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Separate TransformerEmbedding layer #33
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lgtm!
torchtrain/models/llama/model.py
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@@ -278,6 +278,40 @@ def forward(self, x): | |||
return self.w2(F.silu(self.w1(x)) * self.w3(x)) | |||
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class TransformerEmbedding(nn.Module): |
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nit: maybe call it RotaryEmbedding
as it does not only do plain embedding but also compute the freqs_cis
?
Make it easier to chop Transformer into pieces for PP
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Make it easier to chop Transformer into pieces for PP
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Avoid diverging the model structure (FQNs and checkpoint interoperability) with similar models. This reverts commit f30202c. ghstack-source-id: 9811f5fa99fdde387efe6018aa00afd28e7e923b Pull Request resolved: pytorch#214
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Make it easier to chop Transformer into pieces for PP