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Fix fp16 compatibility issues in multiple segmentation models #83

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Fix fp16 compatibility issues in multiple segmentation models #83

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2 changes: 1 addition & 1 deletion ssseg/modules/models/segmentors/idrnet/idrnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -323,7 +323,7 @@ def obtainidcontext(self, context, logits, class_relations, intervention_clsids=
cls_contexts = torch.stack(cls_contexts)
selected_class_relations = torch.cat(selected_class_relations, dim=1)
if remove_negative_cls_relation:
selected_class_relations[selected_class_relations <= 0] = -1e16
selected_class_relations[selected_class_relations <= 0] = -1e4
selected_class_relations = F.softmax(selected_class_relations, dim=1)
selected_class_relations_tmp = []
for cls_id in valid_clsids:
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2 changes: 1 addition & 1 deletion ssseg/modules/models/segmentors/isnet/semanticlevel.py
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Expand Up @@ -31,7 +31,7 @@ def forward(self, x, preds, feats_il):
inputs = x
batch_size, num_channels, h, w = x.size()
num_classes = preds.size(1)
feats_sl = torch.zeros(batch_size, h*w, num_channels).type_as(x)
feats_sl = torch.zeros(batch_size, h*w, num_channels, device=x.device, dtype=torch.float32)
for batch_idx in range(batch_size):
# (C, H, W), (num_classes, H, W) --> (H*W, C), (H*W, num_classes)
feats_iter, preds_iter = x[batch_idx], preds[batch_idx]
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