T-GRU about trunet

[AmosCch]

是的，按说这里应该再transpose一下，并且GRU的定义里应该要加上batch_first=True

[YangangCao]

T-GRU和F-GRU的输入shape好像是一样的，所以这里怎么提现这个T-GRU？

不一样，你打印一下看看

[YangangCao]

是的，按说这里应该再transpose一下，并且GRU的定义里应该要加上batch_first=True

不明白为什么要transpose，烦请赐教，确实要加batch_first=True，感谢提醒

[AmosCch]

是的，按说这里应该再transpose一下，并且GRU的定义里应该要加上batch_first=True

不明白为什么要transpose，烦请赐教，确实要加batch_first=True，感谢提醒
应该不需要transpose，我理解错了，我以为(1,4,257)中的4是时间帧，感谢提醒。

[atabakp]

The shape of TGRU's input(x9) is (Time, 16, 64). Since it should aggregate the information along the time-axis and batch_first=True in your implementation, therefore the input of TGRU should have "Time" should be the second dimension.
Or set the batch_first=False for the TGRU.

[amirpashamobinitehrani]

@atabakp thanks for the useful info! Do you have any insights regarding the data input shape? seems to be a bit confusing. Referring to this thread here: #5 (comment)