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It seems that the parameter initialized with **randn** (https://github.com/graykode/xlnet-Pytorch/blob/cb793a1c75bdc59e3360f04ec641af726719811f/xlnet.py#L119) will **lead to low-performance**, and I tried **xavier_norm** and **kaiming_uniform**, both reach a much higher AUC and F1 score in my...
The **continuation_indicator_layer** is used to produce one blob as the bottom input for lstm layer, and this layer used the parameter below message ContinuationIndicatorParameter { optional uint32 **time_step** = 1...
Can you share the code of your paper "Ordinal and Attribute Aware Response Generation in a Multimodal Dialogue System" published in ACL 2019.