Rename the .r functions to .dims so as to be a bit more explicit. (#220)

1 files changed, 6 insertions, 6 deletions

diff --git a/candle-core/src/tensor.rs b/candle-core/src/tensor.rs
index 8ba0ba43..561f1863 100644
--- a/candle-core/src/tensor.rs
+++ b/candle-core/src/tensor.rs
@@ -772,7 +772,7 @@ impl Tensor {
 
     /// Applies a 1D convolution over the input tensor.
     pub fn conv1d(&self, kernel: &Self, padding: usize, stride: usize) -> Result<Self> {
-        let (c_out, c_in_k, k_size) = kernel.shape().r3()?;
+        let (c_out, c_in_k, k_size) = kernel.dims3()?;
         let (b_size, c_in, l_in) = match *self.dims() {
             [b_size, c_in, l_in] => (Some(b_size), c_in, l_in),
             [c_in, l_in] => (None, c_in, l_in),
@@ -931,8 +931,8 @@ impl Tensor {
             .bt())?
         }
         let ids_shape = ids.shape();
-        let seq_len = ids_shape.r1()?;
-        let (_, hidden_size) = rhs.shape().r2()?;
+        let seq_len = ids_shape.dims1()?;
+        let (_, hidden_size) = rhs.dims2()?;
         let storage = ids
             .storage()
             .embedding(ids.layout(), &rhs.storage(), rhs.layout())?;
@@ -1013,7 +1013,7 @@ impl Tensor {
             // The number of element in indexes must match the dimension on which the add is
             // performed on the source tensor (and the index values from `indexes` are taken from
             // the target tensor self)
-            mismatch || source_dims[dim] != indexes.shape().r1()?
+            mismatch || source_dims[dim] != indexes.dims1()?
         };
         if mismatch {
             Err(Error::ShapeMismatchBinaryOp {
@@ -1144,7 +1144,7 @@ impl Tensor {
 
     /// Returns the data contained in a 2D tensor as a vector of vector of scalar values.
     pub fn to_vec2<S: crate::WithDType>(&self) -> Result<Vec<Vec<S>>> {
-        let (dim1, dim2) = self.shape().r2()?;
+        let (dim1, dim2) = self.dims2()?;
         let from_cpu_storage = |cpu_storage: &crate::CpuStorage| {
             let data = S::cpu_storage_as_slice(cpu_storage)?;
             let mut rows = vec![];
@@ -1164,7 +1164,7 @@ impl Tensor {
 
     /// Returns the data contained in a 3D tensor.
     pub fn to_vec3<S: crate::WithDType>(&self) -> Result<Vec<Vec<Vec<S>>>> {
-        let (dim1, dim2, dim3) = self.shape().r3()?;
+        let (dim1, dim2, dim3) = self.dims3()?;
         let from_cpu_storage = |cpu_storage: &crate::CpuStorage| {
             let data = S::cpu_storage_as_slice(cpu_storage)?;
             let mut top_rows = vec![];