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More flexible matmul contiguity checks. (#1949)

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* More flexible matmul contiguity checks.

* Also relax the checks on the metal side.
This commit is contained in:
Laurent Mazare
2024-03-27 10:59:05 +01:00
committed by GitHub
parent 75b6d4b0da
commit a9abde5f93
4 changed files with 51 additions and 8 deletions
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12
candle-core/src/cuda_backend.rs
View File

@ -1651,9 +1651,11 @@ fn gemm_config<T>(
let lhs_m1 = lhs_stride[lhs_stride.len() - 1];
let lhs_m2 = lhs_stride[lhs_stride.len() - 2];
// The a tensor has dims batching, k, n (rhs)
let (lda, transa) = if rhs_m1 == 1 && rhs_m2 == n {
// We also allow for the case where the stride on the minor dimension is not as expected but
// there is a single element.
let (lda, transa) = if rhs_m1 == 1 && (rhs_m2 == n || b * k == 1) {
(n as i32, cublasOperation_t::CUBLAS_OP_N)
} else if rhs_m1 == k && rhs_m2 == 1 {
} else if (rhs_m1 == k || b * n == 1) && rhs_m2 == 1 {
(k as i32, cublasOperation_t::CUBLAS_OP_T)
} else {
Err(CudaError::MatMulNonContiguous {
@ -1663,9 +1665,11 @@ fn gemm_config<T>(
})?
};
// The b tensor has dims batching, m, k (lhs)
let (ldb, transb) = if lhs_m1 == 1 && lhs_m2 == k {
// We also allow for the case where the stride on the minor dimension is not as expected but
// there is a single element.
let (ldb, transb) = if lhs_m1 == 1 && (lhs_m2 == k || b * m == 1) {
(k as i32, cublasOperation_t::CUBLAS_OP_N)
} else if lhs_m1 == m && lhs_m2 == 1 {
} else if (lhs_m1 == m || b * k == 1) && lhs_m2 == 1 {
(m as i32, cublasOperation_t::CUBLAS_OP_T)
} else {
Err(CudaError::MatMulNonContiguous {

10
candle-core/src/tensor.rs
View File

@ -2007,6 +2007,16 @@ impl Tensor {
}
}
/// Returns a tensor that is in row major order. This always makes a copy.
pub fn force_contiguous(&self) -> Result<Tensor> {
let shape = self.shape();
let mut storage = unsafe { self.device().alloc_uninit(shape, self.dtype())? };
self.storage()
.copy_strided_src(&mut storage, 0, self.layout())?;
let op = BackpropOp::new1(self, Op::Copy);
Ok(from_storage(storage, shape.clone(), op, false))
}
/// Create a variable based on the values currently stored in a tensor. The storage is always
/// copied.
pub(crate) fn make_var(&self) -> Result<Tensor> {