Fix model initialization bugs

src/bin/sample/main.rs

@@ -61,7 +61,6 @@ fn main() {
             process::exit(1);
         })
     };
-    
      
     let sd = sd.to_device(&device);
 

src/model/autoencoder/mod.rs

@@ -348,6 +348,7 @@ pub struct PaddedConv2d<B: Backend> {
 
 impl<B: Backend> PaddedConv2d<B> {
     fn forward(&self, x: Tensor<B, 4>) -> Tensor<B, 4> {
+        println!("{} {} {:?} {:?}", self.kernel_size, self.stride, self.padding, self.padding_actual);
         let [n_batch, n_channel, height, width] = x.dims();
 
         let desired_height = (self.padding.pad_top + self.padding.pad_bottom + height - self.kernel_size) / self.stride + 1;

src/model/stablediffusion/mod.rs

@@ -114,7 +114,6 @@ impl<B: Backend> StableDiffusion<B> {
 
             let timestep = Tensor::from_ints([t as i32]).to_device(&device);
             let pred_noise = self.forward_diffuser(latent.clone(), timestep, context.clone(), unconditional_context.clone(), unconditional_guidance_scale);
-
             let predx0 = (latent - pred_noise.clone() * sqrt_noise) / current_alpha.sqrt();
             let dir_latent = pred_noise * (1.0 - prev_alpha - sigma * sigma).sqrt();
 

src/model/unet/mod.rs

@@ -369,7 +369,6 @@ pub struct UpsampleConfig {
 impl UpsampleConfig {
     fn init<B: Backend>(&self) -> Upsample<B> {
         let conv = Conv2dConfig::new([self.n_channels, self.n_channels], [3, 3])
-            .with_stride([2, 2])
             .with_padding(PaddingConfig2d::Explicit(1, 1))
             .init();
 
@@ -493,7 +492,7 @@ pub struct TransformerBlockConfig {
 impl TransformerBlockConfig {
     fn init<B: Backend>(&self) -> TransformerBlock<B> {
         let norm1 = nn::LayerNormConfig::new(self.n_state).init();
-        let attn1 = MultiHeadAttentionConfig::new(self.n_state, self.n_context_state, self.n_head).init();
+        let attn1 = MultiHeadAttentionConfig::new(self.n_state, self.n_state, self.n_head).init();
         let norm2 = nn::LayerNormConfig::new(self.n_state).init();
         let attn2 = MultiHeadAttentionConfig::new(self.n_state, self.n_context_state, self.n_head).init();
         let norm3 = nn::LayerNormConfig::new(self.n_state).init();