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albanD wants to merge 1 commit into from
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Update torchmultimodal test golden values after trunc_normal_ change #539

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16 changes: 8 additions & 8 deletions tests/models/albef/test_albef.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,8 +82,8 @@ def albef_model_output(albef_model):
def test_albef_image_embeddings(albef_model_output):
expected = Tensor(
[
[[1.364883, -1.003092, -0.361791], [-0.634884, 1.411830, -0.776947]],
[[1.401580, -0.537510, -0.864071], [1.378901, -0.417473, -0.961429]],
[[1.337287, -0.270253, -1.067032], [1.414201, -0.705347, -0.708854]],
[[1.402044, -0.540827, -0.861216], [-1.410284, 0.613923, 0.796362]],
]
)
assert_expected(albef_model_output.image_embeddings, expected, rtol=0, atol=1e-4)
Expand All @@ -92,8 +92,8 @@ def test_albef_image_embeddings(albef_model_output):
def test_albef_image_embeddings_momentum(albef_model_output):
expected = Tensor(
[
[[1.364883, -1.003092, -0.361791], [-0.634884, 1.411830, -0.776947]],
[[1.401580, -0.537510, -0.864070], [1.378902, -0.417473, -0.961429]],
[[1.337286, -0.270253, -1.067033], [1.414201, -0.705347, -0.708854]],
[[1.402043, -0.540827, -0.861217], [-1.410284, 0.613922, 0.796362]],
]
)
assert_expected(albef_model_output.image_embeddings_m, expected, rtol=0, atol=1e-4)
Expand Down Expand Up @@ -122,8 +122,8 @@ def test_albef_text_embeddings_momentum(albef_model_output):
def test_albef_multimodal_embeddings(albef_model_output):
expected = Tensor(
[
[[-0.068738, 1.257666, -1.188928], [1.409873, -0.609056, -0.800817]],
[[-1.402520, 0.544084, 0.858435], [1.202279, -1.246038, 0.043760]],
[[1.228663, -0.007874, -1.220789], [1.401657, -0.863674, -0.537983]],
[[-1.021501, 1.357746, -0.336245], [1.409910, -0.800425, -0.609485]],
]
)
assert_expected(
Expand All @@ -134,8 +134,8 @@ def test_albef_multimodal_embeddings(albef_model_output):
def test_albef_multimodal_embeddings_momentum(albef_model_output):
expected = Tensor(
[
[[-0.068738, 1.257666, -1.188928], [1.409873, -0.609056, -0.800817]],
[[-1.402520, 0.544084, 0.858435], [1.202279, -1.246038, 0.043760]],
[[1.228662, -0.007872, -1.220790], [1.401657, -0.863674, -0.537983]],
[[-1.021501, 1.357746, -0.336245], [1.409910, -0.800426, -0.609485]],
]
)
assert_expected(
Expand Down
4 changes: 2 additions & 2 deletions tests/models/albef/test_image_encoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,8 +31,8 @@ def test_vision_transformer(self):
output = vit(input)
expected = Tensor(
[
[1.399478, -0.875986, -0.523492],
[-0.869867, 1.400589, -0.530722],
[1.407929, -0.819281, -0.588648],
[-0.692709, 1.414116, -0.721407],
]
).unsqueeze(0)
assert_expected(output, expected, rtol=0, atol=1e-4)
Expand Down
18 changes: 9 additions & 9 deletions tests/models/test_omnivore.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,19 +40,19 @@ def test_omnivore_swin_t_forward(omnivore_swin_t_model, device):

assert_expected(image_score.size(), torch.Size((1, 1000)))
assert_expected(
image_score.abs().sum(), torch.tensor(184.01417), rtol=1e-3, atol=1e-3
image_score.abs().sum(), torch.tensor(208.64470), rtol=1e-3, atol=1e-3
)

rgbd = torch.randn((1, 4, 1, 112, 112), device=device)
rgbd_score = model(rgbd, input_type="rgbd")
assert_expected(rgbd_score.size(), torch.Size((1, 19)))
assert_expected(rgbd_score.abs().sum(), torch.tensor(3.60813), rtol=1e-3, atol=1e-3)
assert_expected(rgbd_score.abs().sum(), torch.tensor(4.42536), rtol=1e-3, atol=1e-3)

video = torch.randn((1, 3, 4, 112, 112), device=device)
video_score = model(video, input_type="video")
assert_expected(video_score.size(), torch.Size((1, 400)))
assert_expected(
video_score.abs().sum(), torch.tensor(110.70048), rtol=1e-3, atol=1e-3
video_score.abs().sum(), torch.tensor(71.27126), rtol=1e-3, atol=1e-3
)


Expand All @@ -64,19 +64,19 @@ def test_omnivore_swin_s_forward(omnivore_swin_s_model, device):

assert_expected(image_score.size(), torch.Size((1, 1000)))
assert_expected(
image_score.abs().sum(), torch.tensor(239.73104), rtol=1e-3, atol=1e-3
image_score.abs().sum(), torch.tensor(215.43909), rtol=1e-3, atol=1e-3
)

rgbd = torch.randn((1, 4, 1, 112, 112), device=device)
rgbd_score = model(rgbd, input_type="rgbd")
assert_expected(rgbd_score.size(), torch.Size((1, 19)))
assert_expected(rgbd_score.abs().sum(), torch.tensor(5.80919), rtol=1e-3, atol=1e-3)
assert_expected(rgbd_score.abs().sum(), torch.tensor(4.23604), rtol=1e-3, atol=1e-3)

video = torch.randn((1, 3, 4, 112, 112), device=device)
video_score = model(video, input_type="video")
assert_expected(video_score.size(), torch.Size((1, 400)))
assert_expected(
video_score.abs().sum(), torch.tensor(136.49894), rtol=1e-3, atol=1e-3
video_score.abs().sum(), torch.tensor(136.16075), rtol=1e-3, atol=1e-3
)


Expand All @@ -88,19 +88,19 @@ def test_omnivore_swin_b_forward(omnivore_swin_b_model, device):

assert_expected(image_score.size(), torch.Size((1, 1000)))
assert_expected(
image_score.abs().sum(), torch.tensor(278.06488), rtol=1e-3, atol=1e-3
image_score.abs().sum(), torch.tensor(251.88954), rtol=1e-3, atol=1e-3
)

rgbd = torch.randn((1, 4, 1, 112, 112), device=device)
rgbd_score = model(rgbd, input_type="rgbd")
assert_expected(rgbd_score.size(), torch.Size((1, 19)))
assert_expected(rgbd_score.abs().sum(), torch.tensor(4.52186), rtol=1e-3, atol=1e-3)
assert_expected(rgbd_score.abs().sum(), torch.tensor(3.82680), rtol=1e-3, atol=1e-3)

video = torch.randn((1, 3, 4, 112, 112), device=device)
video_score = model(video, input_type="video")
assert_expected(video_score.size(), torch.Size((1, 400)))
assert_expected(
video_score.abs().sum(), torch.tensor(138.22859), rtol=1e-3, atol=1e-3
video_score.abs().sum(), torch.tensor(140.93663), rtol=1e-3, atol=1e-3
)


Expand Down
2 changes: 1 addition & 1 deletion tests/modules/encoders/test_swin_transformer_3d_encoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ def test_swin_transformer_3d_encoder(self):

scores = self.encoder(image)
self.assertEqual(scores.size(), torch.Size([1, 768]))
self.assertAlmostEqual(scores.abs().sum().item(), 247.14674, 2)
self.assertAlmostEqual(scores.abs().sum().item(), 279.50031, 2)

def test_swin_transformer_3d_scripting(self):
torch.jit.script(self.encoder)
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