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T-GRU #4

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shenbuguanni opened this issue Apr 24, 2022 · 6 comments
Open

T-GRU #4

shenbuguanni opened this issue Apr 24, 2022 · 6 comments

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@shenbuguanni
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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?

@AmosCch
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AmosCch commented May 23, 2022

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
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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
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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
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AmosCch commented May 25, 2022

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
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atabakp commented Jul 12, 2022

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
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@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)

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