Add the upblocks. (#853)

candle-core/src/lib.rs

@@ -110,7 +110,7 @@ impl ToUsize2 for (usize, usize) {
 }
 
 // A simple trait defining a module with forward method using a single argument.
-pub trait Module: std::fmt::Debug {
+pub trait Module {
     fn forward(&self, xs: &Tensor) -> Result<Tensor>;
 }
 
@@ -119,3 +119,9 @@ impl Module for quantized::QMatMul {
         self.forward(xs)
     }
 }
+
+impl<T: Fn(&Tensor) -> Result<Tensor>> Module for T {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        self(xs)
+    }
+}

candle-nn/src/ops.rs

@@ -44,6 +44,10 @@ pub fn sigmoid(xs: &Tensor) -> Result<Tensor> {
     (xs.neg()?.exp()? + 1.0)?.recip()
 }
 
+pub fn leaky_relu(xs: &Tensor, negative_slope: f64) -> Result<Tensor> {
+    xs.relu()?.minimum(&(xs * negative_slope)?)
+}
+
 pub fn dropout(xs: &Tensor, drop_p: f32) -> Result<Tensor> {
     // This implementation is inefficient as it stores the full mask for the backward pass.
     // Instead we could just store the seed and have a specialized kernel that would both

candle-transformers/src/models/wuerstchen/diffnext.rs

@@ -161,8 +161,57 @@ impl WDiffNeXt {
             down_blocks.push(down_block)
         }
 
-        // TODO: populate.
+        let mut up_blocks = Vec::with_capacity(C_HIDDEN.len());
-        let up_blocks = Vec::with_capacity(C_HIDDEN.len());
+        for (i, &c_hidden) in C_HIDDEN.iter().enumerate().rev() {
+            let vb = vb.pp("up_blocks").pp(i);
+            let mut sub_blocks = Vec::with_capacity(BLOCKS[i]);
+            let mut layer_i = 0;
+            for j in 0..BLOCKS[i] {
+                let c_skip = if INJECT_EFFNET[i] { c_cond } else { 0 };
+                let c_skip_res = if i < BLOCKS.len() - 1 && j == 0 {
+                    c_hidden + c_skip
+                } else {
+                    c_skip
+                };
+                let res_block = ResBlockStageB::new(c_hidden, c_skip_res, 3, vb.pp(layer_i))?;
+                layer_i += 1;
+                let ts_block = TimestepBlock::new(c_hidden, c_r, vb.pp(layer_i))?;
+                layer_i += 1;
+                let attn_block = if j == 0 {
+                    None
+                } else {
+                    let attn_block =
+                        AttnBlock::new(c_hidden, c_cond, NHEAD[i], true, vb.pp(layer_i))?;
+                    layer_i += 1;
+                    Some(attn_block)
+                };
+                let sub_block = SubBlock {
+                    res_block,
+                    ts_block,
+                    attn_block,
+                };
+                sub_blocks.push(sub_block)
+            }
+            let (layer_norm, conv, start_layer_i) = if i > 0 {
+                let layer_norm = WLayerNorm::new(C_HIDDEN[i - 1], vb.pp(layer_i))?;
+                layer_i += 1;
+                let cfg = candle_nn::Conv2dConfig {
+                    stride: 2,
+                    ..Default::default()
+                };
+                let conv = candle_nn::conv2d(C_HIDDEN[i - 1], c_hidden, 2, cfg, vb.pp(layer_i))?;
+                layer_i += 1;
+                (Some(layer_norm), Some(conv), 2)
+            } else {
+                (None, None, 0)
+            };
+            let up_block = UpBlock {
+                layer_norm,
+                conv,
+                sub_blocks,
+            };
+            up_blocks.push(up_block)
+        }
 
         let clf_ln = WLayerNorm::new(C_HIDDEN[0], vb.pp("clf.0"))?;
         let clf_conv = candle_nn::conv2d(

candle-transformers/src/models/wuerstchen/prior.rs

@@ -85,10 +85,9 @@ impl WPrior {
     pub fn forward(&self, xs: &Tensor, r: &Tensor, c: &Tensor) -> Result<Tensor> {
         let x_in = xs;
         let mut xs = xs.apply(&self.projection)?;
-        // TODO: leaky relu
         let c_embed = c
             .apply(&self.cond_mapper_lin1)?
-            .relu()?
+            .apply(&|xs: &_| candle_nn::ops::leaky_relu(xs, 0.2))?
             .apply(&self.cond_mapper_lin2)?;
         let r_embed = self.gen_r_embedding(r)?;
         for block in self.blocks.iter() {