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Abstract the implementation of Shape.

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This commit is contained in:
laurent
2023-06-22 12:39:15 +01:00
parent f052020ba2
commit 625e08d6ab
2 changed files with 19 additions and 9 deletions
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15
src/tensor.rs
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@ -283,9 +283,8 @@ impl Tensor {
});
}
let mut c_shape: Vec<_> = a_dims[..dim - 2].into();
c_shape.extend(&[m, n]);
let c_shape = Shape(c_shape);
let c_shape = Shape::from(&a_dims[..dim - 2]).extend(&[m, n]);
let c_stride = c_shape.stride_contiguous();
let batching: usize = a_dims[..dim - 2].iter().product();
let storage = self.storage.matmul_impl(
@ -297,8 +296,8 @@ impl Tensor {
let tensor_ = Tensor_ {
id: TensorId::new(),
storage,
shape: c_shape.clone(),
stride: c_shape.stride_contiguous(),
shape: c_shape,
stride: c_stride,
op: Some(Op::Matmul(self.clone(), rhs.clone())),
is_variable: false,
};
@ -414,7 +413,6 @@ impl Tensor {
pub fn t(&self) -> Result<Tensor> {
let mut stride = self.stride().to_vec();
let mut shape = self.shape().clone();
let n = stride.len();
if n < 2 {
return Err(Error::UnexpectedNumberOfDims {
@ -423,12 +421,13 @@ impl Tensor {
shape: self.shape().clone(),
});
}
(shape.0[n - 2], shape.0[n - 1]) = (shape.0[n - 1], shape.0[n - 2]);
let mut dims = self.shape().dims().to_vec();
(dims[n - 2], dims[n - 1]) = (dims[n - 1], dims[n - 2]);
(stride[n - 2], stride[n - 1]) = (stride[n - 1], stride[n - 2]);
let tensor_ = Tensor_ {
id: TensorId::new(),
storage: self.storage.clone(),
shape,
shape: Shape::from(dims),
stride,
// TODO The op should have a backward
op: None,