Add NGen3 #36901
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Add NGen3 #36901
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@ArthurZucker and @Rocketknight1 |
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| class Block(nn.Module): | ||
| def __init__(self, config: NGEN3Config): | ||
| super().__init__() | ||
| self.ln1 = nn.LayerNorm(config.n_embd) | ||
| self.attn = CausalSelfAttention(config) | ||
| self.ln2 = nn.LayerNorm(config.n_embd) | ||
| self.mlp = MoEMLP(config) if config.use_moe else MLP(config) | ||
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| def forward(self, x: torch.Tensor) -> torch.Tensor: | ||
| # Residual connection for attention | ||
| residual = x | ||
| x = self.ln1(x) | ||
| x = self.attn(x) | ||
| x = residual + x | ||
| # Residual connection for feedforward | ||
| residual = x | ||
| x = self.ln2(x) | ||
| x = self.mlp(x) | ||
| return residual + x |
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can you try to align variable names / layer names with LlamaDecoderLayer here?
| x = self.mlp(x) | ||
| return residual + x | ||
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| class CausalSelfAttention(nn.Module): |
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this should be completely equivalent to a variation of LlamaAttention with fused qkv. Nothing very new and the mask should not be saved there
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@Thishyaketh we need a proper description of the PR with:
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This PR Fixes Issues in uploading NGen 3 to Transformers