AttributeError: 'SqueezeExcite' object has no attribute 'gate' about face-emotion-recognition HOT 4 CLOSED

Here is the detailed error message.

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:13: DeprecationWarning: np.int is a deprecated alias for the builtin int. To silence this warning, use int by itself. Doing this will not modify any behavior and is safe. When replacing np.int, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
del sys.path[0]

AttributeError Traceback (most recent call last)
in ()
17 img_tensor = test_transforms(Image.fromarray(face_img))
18 img_tensor.unsqueeze_(0)
---> 19 scores = model(img_tensor.to(device))
20 scores=scores[0].data.cpu().numpy()
21 plt.figure(figsize=(3, 3))

11 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1108 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1109 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110 return forward_call(*input, **kwargs)
1111 # Do not call functions when jit is used
1112 full_backward_hooks, non_full_backward_hooks = [], []

/usr/local/lib/python3.7/dist-packages/timm/models/efficientnet.py in forward(self, x)
518
519 def forward(self, x):
--> 520 x = self.forward_features(x)
521 x = self.global_pool(x)
522 if self.drop_rate > 0.:

/usr/local/lib/python3.7/dist-packages/timm/models/efficientnet.py in forward_features(self, x)
511 x = self.bn1(x)
512 x = self.act1(x)
--> 513 x = self.blocks(x)
514 x = self.conv_head(x)
515 x = self.bn2(x)

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1108 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1109 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110 return forward_call(*input, **kwargs)
1111 # Do not call functions when jit is used
1112 full_backward_hooks, non_full_backward_hooks = [], []

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py in forward(self, input)
139 def forward(self, input):
140 for module in self:
--> 141 input = module(input)
142 return input
143

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1108 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1109 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110 return forward_call(*input, **kwargs)
1111 # Do not call functions when jit is used
1112 full_backward_hooks, non_full_backward_hooks = [], []

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py in forward(self, input)
139 def forward(self, input):
140 for module in self:
--> 141 input = module(input)
142 return input
143

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1108 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1109 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110 return forward_call(*input, **kwargs)
1111 # Do not call functions when jit is used
1112 full_backward_hooks, non_full_backward_hooks = [], []

/usr/local/lib/python3.7/dist-packages/timm/models/efficientnet_blocks.py in forward(self, x)
120 x = self.act1(x)
121
--> 122 x = self.se(x)
123
124 x = self.conv_pw(x)

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
1108 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1109 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1110 return forward_call(*input, **kwargs)
1111 # Do not call functions when jit is used
1112 full_backward_hooks, non_full_backward_hooks = [], []

/usr/local/lib/python3.7/dist-packages/timm/models/efficientnet_blocks.py in forward(self, x)
45 x_se = self.act1(x_se)
46 x_se = self.conv_expand(x_se)
---> 47 return x * self.gate(x_se)
48
49

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in getattr(self, name)
1184 return modules[name]
1185 raise AttributeError("'{}' object has no attribute '{}'".format(
-> 1186 type(self).name, name))
1187
1188 def setattr(self, name: str, value: Union[Tensor, 'Module']) -> None:

AttributeError: 'SqueezeExcite' object has no attribute 'gate'

from face-emotion-recognition.

Please, check that you have the timm package version 0.4.5 (see readme). They changed EfficientNet in the latest package after I trained my models

from face-emotion-recognition.

Thanks for your help, it is now up and running, thanks for the excellent work you did.

from face-emotion-recognition.

Ok, nice, I'm closing the issue

from face-emotion-recognition.