Avoid duplicating the storage by refcounting it.

src/tensor.rs

@@ -17,7 +17,7 @@ impl TensorId {
 
 pub struct Tensor_ {
     id: TensorId,
-    storage: Storage,
+    storage: Arc<Storage>,
     shape: Shape,
     // The strides are given in number of elements and not in bytes.
     stride: Vec<usize>,
@@ -25,6 +25,9 @@ pub struct Tensor_ {
     is_variable: bool,
 }
 
+// Tensors are refcounted so that cloning is cheap when building the op graph.
+// Storages are also refcounted independently so that its possible to avoid
+// copying the storage for operations that only modify the shape or stride.
 #[derive(Clone)]
 pub struct Tensor(Arc<Tensor_>);
 
@@ -104,7 +107,7 @@ fn from_storage(storage: Storage, shape: Shape, op: Option<Op>, is_variable: boo
     let stride = shape.stride_contiguous();
     let tensor_ = Tensor_ {
         id: TensorId::new(),
-        storage,
+        storage: Arc::new(storage),
         shape,
         stride,
         op,
@@ -274,7 +277,7 @@ impl Tensor {
             let data = S::cpu_storage_as_slice(cpu_storage)?;
             Ok::<_, Error>(data[0])
         };
-        match &self.storage {
+        match self.storage.as_ref() {
             Storage::Cpu(cpu_storage) => from_cpu_storage(cpu_storage),
             Storage::Cuda(storage) => from_cpu_storage(&storage.to_cpu_storage()?),
         }
@@ -394,7 +397,7 @@ impl Tensor {
     /// into account so the size of the resulting buffer might be larger than the
     /// tensor number of elements.
     pub fn storage_data<S: crate::WithDType>(&self) -> Result<std::borrow::Cow<[S]>> {
-        match &self.storage {
+        match self.storage.as_ref() {
             Storage::Cpu(cpu_storage) => {
                 let slice = S::cpu_storage_as_slice(cpu_storage)?;
                 Ok(std::borrow::Cow::Borrowed(slice))
@@ -415,7 +418,7 @@ impl Tensor {
                 shape: self.shape().clone(),
             });
         }
-        match &self.storage {
+        match self.storage.as_ref() {
             Storage::Cpu(cpu_storage) => {
                 let data = S::cpu_storage_as_slice(cpu_storage)?;
                 Ok(self.strided_index().map(|i| data[i]).collect())
@@ -442,7 +445,7 @@ impl Tensor {
             assert!(src_index.next().is_none());
             Ok(rows)
         };
-        match &self.storage {
+        match self.storage.as_ref() {
             Storage::Cpu(storage) => from_cpu_storage(storage),
             Storage::Cuda(storage) => from_cpu_storage(&storage.to_cpu_storage()?),
         }
@@ -465,7 +468,7 @@ impl Tensor {
             assert!(src_index.next().is_none());
             Ok(top_rows)
         };
-        match &self.storage {
+        match self.storage.as_ref() {
             Storage::Cpu(storage) => from_cpu_storage(storage),
             Storage::Cuda(storage) => from_cpu_storage(&storage.to_cpu_storage()?),
         }
@@ -539,7 +542,7 @@ impl Tensor {
         };
         let tensor_ = Tensor_ {
             id: TensorId::new(),
-            storage: self.storage.try_clone()?,
+            storage: self.storage.clone(),
             shape: Shape::from(dims),
             stride,
             op,
@@ -557,7 +560,7 @@ impl Tensor {
     pub fn copy(&self) -> Result<Tensor> {
         let tensor_ = Tensor_ {
             id: TensorId::new(),
-            storage: self.storage.try_clone()?,
+            storage: Arc::new(self.storage.try_clone()?),
             shape: self.shape.clone(),
             stride: self.stride.clone(),
             op: self.op.clone(),
@@ -566,14 +569,12 @@ impl Tensor {
         Ok(Tensor(Arc::new(tensor_)))
     }
 
-    // TODO: Currently this duplicates the storage, the PyTorch version would share the storage,
-    // maybe we should do the same?
     /// Returns a new tensor detached from the current graph, gradient are not propagated through
     /// this new node.
     pub fn detach(&self) -> Result<Tensor> {
         let tensor_ = Tensor_ {
             id: TensorId::new(),
-            storage: self.storage.try_clone()?,
+            storage: self.storage.clone(),
             shape: self.shape.clone(),
             stride: self.stride.clone(),
             op: None,
@@ -587,7 +588,7 @@ impl Tensor {
         if self.device().same_id(device) {
             Ok(self.clone())
         } else {
-            let storage = match (&self.storage, device) {
+            let storage = match (self.storage.as_ref(), device) {
                 (Storage::Cpu(storage), Device::Cuda(cuda)) => {
                     Storage::Cuda(cuda.cuda_from_cpu_storage(storage)?)
                 }
@@ -607,7 +608,7 @@ impl Tensor {
             };
             let tensor_ = Tensor_ {
                 id: TensorId::new(),
-                storage,
+                storage: Arc::new(storage),
                 shape: self.shape.clone(),
                 stride: self.stride.clone(),
                 op,