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Fix the padding used in stable diffusion. (#362)

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This commit is contained in:
Laurent Mazare
2023-08-09 14:23:59 +02:00
committed by GitHub
parent 9c4cf6804b
commit be21d7e75a
2 changed files with 4 additions and 5 deletions
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4
candle-examples/examples/stable-diffusion/clip.rs
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@ -31,7 +31,7 @@ pub struct Config {
intermediate_size: usize, intermediate_size: usize,
pub max_position_embeddings: usize, pub max_position_embeddings: usize,
// The character to use for padding, use EOS when not set. // The character to use for padding, use EOS when not set.
pad_with: Option<String>, pub pad_with: Option<String>,
num_hidden_layers: usize, num_hidden_layers: usize,
num_attention_heads: usize, num_attention_heads: usize,
#[allow(dead_code)] #[allow(dead_code)]
@ -257,7 +257,7 @@ impl ClipEncoder {
fn forward(&self, xs: &Tensor, causal_attention_mask: &Tensor) -> Result<Tensor> { fn forward(&self, xs: &Tensor, causal_attention_mask: &Tensor) -> Result<Tensor> {
let mut xs = xs.clone(); let mut xs = xs.clone();
for layer in self.layers.iter() { for layer in self.layers.iter() {
xs = layer.forward(&xs, causal_attention_mask)? xs = layer.forward(&xs, causal_attention_mask)?;
} }
Ok(xs) Ok(xs)
} }

5
candle-examples/examples/stable-diffusion/main.rs
View File

@ -181,8 +181,8 @@ fn run(args: Args) -> Result<()> {
let device = candle_examples::device(cpu)?; let device = candle_examples::device(cpu)?;
let tokenizer = Tokenizer::from_file(tokenizer).map_err(E::msg)?; let tokenizer = Tokenizer::from_file(tokenizer).map_err(E::msg)?;
let pad_id = match tokenizer.get_padding() { let pad_id = match &sd_config.clip.pad_with {
Some(padding) => padding.pad_id, Some(padding) => *tokenizer.get_vocab(true).get(padding.as_str()).unwrap(),
None => *tokenizer.get_vocab(true).get("<|endoftext|>").unwrap(), None => *tokenizer.get_vocab(true).get("<|endoftext|>").unwrap(),
}; };
println!("Running with prompt \"{prompt}\"."); println!("Running with prompt \"{prompt}\".");
@ -212,7 +212,6 @@ fn run(args: Args) -> Result<()> {
let uncond_embeddings = text_model.forward(&uncond_tokens)?; let uncond_embeddings = text_model.forward(&uncond_tokens)?;
let text_embeddings = Tensor::cat(&[uncond_embeddings, text_embeddings], 0)?; let text_embeddings = Tensor::cat(&[uncond_embeddings, text_embeddings], 0)?;
println!("text-embeddings: {text_embeddings:?}");
println!("Building the autoencoder."); println!("Building the autoencoder.");
let vae = sd_config.build_vae(&vae_weights, &device)?; let vae = sd_config.build_vae(&vae_weights, &device)?;
println!("Building the unet."); println!("Building the unet.");