mmaction/models/recognizers/base_semi.py
def forward(self, imgs, label=None, return_loss=True, imgs_weak=None, imgs_strong=None, label_unlabeled=None, human_mask=None, imagenet_prob=None):
        """Define the computation performed at every call."""
        if return_loss:
            if label is None:
                raise ValueError('Label should not be None.')
            if imgs_weak is None or imgs_strong is None or label_unlabeled is None:
                raise ValueError('Unlabeled data should be available.')
            return self.forward_train(imgs, label, imgs_weak, imgs_strong, label_unlabeled, human_mask, imagenet_prob)
        else:
            return self.forward_test(imgs)
Define the computation performed at every call.
Define the computation performed at every call.
Define the computation performed at every call .
def forward(self, imgs, label=None, return_loss=True, imgs_weak=None, imgs_strong=None, label_unlabeled=None, human_mask=None, imagenet_prob=None):
        if return_loss:
            if label is None:
                raise ValueError('Label should not be None.')
            if imgs_weak is None or imgs_strong is None or label_unlabeled is None:
                raise ValueError('Unlabeled data should be available.')
            return self.forward_train(imgs, label, imgs_weak, imgs_strong, label_unlabeled, human_mask, imagenet_prob)
        else:
            return self.forward_test(imgs)
def forward ( self , imgs , label = None , return_loss = True , imgs_weak = None , imgs_strong = None , label_unlabeled = None , human_mask = None , imagenet_prob = None ) : if return_loss : if label is None : raise ValueError ( 'Label should not be None.' ) if imgs_weak is None or imgs_strong is None or label_unlabeled is None : raise ValueError ( 'Unlabeled data should be available.' ) return self . forward_train ( imgs , label , imgs_weak , imgs_strong , label_unlabeled , human_mask , imagenet_prob ) else : return self . forward_test ( imgs )
Define the computation performed at every call.
Define the computation performed at every call .
"""Define the computation performed at every call."""
self
imgs
label
return_loss
imgs_weak
imgs_strong
label_unlabeled
human_mask
imagenet_prob