diff --git a/src/error.rs b/src/error.rs
index 7a3b9960..31bcf4c3 100644
--- a/src/error.rs
+++ b/src/error.rs
@@ -90,6 +90,9 @@ pub enum Error {
     /// I/O error.
     #[error(transparent)]
     Io(#[from] std::io::Error),
+
+    #[error("cannot broadcast {src_shape:?} to {dst_shape:?}")]
+    BroadcastIncompatibleShapes { src_shape: Shape, dst_shape: Shape },
 }
 
 pub type Result<T> = std::result::Result<T, Error>;
diff --git a/src/tensor.rs b/src/tensor.rs
index 5d883329..fb8c0960 100644
--- a/src/tensor.rs
+++ b/src/tensor.rs
@@ -605,8 +605,8 @@ impl Tensor {
             storage: Arc::new(self.storage.try_clone()?),
             shape: self.shape.clone(),
             stride: self.stride.clone(),
-            op: self.op.clone(),
-            is_variable: self.is_variable,
+            op: None, // TODO
+            is_variable: false,
         };
         Ok(Tensor(Arc::new(tensor_)))
     }
@@ -654,7 +654,7 @@ impl Tensor {
                 shape: self.shape.clone(),
                 stride: self.stride.clone(),
                 op,
-                is_variable: self.is_variable,
+                is_variable: false,
             };
             Ok(Tensor(Arc::new(tensor_)))
         }
@@ -662,28 +662,60 @@ impl Tensor {
 
     /// Returns a new tensor duplicating data from the original tensor. New dimensions are inserted
     /// on the left.
-    pub fn broadcast<S: Into<Shape>>(&self, left_shape: S) -> Result<Self> {
+    pub fn broadcast_left<S: Into<Shape>>(&self, left_shape: S) -> Result<Self> {
         let left_shape = left_shape.into();
+        let mut dims = left_shape.into_dims();
+        dims.extend(self.shape.dims());
+        self.broadcast_as(dims)
+    }
+
+    pub fn broadcast_as<S: Into<Shape>>(&self, shape: S) -> Result<Self> {
         let op = if self.track_op() {
             Some(Op::Broadcast(self.clone()))
         } else {
             None
         };
-        let mut stride = vec![0; left_shape.rank()];
-        stride.extend_from_slice(&self.stride);
-        let mut dims = left_shape.into_dims();
-        dims.extend(self.shape.dims());
+        let shape = shape.into();
+        if shape.rank() < self.rank() {
+            return Err(Error::BroadcastIncompatibleShapes {
+                src_shape: self.shape().clone(),
+                dst_shape: shape,
+            });
+        }
+        let added_dims = shape.rank() - self.rank();
+        let mut stride = vec![0; added_dims];
+        for (&dst_dim, (&src_dim, &src_stride)) in shape.dims()[added_dims..]
+            .iter()
+            .zip(self.dims().iter().zip(self.stride()))
+        {
+            let s = if dst_dim == src_dim {
+                src_stride
+            } else if src_dim != 1 {
+                return Err(Error::BroadcastIncompatibleShapes {
+                    src_shape: self.shape().clone(),
+                    dst_shape: shape,
+                });
+            } else {
+                0
+            };
+            stride.push(s)
+        }
         let tensor_ = Tensor_ {
             id: TensorId::new(),
             storage: self.storage.clone(),
-            shape: Shape::from(dims),
+            shape,
             stride,
             op,
-            is_variable: self.is_variable,
+            is_variable: false,
         };
         Ok(Tensor(Arc::new(tensor_)))
     }
 
+    /// An alias for broadcast_as.
+    pub fn expand<S: Into<Shape>>(&self, shape: S) -> Result<Self> {
+        self.broadcast_as(shape)
+    }
+
     pub fn to_dtype(&self, dtype: DType) -> Result<Self> {
         let shape = self.shape();
         let storage = self.storage.to_dtype(shape, self.stride(), dtype)?;
@@ -706,8 +738,8 @@ impl Tensor {
             Ok(from_storage(
                 storage,
                 shape.clone(),
-                self.op.clone(),
-                self.is_variable,
+                None, // TODO
+                false,
             ))
         }
     }
diff --git a/tests/tensor_tests.rs b/tests/tensor_tests.rs
index c5a332e7..1dde769a 100644
--- a/tests/tensor_tests.rs
+++ b/tests/tensor_tests.rs
@@ -144,7 +144,7 @@ fn broadcast() -> Result<()> {
     let data = &[3f32, 1., 4.];
     let tensor = Tensor::new(data, &Device::Cpu)?;
     assert_eq!(
-        tensor.broadcast((3, 1))?.to_vec3::<f32>()?,
+        tensor.broadcast_left((3, 1))?.to_vec3::<f32>()?,
         &[[[3.0, 1.0, 4.0]], [[3.0, 1.0, 4.0]], [[3.0, 1.0, 4.0]]]
     );
     Ok(())