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This enables running ProstT5's (https://huggingface.co/Rostlab/ProstT5) encoder-only mode in Candle. This ProstT5 mode stores it's embed_tokens weights within the encoder, as its decoding stage was replaced with a CNN. You could write more, like: This alone is not sufficient to run ProstT5 within Candle examples. We will develop a ProstT5 runner outside candle for now, but would be willing to upstream it to candle-examples at a later point.

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This commit is contained in:
Victor-Mihaila
2024-04-12 02:57:28 +09:00
parent f65f69c977
commit d886d3ce5e
1 changed files with 4 additions and 2 deletions
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6
candle-transformers/src/models/t5.rs
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@ -183,7 +183,7 @@ impl Module for T5LayerNorm {
let xs_f32 = xs.to_dtype(DType::F32)?; let xs_f32 = xs.to_dtype(DType::F32)?;
// variance = hidden_states.to(torch.float32).pow(2).mean(-1, keepdim=True) // variance = hidden_states.to(torch.float32).pow(2).mean(-1, keepdim=True)
let variance = xs_f32.sqr()?.mean_keepdim(D::Minus1)?; let variance = xs_f32.sqr()?.mean_keepdim(D::Minus1)?;
let xs = xs_f32.broadcast_div(&(variance + self.variance_epsilon)?.sqrt()?)?; let xs = xs.broadcast_div(&(variance + self.variance_epsilon)?.sqrt()?)?;
let xs = xs.to_dtype(dtype)?; let xs = xs.to_dtype(dtype)?;
let xs = xs.broadcast_mul(&self.weight)?; let xs = xs.broadcast_mul(&self.weight)?;
Ok(xs) Ok(xs)
@ -709,8 +709,10 @@ impl T5EncoderModel {
pub fn load(vb: VarBuilder, cfg: &Config) -> Result<Self> { pub fn load(vb: VarBuilder, cfg: &Config) -> Result<Self> {
let shared_vb = if vb.contains_tensor("shared.weight") { let shared_vb = if vb.contains_tensor("shared.weight") {
vb.pp("shared") vb.pp("shared")
} else { } else if vb.contains_tensor("decoder.embed_tokens") {
vb.pp("decoder").pp("embed_tokens") vb.pp("decoder").pp("embed_tokens")
} else {
vb.pp("encoder").pp("embed_tokens")
}; };
let shared = Embedding::new(cfg.vocab_size, cfg.d_model, shared_vb)?; let shared = Embedding::new(cfg.vocab_size, cfg.d_model, shared_vb)?;
let shared = Arc::new(shared); let shared = Arc::new(shared);