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@ -115,17 +115,24 @@ class ParallelEmbedding(nn.Module):
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Raises:
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Raises:
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ValueError: If `world_size` is not defined.
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ValueError: If `world_size` is not defined.
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"""
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"""
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if world_size > 1:
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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if self.world_size < 1:
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raise ValueError("world_size must be >= 1")
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if self.world_size == 1:
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return F.embedding(x, self.weight)
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# For world_size > 1
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mask = (x < self.vocab_start_idx) | (x >= self.vocab_end_idx)
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mask = (x < self.vocab_start_idx) | (x >= self.vocab_end_idx)
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x = x - self.vocab_start_idx
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x = x - self.vocab_start_idx
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x[mask] = 0
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x[mask] = 0
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y = F.embedding(x, self.weight)
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y = F.embedding(x, self.weight)
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if world_size > 1:
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y[mask] = 0
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y[mask] = 0
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dist.all_reduce(y)
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dist.all_reduce(y)
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return y
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return y
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def linear(x: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None) -> torch.Tensor:
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def linear(x: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None) -> torch.Tensor:
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"""
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"""
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Applies a linear transformation to the incoming data: y = xA^T + b.
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Applies a linear transformation to the incoming data: y = xA^T + b.
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