coreylowman · coreylowman · Feb 21, 2023 · Feb 21, 2023
diff --git a/src/nn/activations.rs b/src/nn/activations.rs
@@ -1,6 +1,6 @@
 use crate::{gradients::Tape, shapes::*, tensor::*, tensor_ops::*};
 
-use super::module::{BuildModule, Module, NonMutableModule, ZeroSizedModule};
+use super::module::{Module, NonMutableModule, ZeroSizedModule};
 
 macro_rules! activation_impls {
     ($struct_name:ident, $func_name:ident, #[$docstring:meta]) => {
@@ -11,12 +11,6 @@ macro_rules! activation_impls {
         impl ZeroSizedModule for $struct_name {}
         impl NonMutableModule for $struct_name {}
 
-        impl<D: Device<E>, E: Dtype> BuildModule<D, E> for $struct_name {
-            fn try_build(_: &D) -> Result<Self, <D>::Err> {
-                Ok(Default::default())
-            }
-        }
-
         impl<S: Shape, E: Dtype, D: Device<E>, T: Tape<D>> Module<Tensor<S, E, D, T>>
             for $struct_name
         {
@@ -47,12 +41,6 @@ pub struct Softmax;
 impl ZeroSizedModule for Softmax {}
 impl NonMutableModule for Softmax {}
 
-impl<D: Device<E>, E: Dtype> BuildModule<D, E> for Softmax {
-    fn try_build(_: &D) -> Result<Self, <D>::Err> {
-        Ok(Default::default())
-    }
-}
-
 impl<Ax: Axes, S: Shape<LastAxis = Ax> + ReduceShape<Ax>, E: Dtype, D: Device<E>, T: Tape<D>>
     Module<Tensor<S, E, D, T>> for Softmax
 {

diff --git a/src/nn/dropout.rs b/src/nn/dropout.rs
@@ -1,6 +1,6 @@
 use crate::{gradients::*, shapes::*, tensor::Tensor, tensor_ops::*};
 
-use super::{BuildModule, Module, ModuleMut, ZeroSizedModule};
+use super::{Module, ModuleMut, ZeroSizedModule};
 
 /// Does nothing as a [Module], and calls [dropout()] as [ModuleMut] with probability `1.0 / N`.
 ///
@@ -45,12 +45,6 @@ pub struct DropoutOneIn<const N: usize>;
 
 impl<const N: usize> ZeroSizedModule for DropoutOneIn<N> {}
 
-impl<const N: usize, D: Device<E>, E: Dtype> BuildModule<D, E> for DropoutOneIn<N> {
-    fn try_build(_: &D) -> Result<Self, <D>::Err> {
-        Ok(Default::default())
-    }
-}
-
 impl<const N: usize, S: Shape, E: Dtype, D: Device<E>> Module<Tensor<S, E, D, NoneTape>>
     for DropoutOneIn<N>
 {
@@ -123,12 +117,6 @@ impl Default for Dropout {
 
 impl ZeroSizedModule for Dropout {}
 
-impl<D: Device<E>, E: Dtype> BuildModule<D, E> for Dropout {
-    fn try_build(_: &D) -> Result<Self, <D>::Err> {
-        Ok(Default::default())
-    }
-}
-
 impl<S: Shape, E: Dtype, D: Device<E>> Module<Tensor<S, E, D, NoneTape>> for Dropout {
     type Output = Tensor<S, E, D, NoneTape>;
     /// Does nothing.

diff --git a/src/nn/flatten.rs b/src/nn/flatten.rs
@@ -1,8 +1,7 @@
 #[allow(unused)]
 use crate::{gradients::Tape, shapes::*, tensor::Tensor, tensor_ops::*};
 
-#[allow(unused)]
-use super::{BuildModule, Module, NonMutableModule, ZeroSizedModule};
+use super::{NonMutableModule, ZeroSizedModule};
 
 /// **Requires Nightly** Flattens 3d tensors to 1d, and 4d tensors to 2d.
 #[derive(Default, Clone, Copy)]
@@ -11,15 +10,9 @@ pub struct Flatten2D;
 impl ZeroSizedModule for Flatten2D {}
 impl NonMutableModule for Flatten2D {}
 
-impl<D: Device<E>, E: Dtype> BuildModule<D, E> for Flatten2D {
-    fn try_build(_: &D) -> Result<Self, <D>::Err> {
-        Ok(Default::default())
-    }
-}
-
 #[cfg(feature = "nightly")]
 impl<const C: usize, const H: usize, const W: usize, D: Device<E>, E: Dtype, T: Tape<D>>
-    Module<Tensor<Rank3<C, H, W>, E, D, T>> for Flatten2D
+    super::Module<Tensor<Rank3<C, H, W>, E, D, T>> for Flatten2D
 where
     Rank3<C, H, W>: HasSameNumelAs<Rank1<{ C * H * W }>>,
 {
@@ -31,7 +24,7 @@ where
 
 #[cfg(feature = "nightly")]
 impl<const B: usize, const C: usize, const H: usize, const W: usize, D, E: Dtype, T: Tape<D>>
-    Module<Tensor<Rank4<B, C, H, W>, E, D, T>> for Flatten2D
+    super::Module<Tensor<Rank4<B, C, H, W>, E, D, T>> for Flatten2D
 where
     D: Device<E>,
     Rank4<B, C, H, W>: HasSameNumelAs<Rank2<B, { C * H * W }>>,

diff --git a/src/nn/module.rs b/src/nn/module.rs
@@ -85,6 +85,12 @@ impl<T: ZeroSizedModule + BuildModule<D, E>, D: DeviceStorage, E: Dtype> BuildOn
     type Built = T;
 }
 
+impl<E: Dtype, D: DeviceStorage, T: ZeroSizedModule> BuildModule<D, E> for T {
+    fn try_build(_: &D) -> Result<Self, <D>::Err> {
+        Ok(Default::default())
+    }
+}
+
 impl<T: ZeroSizedModule, D: DeviceStorage, E: Dtype> ResetParams<D, E> for T {
     fn try_reset_params(&mut self) -> Result<(), <D>::Err> {
         Ok(())

diff --git a/src/nn/pool2d.rs b/src/nn/pool2d.rs
@@ -1,8 +1,6 @@
 #[cfg(feature = "nightly")]
 use crate::tensor_ops::{ConstAvgPool2D, ConstMaxPool2D, ConstMinPool2D};
 
-use crate::{shapes::Dtype, tensor_ops::Device};
-
 #[allow(unused)]
 use super::{BuildModule, Module, NonMutableModule, ZeroSizedModule};
 
@@ -41,12 +39,6 @@ macro_rules! impl_pools {
         impl<const K: usize, const S: usize, const P: usize> ZeroSizedModule for $PoolTy<K, S, P> {}
         impl<const K: usize, const S: usize, const P: usize> NonMutableModule for $PoolTy<K, S, P> {}
 
-        impl<const K: usize, const S: usize, const P: usize, D: Device<E>, E: Dtype> BuildModule<D, E> for $PoolTy<K, S, P> {
-            fn try_build(_: &D) -> Result<Self, <D>::Err> {
-                Ok(Default::default())
-            }
-        }
-
         #[cfg(feature = "nightly")]
         impl<const K: usize, const S: usize, const P: usize, Img: $Trait<K, S, P>> Module<Img>
             for $PoolTy<K, S, P>

diff --git a/src/nn/pool_global.rs b/src/nn/pool_global.rs
@@ -1,6 +1,6 @@
 use crate::{gradients::*, shapes::*, tensor::*, tensor_ops::*};
 
-use super::{BuildModule, Module, NonMutableModule, ZeroSizedModule};
+use super::{Module, NonMutableModule, ZeroSizedModule};
 
 /// Applies average pooling over an entire image, fully reducing the height and width
 /// dimensions:
@@ -61,12 +61,6 @@ macro_rules! impl_pools {
         impl ZeroSizedModule for $PoolTy {}
         impl NonMutableModule for $PoolTy {}
 
-        impl<D: Device<E>, E: Dtype> BuildModule<D, E> for $PoolTy {
-            fn try_build(_: &D) -> Result<Self, <D>::Err> {
-                Ok(Default::default())
-            }
-        }
-
         impl<C: Dim, H: Dim, W: Dim, E: Dtype, D: Device<E>, T: Tape<D>>
             Module<Tensor<(C, H, W), E, D, T>> for $PoolTy
         {