H3 / LongConvKernel - l_max=None isn't working

[grazder]

In H3 model here noted that

safari/src/models/sequence/h3_conv.py

Line 36 in 1ff064e

l_max: the maximum kernel length, also denoted by L. Set l_max=None to always use a global kernel

But it isn't working, because of

safari/src/models/sequence/long_conv_kernel.py

Line 56 in 1ff064e

return torch.randn(self.channels, self.H, self.L) * 0.002

Which is leading to torch.randn(int, int, None) error:

TypeError: randn(): argument 'size' must be tuple of ints, but found element of type NoneType at pos 3

So, are global kernels supported now? Or, to make it more global, should I use large l_max value?

[DanFu09]

The H3Conv replaces the SSM with a fixed-length long convolution the size of the input, so you need to set the l_max. The SSM version of H3 has no fixed context length, so that’s why it’s not necessary for that case.

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On Thu, Mar 9, 2023 at 9:08 AM Alexey Korepanov ***@***.***> wrote: In H3 model here noted that https://github.com/HazyResearch/safari/blob/1ff064eb43a455e217449314dfbbd83dcac7871c/src/models/sequence/h3_conv.py#L36 But it isn't working, because of https://github.com/HazyResearch/safari/blob/1ff064eb43a455e217449314dfbbd83dcac7871c/src/models/sequence/long_conv_kernel.py#L56 Which is leading to torch.randn(int, int, None) error: TypeError: randn(): argument 'size' must be tuple of ints, but found element of type NoneType at pos 3 So, are global kernels supported now? Or, to make it more global, should I use the large l_max value? — Reply to this email directly, view it on GitHub <#2>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABDDIISS53RDBV3INEJGOATW3HI3HANCNFSM6AAAAAAVVDARFQ> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[grazder]

ok thank!
it would be clearer if there was an assert or something like that.
this would be helpful for users like me who use just the model implementation without any other framework things

[DanFu09]

Thanks, this feedback makes sense! Will add some more notes and documentation next week (currently traveling).

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On Thu, Mar 9, 2023 at 4:04 PM Alexey Korepanov ***@***.***> wrote: ok, it would be clearer if there was an assert or something like that. this would be helpful for users like me who use just the model implementation without any other framework things — Reply to this email directly, view it on GitHub <#2 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABDDIITA4YQFTXTWTM2FXKTW3IZWJANCNFSM6AAAAAAVVDARFQ> . You are receiving this because you commented.Message ID: ***@***.***>