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REFACTOR: Sequential Dataset & DataLoader #873
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if field != self.uid_field and field + list_suffix in l1_inter_dict: | ||
candidate_field_set.add(field) | ||
new_dict[field] = torch.cat([self.inter_feat[field], l1_inter_dict[field + list_suffix][:,0]]) | ||
elif (not field.endswith(list_suffix)) and (field != self.item_list_length_field): |
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能满足这个条件的只有uid field吧
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或许 target item 的其他 feature 也可以满足?
@@ -43,6 +43,7 @@ normalize_field: ~ | |||
normalize_all: ~ | |||
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# Sequential Model Needed | |||
augmentation: False |
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所以这个参数还要保留吗?
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Got it, thanks!
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