def forward(self, pvam_feature, gsrm_feature):
    (b, t, c1) = pvam_feature.shape
    (b, t, c2) = gsrm_feature.shape
    combine_feature_ = torch.cat([pvam_feature, gsrm_feature], dim=2)
    img_comb_feature_ = torch.reshape(combine_feature_, shape=((- 1), (c1 + c2)))
    img_comb_feature_map = self.fc0(img_comb_feature_)
    img_comb_feature_map = torch.sigmoid(img_comb_feature_map)
    img_comb_feature_map = torch.reshape(img_comb_feature_map, shape=((- 1), t, c1))
    combine_feature = ((img_comb_feature_map * pvam_feature) + ((1.0 - img_comb_feature_map) * gsrm_feature))
    img_comb_feature = torch.reshape(combine_feature, shape=((- 1), c1))
    out = self.fc1(img_comb_feature)
    return out
def forward(self, pvam_feature, gsrm_feature):
    (b, t, c1) = pvam_feature.shape
    (b, t, c2) = gsrm_feature.shape
    combine_feature_ = torch.cat([pvam_feature, gsrm_feature], dim=2)
    img_comb_feature_ = torch.reshape(combine_feature_, shape=((- 1), (c1 + c2)))
    img_comb_feature_map = self.fc0(img_comb_feature_)
    img_comb_feature_map = torch.sigmoid(img_comb_feature_map)
    img_comb_feature_map = torch.reshape(img_comb_feature_map, shape=((- 1), t, c1))
    combine_feature = ((img_comb_feature_map * pvam_feature) + ((1.0 - img_comb_feature_map) * gsrm_feature))
    img_comb_feature = torch.reshape(combine_feature, shape=((- 1), c1))
    out = self.fc1(img_comb_feature)
    return out