Skip to content

Make Inception V3 torch-scriptable #2976

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 3 commits into from
Nov 9, 2020
Merged

Make Inception V3 torch-scriptable #2976

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
c7fe6e1
Making quantized inception torchscriptable.
datumbox Nov 9, 2020
e30eac0
Adding a test.
datumbox Nov 9, 2020
c2c1c2f
Fix mypy warning.
datumbox Nov 9, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 12 additions & 0 deletions test/test_models.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -339,6 +339,18 @@ def get_gn(num_channels):
self.assertFalse(any(isinstance(x, nn.BatchNorm2d) for x in model.modules()))
self.assertTrue(any(isinstance(x, nn.GroupNorm) for x in model.modules()))

def test_inceptionv3_eval(self):
# replacement for models.inception_v3(pretrained=True) that does not download weights
kwargs = {}
kwargs['transform_input'] = True
kwargs['aux_logits'] = True
kwargs['init_weights'] = False
model = models.Inception3(**kwargs)
model.aux_logits = False
model.AuxLogits = None
m = torch.jit.script(model.eval())
self.checkModule(m, "inception_v3", torch.rand(1, 3, 299, 299))

def test_fasterrcnn_double(self):
model = models.detection.fasterrcnn_resnet50_fpn(num_classes=50, pretrained_backbone=False)
model.double()
Expand Down
12 changes: 6 additions & 6 deletions torchvision/models/inception.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@ def inception_v3(pretrained: bool = False, progress: bool = True, **kwargs: Any)
model.load_state_dict(state_dict)
if not original_aux_logits:
model.aux_logits = False
del model.AuxLogits
model.AuxLogits = None
return model

return Inception3(**kwargs)
Expand Down Expand Up @@ -108,6 +108,7 @@ def __init__(
self.Mixed_6c = inception_c(768, channels_7x7=160)
self.Mixed_6d = inception_c(768, channels_7x7=160)
self.Mixed_6e = inception_c(768, channels_7x7=192)
self.AuxLogits: Optional[nn.Module] = None
if aux_logits:
self.AuxLogits = inception_aux(768, num_classes)
self.Mixed_7a = inception_d(768)
Expand Down Expand Up @@ -170,11 +171,10 @@ def _forward(self, x: Tensor) -> Tuple[Tensor, Optional[Tensor]]:
# N x 768 x 17 x 17
x = self.Mixed_6e(x)
# N x 768 x 17 x 17
aux_defined = self.training and self.aux_logits
if aux_defined:
aux = self.AuxLogits(x)
else:
aux = None
aux = torch.jit.annotate(Optional[Tensor], None)
if self.AuxLogits is not None:
if self.training:
aux = self.AuxLogits(x)
# N x 768 x 17 x 17
x = self.Mixed_7a(x)
# N x 1280 x 8 x 8
Expand Down
4 changes: 2 additions & 2 deletions torchvision/models/quantization/inception.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ def inception_v3(pretrained=False, progress=True, quantize=False, **kwargs):
if quantize:
if not original_aux_logits:
model.aux_logits = False
del model.AuxLogits
model.AuxLogits = None
model_url = quant_model_urls['inception_v3_google' + '_' + backend]
else:
model_url = inception_module.model_urls['inception_v3_google']
Expand All @@ -80,7 +80,7 @@ def inception_v3(pretrained=False, progress=True, quantize=False, **kwargs):
if not quantize:
if not original_aux_logits:
model.aux_logits = False
del model.AuxLogits
model.AuxLogits = None
return model


Expand Down