-08, 9.7563e-07, 1.0280e-06, 1.0133e-06, 1.4979e-06, -2.9716e-07, -6.1817e-07]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) def test_output_pretrained_vp(self): model = NCSNpp.from_pretrained("fusing/ddpm-cifar10-vp-dummy") @@ -805,7 +805,7 @@ class NCSNppModelTests(ModelTesterMixin, unittest.TestCase): expected_output_slice = torch.tensor([-3.9086e-07, -1.1001e-05, 1.8881e-06, 1.1106e-05, 1.6629e-06, 2.9820e-06, 8.4978e-06, 8.0253e-07, 1.5435e-06]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) class VQModelTests(ModelTesterMixin, unittest.TestCase): @@ -878,10 +878,9 @@ class VQModelTests(ModelTesterMixin, unittest.TestCase): output_slice = output[0, -1, -3:, -3:].flatten() # fmt: off - expected_output_slice = torch.tensor([-1.1321, 0.1056, 0.3505, -0.6461, -0.2014, 0.0419, -0.5763, -0.8462, - -0.4218]) + expected_output_slice = torch.tensor([-1.1321, 0.1056, 0.3505, -0.6461, -0.2014, 0.0419, -0.5763, -0.8462, -0.4218]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) class AutoEncoderKLTests(ModelTesterMixin, unittest.TestCase): @@ -950,10 +949,9 @@ class AutoEncoderKLTests(ModelTesterMixin, unittest.TestCase): output_slice = output[0, -1, -3:, -3:].flatten() # fmt: off - expected_output_slice = torch.tensor([-0.0814, -0.0229, -0.1320, -0.4123, -0.0366, -0.3473, 0.0438, -0.1662, - 0.1750]) + expected_output_slice = torch.tensor([-0.0814, -0.0229, -0.1320, -0.4123, -0.0366, -0.3473, 0.0438, -0.1662, 0.1750]) # fmt: on - self.assertTrue(torch.allclose(output_slice, expected_output_slice, atol=1e-3)) + self.assertTrue(torch.allclose(output_slice, expected_output_slice, rtol=1e-3)) class PipelineTesterMixin(unittest.TestCase):