[lab4] Removed const size from Layer trait

lab4/src/algo/layer.rs

@@ -1,9 +1,9 @@
-pub trait Layer<const PrevLayerSize: usize, const CurrentLayerSize: usize> {
+pub trait Layer {
     type InputType;
     type OutputType;
 
-    fn compute(
+    fn compute(&self, input_data: &[Self::InputType], output_data: &mut [Self::OutputType]);
-        &self,
+
-        input_data: &[Self::InputType; PrevLayerSize],
+    fn input_size(&self) -> usize;
-    ) -> [Self::OutputType; CurrentLayerSize];
+    fn output_size(&self) -> usize;
-}
+}

lab4/src/algo/layer_impl.rs

@@ -1,43 +1,51 @@
 use crate::algo::layer::Layer;
-use crate::algo::net::LayersConnect;
+use crate::algo::layers_union::LayersUnion;
 use std::iter::Sum;
 use std::marker::PhantomData;
-use std::ops::{Add, Mul};
+use std::ops::Add;
 
 struct Neuron<const PrevLayerSize: usize> {
     input_weights: [f64; PrevLayerSize],
 }
 
-pub trait ApplyWeight {
+pub trait ApplyWeight<Output> {
-    type Output;
+    fn apply_weight(&self, w: f64) -> Output;
-    fn apply_weight(&self, w: f64) -> Self::Output;
+}
+
+impl ApplyWeight<f64> for f64 {
+    fn apply_weight(&self, w: f64) -> f64 {
+        return *self * w;
+    }
 }
 
 pub struct LayerImpl<
     const PrevLayerSize: usize,
     const CurrentLayerSize: usize,
-    InputType: ApplyWeight,
+    InputType: ApplyWeight<WeightedType>,
-    ActivationType: Sum<<InputType as ApplyWeight>::Output>,
+    WeightedType,
+    ActivationType: Sum<WeightedType>,
     ActivationFunction: Fn(ActivationType) -> OutputType,
     OutputType,
 > {
     neurons: [Neuron<PrevLayerSize>; CurrentLayerSize],
     activation_function: ActivationFunction,
-    __phantom: PhantomData<(InputType, ActivationType, OutputType)>,
+    __phantom: PhantomData<(InputType, WeightedType, ActivationType, OutputType)>,
 }
 
 impl<
     const PrevLayerSize: usize,
     const CurrentLayerSize: usize,
-    InputType: ApplyWeight,
+    InputType: ApplyWeight<WeightedType>,
-    ActivationType: Sum<<InputType as ApplyWeight>::Output>,
+    WeightedType,
+    ActivationType: Sum<WeightedType>,
     ActivationFunction: Fn(ActivationType) -> OutputType,
     OutputType,
-> Layer<PrevLayerSize, CurrentLayerSize>
+> Layer
     for LayerImpl<
         PrevLayerSize,
         CurrentLayerSize,
         InputType,
+        WeightedType,
         ActivationType,
         ActivationFunction,
         OutputType,
@@ -46,45 +54,49 @@ impl<
     type InputType = InputType;
     type OutputType = OutputType;
 
-    fn compute(&self, input_data: &[InputType; PrevLayerSize]) -> [OutputType; CurrentLayerSize] {
+    fn compute(&self, input_data: &[InputType], output_data: &mut [OutputType]) {
-        let mut output: [OutputType; CurrentLayerSize] =
-            std::array::from_fn(|_| unsafe { std::mem::uninitialized::<OutputType>() });
         for (i, n) in self.neurons.iter().enumerate() {
             let P = input_data
                 .iter()
                 .zip(n.input_weights)
                 .map(|(x, w)| x.apply_weight(w))
                 .sum();
-            output[i] = (self.activation_function)(P);
+            output_data[i] = (self.activation_function)(P);
         }
+    }
 
-        return output;
+    fn input_size(&self) -> usize {
+        return PrevLayerSize;
+    }
+
+    fn output_size(&self) -> usize {
+        return CurrentLayerSize;
     }
 }
 
 impl<
     const PrevPrevLayerSize: usize,
     const PrevLayerSize: usize,
-    const CurrentLayerSize: usize,
+    PrevLayerInputType: ApplyWeight<PrevLayerWeightedType>,
-    PrevLayerInputType: ApplyWeight,
+    PrevLayerWeightedType,
-    PrevLayerActivationType: Sum<<PrevLayerInputType as ApplyWeight>::Output>,
+    PrevLayerActivationType: Sum<PrevLayerWeightedType>,
     PrevLayerActivationFunction: Fn(PrevLayerActivationType) -> PrevLayerOutputType,
     PrevLayerOutputType,
-    CurrentLayer: Layer<PrevLayerSize, CurrentLayerSize, InputType = PrevLayerOutputType>,
+    CurrentLayer: Layer<InputType = PrevLayerOutputType>,
 > Add<CurrentLayer>
     for LayerImpl<
         PrevPrevLayerSize,
         PrevLayerSize,
         PrevLayerInputType,
+        PrevLayerWeightedType,
         PrevLayerActivationType,
         PrevLayerActivationFunction,
         PrevLayerOutputType,
     >
 {
-    type Output =
+    type Output = LayersUnion<Self, CurrentLayer>;
-        LayersConnect<PrevPrevLayerSize, PrevLayerSize, CurrentLayerSize, Self, CurrentLayer>;
 
     fn add(self, rhs: CurrentLayer) -> Self::Output {
-        return LayersConnect::join(self, rhs);
+        return LayersUnion::join(self, rhs);
     }
 }

lab4/src/algo/layers_union.rs

@@ -0,0 +1,67 @@
+use crate::algo::layer::Layer;
+use std::ops::Add;
+
+pub struct LayersUnion<
+    PrevLayer: Layer,
+    CurrentLayer: Layer<InputType = PrevLayer::OutputType>,
+> {
+    prev_layer: PrevLayer,
+    current_layer: CurrentLayer,
+}
+
+impl<PrevLayer: Layer, CurrentLayer: Layer<InputType = PrevLayer::OutputType>>
+    LayersUnion<PrevLayer, CurrentLayer>
+{
+    pub fn join(l1: PrevLayer, l2: CurrentLayer) -> Self {
+        assert_eq!(l1.output_size(), l2.input_size());
+        return Self {
+            prev_layer: l1,
+            current_layer: l2,
+        };
+    }
+}
+
+impl<PrevLayer: Layer, CurrentLayer: Layer<InputType = PrevLayer::OutputType>> Layer
+    for LayersUnion<PrevLayer, CurrentLayer>
+{
+    type InputType = PrevLayer::InputType;
+    type OutputType = CurrentLayer::OutputType;
+
+    fn compute(&self, input_data: &[Self::InputType], output_data: &mut [Self::OutputType]) {
+        let mut intermediate_data_s =
+            vec![0u8; self.prev_layer.output_size() * size_of::<PrevLayer::OutputType>()]
+                .into_boxed_slice();
+
+        let intermediate_data;
+        unsafe {
+            intermediate_data = std::slice::from_raw_parts_mut(
+                intermediate_data_s.as_mut_ptr().cast::<PrevLayer::OutputType>(),
+                self.prev_layer.output_size(),
+            )
+        }
+        self.prev_layer.compute(input_data, intermediate_data);
+        self.current_layer.compute(intermediate_data, output_data);
+    }
+
+    fn input_size(&self) -> usize {
+        return self.prev_layer.input_size();
+    }
+
+    fn output_size(&self) -> usize {
+        return self.current_layer.output_size();
+    }
+}
+
+impl<
+    PrevLayer: Layer,
+    CurrentLayer: Layer<InputType = PrevLayer::OutputType>,
+    NextLayer: Layer<InputType = CurrentLayer::OutputType>,
+> Add<NextLayer>
+    for LayersUnion<PrevLayer, CurrentLayer>
+{
+    type Output = LayersUnion<Self, NextLayer>;
+
+    fn add(self, rhs: NextLayer) -> Self::Output {
+        return LayersUnion::join(self, rhs);
+    }
+}

lab4/src/algo/mod.rs

@@ -1,3 +1,3 @@
 mod layer;
-mod net;
+mod layers_union;
 mod layer_impl;

lab4/src/algo/net.rs

@@ -1,74 +0,0 @@
-use crate::algo::layer::Layer;
-use std::ops::{Add};
-
-pub(super) struct LayersConnect<
-    const PrevPrevLayerSize: usize,
-    const PrevLayerSize: usize,
-    const CurrentLayerSize: usize,
-    PrevLayer: Layer<PrevPrevLayerSize, PrevLayerSize>,
-    CurrentLayer: Layer<PrevLayerSize, CurrentLayerSize, InputType = PrevLayer::OutputType>,
-> {
-    prev_layer: PrevLayer,
-    current_layer: CurrentLayer,
-}
-
-impl<
-    const PrevPrevLayerSize: usize,
-    const PrevLayerSize: usize,
-    const CurrentLayerSize: usize,
-    PrevLayer: Layer<PrevPrevLayerSize, PrevLayerSize>,
-    CurrentLayer: Layer<PrevLayerSize, CurrentLayerSize, InputType = PrevLayer::OutputType>,
-> LayersConnect<PrevPrevLayerSize, PrevLayerSize, CurrentLayerSize, PrevLayer, CurrentLayer>
-{
-    pub fn join(l1: PrevLayer, l2: CurrentLayer) -> Self {
-        return Self {
-            prev_layer: l1,
-            current_layer: l2,
-        };
-    }
-}
-
-impl<
-    const PrevPrevLayerSize: usize,
-    const PrevLayerSize: usize,
-    const CurrentLayerSize: usize,
-    PrevLayer: Layer<PrevPrevLayerSize, PrevLayerSize>,
-    CurrentLayer: Layer<PrevLayerSize, CurrentLayerSize, InputType = PrevLayer::OutputType>,
-> Layer<PrevPrevLayerSize, CurrentLayerSize>
-    for LayersConnect<PrevPrevLayerSize, PrevLayerSize, CurrentLayerSize, PrevLayer, CurrentLayer>
-{
-    type InputType = PrevLayer::InputType;
-    type OutputType = CurrentLayer::OutputType;
-
-    fn compute(
-        &self,
-        input_data: &[Self::InputType; PrevPrevLayerSize],
-    ) -> [Self::OutputType; CurrentLayerSize] {
-        let intermediate_data = self.prev_layer.compute(input_data);
-        return self.current_layer.compute(&intermediate_data);
-    }
-}
-
-impl<
-    const PrevPrevLayerSize: usize,
-    const PrevLayerSize: usize,
-    const CurrentLayerSize: usize,
-    const NextLayerSize: usize,
-    PrevLayer: Layer<PrevPrevLayerSize, PrevLayerSize>,
-    CurrentLayer: Layer<PrevLayerSize, CurrentLayerSize, InputType = PrevLayer::OutputType>,
-    NextLayer: Layer<CurrentLayerSize, NextLayerSize, InputType = CurrentLayer::OutputType>,
-> Add<NextLayer>
-    for LayersConnect<
-        PrevPrevLayerSize,
-        PrevLayerSize,
-        CurrentLayerSize,
-        PrevLayer,
-        CurrentLayer,
-    >
-{
-    type Output = LayersConnect<PrevPrevLayerSize, CurrentLayerSize, NextLayerSize, Self, NextLayer>;
-
-    fn add(self, rhs: NextLayer) -> Self::Output {
-        return LayersConnect::join(self, rhs)
-    }
-}