chore/layer/nll: fmt, cleanup, asserts

fff-rs · Sep 12, 2022 · 290c0b7 · 290c0b7
1 parent 3da2df8
commit 290c0b7
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Showing 3 changed files with 18 additions and 19 deletions.
diff --git a/coaster/tests/shared_memory_specs.rs b/coaster/tests/shared_memory_specs.rs
@@ -2,10 +2,10 @@ use coaster as co;
 
 #[cfg(test)]
 mod shared_memory_spec {
-    use super::co::prelude::*;
-    use super::co::tensor::Error;
     #[cfg(features = "cuda")]
     use super::co::frameworks::native::flatbox::FlatBox;
+    use super::co::prelude::*;
+    use super::co::tensor::Error;
 
     #[cfg(features = "cuda")]
     fn write_to_memory<T: Copy>(mem: &mut FlatBox, data: &[T]) {

diff --git a/juice/src/layers/loss/negative_log_likelihood.rs b/juice/src/layers/loss/negative_log_likelihood.rs
@@ -166,4 +166,4 @@ impl Into<LayerType> for NegativeLogLikelihoodConfig {
     fn into(self) -> LayerType {
         LayerType::NegativeLogLikelihood(self)
     }
-}
+}
diff --git a/juice/tests/layer_specs.rs b/juice/tests/layer_specs.rs
@@ -386,8 +386,8 @@ mod layer_spec {
             .is_err());
     }
 
-    use juice::layers::SequentialConfig;
     use juice::layers::NegativeLogLikelihoodConfig;
+    use juice::layers::SequentialConfig;
 
     #[test]
     fn nll_basic() {
@@ -401,19 +401,15 @@ mod layer_spec {
         let nll_layer_cfg = NegativeLogLikelihoodConfig { num_classes: 10 };
         let nll_cfg = LayerConfig::new("nll", nll_layer_cfg);
         classifier_cfg.add_layer(nll_cfg);
-        let mut network = Layer::from_config(
-            native_backend.clone(),
-            &LayerConfig::new("foo", classifier_cfg),
-        );
-        let labels_data = (0..(BATCH_SIZE * KLASS_COUNT))
-            .into_iter()
-            .map(|x| x as f32)
-            .collect::<Vec<f32>>();
+        let mut network = Layer::from_config(native_backend.clone(), &LayerConfig::new("foo", classifier_cfg));
         let desc = [BATCH_SIZE, KLASS_COUNT];
         let desc: &[usize] = &desc[..];
         let mut input = SharedTensor::<f32>::new(&desc);
         let mem = input.write_only(native_backend.device()).unwrap();
-        let input_data = (0..(KLASS_COUNT * BATCH_SIZE)).into_iter().map(|x| x as f32 * 3.77).collect::<Vec<f32>>();
+        let input_data = (0..(KLASS_COUNT * BATCH_SIZE))
+            .into_iter()
+            .map(|x| x as f32 * 3.77)
+            .collect::<Vec<f32>>();
         let input_data = &input_data[..];
         juice::util::write_to_memory(mem, input_data);
 
@@ -435,11 +431,14 @@ mod layer_spec {
             std::sync::Arc::new(std::sync::RwLock::new(labels)),
         ];
 
-        let output = network.forward(input.as_slice());
-
-        let x = output[0].read().unwrap();
-        dbg!(&x);
-        let out = x.read(native_backend.device()).unwrap();
-        dbg!(out.as_slice::<f32>());
+        let out = network.forward(input.as_slice());
+        assert_eq!(out.len(), 1);
+        let out = &out[0];
+        let out = out.read().unwrap();
+        assert_eq!(out.desc().dims(), &vec![BATCH_SIZE, 1]);
+        let out = out.read(native_backend.device()).unwrap();
+        let out_mem = out.as_slice::<f32>();
+        assert_eq!(out_mem.len(), BATCH_SIZE);
+        assert!(out_mem[0] < 0_f32);
     }
 }