diff --git a/openselfsup/models/byol.py b/openselfsup/models/byol.py index 823253f6..985971a6 100644 --- a/openselfsup/models/byol.py +++ b/openselfsup/models/byol.py @@ -15,9 +15,10 @@ class BYOL(nn.Module): Self-Supervised Learning (https://arxiv.org/abs/2006.07733)". Args: - backbone (nn.Module): Module of backbone ConvNet. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. + backbone (dict): Config dict for module of backbone ConvNet. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. base_momentum (float): The base momentum coefficient for the target network. Default: 0.996. diff --git a/openselfsup/models/classification.py b/openselfsup/models/classification.py index 721f40b0..f19b6038 100644 --- a/openselfsup/models/classification.py +++ b/openselfsup/models/classification.py @@ -14,9 +14,9 @@ class Classification(nn.Module): """Simple image classification. Args: - backbone (nn.Module): Module of backbone ConvNet. + backbone (dict): Config dict for module of backbone ConvNet. with_sobel (bool): Whether to apply a Sobel filter on images. Default: False. - head (nn.Module): Module of loss functions. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. """ diff --git a/openselfsup/models/deepcluster.py b/openselfsup/models/deepcluster.py index b5f5cd8a..e68a73b5 100644 --- a/openselfsup/models/deepcluster.py +++ b/openselfsup/models/deepcluster.py @@ -18,10 +18,11 @@ class DeepCluster(nn.Module): of Visual Features (https://arxiv.org/abs/1807.05520)". Args: - backbone (nn.Module): Module of backbone ConvNet. + backbone (dict): Config dict for module of backbone ConvNet. with_sobel (bool): Whether to apply a Sobel filter on images. Default: False. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. """ diff --git a/openselfsup/models/moco.py b/openselfsup/models/moco.py index b3e8fc87..6ce83d6f 100644 --- a/openselfsup/models/moco.py +++ b/openselfsup/models/moco.py @@ -17,9 +17,10 @@ class MOCO(nn.Module): "https://github.com/facebookresearch/moco/blob/master/moco/builder.py". Args: - backbone (nn.Module): Module of backbone ConvNet. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. + backbone (dict): Config dict for module of backbone ConvNet. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. queue_len (int): Number of negative keys maintained in the queue. Default: 65536. diff --git a/openselfsup/models/npid.py b/openselfsup/models/npid.py index a61ed92b..0203919d 100644 --- a/openselfsup/models/npid.py +++ b/openselfsup/models/npid.py @@ -15,10 +15,11 @@ class NPID(nn.Module): Instance Discrimination (https://arxiv.org/abs/1805.01978)". Args: - backbone (nn.Module): Module of backbone ConvNet. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. - memory_bank (nn.Module): Module of memory banks. + backbone (dict): Config dict for module of backbone ConvNet. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. + memory_bank (dict): Config dict for module of memory banks. Default: None. neg_num (int): Number of negative samples for each image. Default: 65536. ensure_neg (bool): If False, there is a small probability that negative samples contain positive ones. Default: False. diff --git a/openselfsup/models/odc.py b/openselfsup/models/odc.py index 9acc6332..34c03c53 100644 --- a/openselfsup/models/odc.py +++ b/openselfsup/models/odc.py @@ -17,11 +17,12 @@ class ODC(nn.Module): (https://arxiv.org/abs/2006.10645)". Args: - backbone (nn.Module): Module of backbone ConvNet. + backbone (dict): Config dict for module of backbone ConvNet. with_sobel (bool): Whether to apply a Sobel filter on images. Default: False. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. - memory_bank (nn.Module): Module of memory banks. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. + memory_bank (dict): Module of memory banks. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. """ diff --git a/openselfsup/models/relative_loc.py b/openselfsup/models/relative_loc.py index 56d23fc6..173eb7c2 100644 --- a/openselfsup/models/relative_loc.py +++ b/openselfsup/models/relative_loc.py @@ -15,9 +15,10 @@ class RelativeLoc(nn.Module): by Context Prediction (https://arxiv.org/abs/1505.05192)". Args: - backbone (nn.Module): Module of backbone ConvNet. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. + backbone (dict): Config dict for module of backbone ConvNet. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. """ diff --git a/openselfsup/models/rotation_pred.py b/openselfsup/models/rotation_pred.py index e1cd844f..59049aa8 100644 --- a/openselfsup/models/rotation_pred.py +++ b/openselfsup/models/rotation_pred.py @@ -15,8 +15,8 @@ class RotationPred(nn.Module): by Predicting Image Rotations (https://arxiv.org/abs/1803.07728)". Args: - backbone (nn.Module): Module of backbone ConvNet. - head (nn.Module): Module of loss functions. + backbone (dict): Config dict for module of backbone ConvNet. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. """ diff --git a/openselfsup/models/simclr.py b/openselfsup/models/simclr.py index c7b16587..42073596 100644 --- a/openselfsup/models/simclr.py +++ b/openselfsup/models/simclr.py @@ -16,9 +16,10 @@ class SimCLR(nn.Module): of Visual Representations (https://arxiv.org/abs/2002.05709)". Args: - backbone (nn.Module): Module of backbone ConvNet. - neck (nn.Module): Module of deep features to compact feature vectors. - head (nn.Module): Module of loss functions. + backbone (dict): Config dict for module of backbone ConvNet. + neck (dict): Config dict for module of deep features to compact feature vectors. + Default: None. + head (dict): Config dict for module of loss functions. Default: None. pretrained (str, optional): Path to pre-trained weights. Default: None. """