mirror of
https://github.com/ml-explore/mlx.git
synced 2025-12-16 01:49:05 +08:00
Refactor common into cpu specific and truly common (#1817)
* refactor * fix extension example * fix no-cpu
This commit is contained in:
Awni Hannun
149
mlx/backend/cpu/svd.cpp
Normal file
149
mlx/backend/cpu/svd.cpp
Normal file
@@ -0,0 +1,149 @@
|
||||
// Copyright © 2024 Apple Inc.
|
||||
|
||||
#include "mlx/allocator.h"
|
||||
#include "mlx/backend/cpu/copy.h"
|
||||
#include "mlx/backend/cpu/lapack.h"
|
||||
#include "mlx/primitives.h"
|
||||
|
||||
namespace mlx::core {
|
||||
|
||||
void svd_impl(const array& a, array& u, array& s, array& vt) {
|
||||
// Lapack uses the column-major convention. To avoid having to transpose
|
||||
// the input and then transpose the outputs, we swap the indices/sizes of the
|
||||
// matrices and take advantage of the following identity (see
|
||||
// https://math.stackexchange.com/a/30077)
|
||||
// A = UΣVᵀ
|
||||
// Aᵀ = VΣUᵀ
|
||||
// As a result some of the indices/sizes are swapped as noted above.
|
||||
|
||||
// Rows and cols of the original matrix in row-major order.
|
||||
const int M = a.shape(-2);
|
||||
const int N = a.shape(-1);
|
||||
const int K = std::min(M, N);
|
||||
|
||||
// A of shape M x N. The leading dimension is N since lapack receives Aᵀ.
|
||||
const int lda = N;
|
||||
// U of shape M x M. (N x N in lapack).
|
||||
const int ldu = N;
|
||||
// Vᵀ of shape N x N. (M x M in lapack).
|
||||
const int ldvt = M;
|
||||
|
||||
size_t num_matrices = a.size() / (M * N);
|
||||
|
||||
// lapack clobbers the input, so we have to make a copy.
|
||||
array in(a.shape(), float32, nullptr, {});
|
||||
copy(a, in, a.flags().row_contiguous ? CopyType::Vector : CopyType::General);
|
||||
|
||||
// Allocate outputs.
|
||||
u.set_data(allocator::malloc_or_wait(u.nbytes()));
|
||||
s.set_data(allocator::malloc_or_wait(s.nbytes()));
|
||||
vt.set_data(allocator::malloc_or_wait(vt.nbytes()));
|
||||
|
||||
static constexpr auto job_u = "V";
|
||||
static constexpr auto job_vt = "V";
|
||||
static constexpr auto range = "A";
|
||||
|
||||
// Will contain the number of singular values after the call has returned.
|
||||
int ns = 0;
|
||||
float workspace_dimension = 0;
|
||||
|
||||
// Will contain the indices of eigenvectors that failed to converge (not used
|
||||
// here but required by lapack).
|
||||
auto iwork = array::Data{allocator::malloc_or_wait(sizeof(int) * 12 * K)};
|
||||
|
||||
static const int lwork_query = -1;
|
||||
|
||||
static const int ignored_int = 0;
|
||||
static const float ignored_float = 0;
|
||||
|
||||
int info;
|
||||
|
||||
// Compute workspace size.
|
||||
MLX_LAPACK_FUNC(sgesvdx)
|
||||
(
|
||||
/* jobu = */ job_u,
|
||||
/* jobvt = */ job_vt,
|
||||
/* range = */ range,
|
||||
// M and N are swapped since lapack expects column-major.
|
||||
/* m = */ &N,
|
||||
/* n = */ &M,
|
||||
/* a = */ nullptr,
|
||||
/* lda = */ &lda,
|
||||
/* vl = */ &ignored_float,
|
||||
/* vu = */ &ignored_float,
|
||||
/* il = */ &ignored_int,
|
||||
/* iu = */ &ignored_int,
|
||||
/* ns = */ &ns,
|
||||
/* s = */ nullptr,
|
||||
/* u = */ nullptr,
|
||||
/* ldu = */ &ldu,
|
||||
/* vt = */ nullptr,
|
||||
/* ldvt = */ &ldvt,
|
||||
/* work = */ &workspace_dimension,
|
||||
/* lwork = */ &lwork_query,
|
||||
/* iwork = */ static_cast<int*>(iwork.buffer.raw_ptr()),
|
||||
/* info = */ &info);
|
||||
|
||||
if (info != 0) {
|
||||
std::stringstream ss;
|
||||
ss << "svd_impl: sgesvdx_ workspace calculation failed with code " << info;
|
||||
throw std::runtime_error(ss.str());
|
||||
}
|
||||
|
||||
const int lwork = workspace_dimension;
|
||||
auto scratch = array::Data{allocator::malloc_or_wait(sizeof(float) * lwork)};
|
||||
|
||||
// Loop over matrices.
|
||||
for (int i = 0; i < num_matrices; i++) {
|
||||
MLX_LAPACK_FUNC(sgesvdx)
|
||||
(
|
||||
/* jobu = */ job_u,
|
||||
/* jobvt = */ job_vt,
|
||||
/* range = */ range,
|
||||
// M and N are swapped since lapack expects column-major.
|
||||
/* m = */ &N,
|
||||
/* n = */ &M,
|
||||
/* a = */ in.data<float>() + M * N * i,
|
||||
/* lda = */ &lda,
|
||||
/* vl = */ &ignored_float,
|
||||
/* vu = */ &ignored_float,
|
||||
/* il = */ &ignored_int,
|
||||
/* iu = */ &ignored_int,
|
||||
/* ns = */ &ns,
|
||||
/* s = */ s.data<float>() + K * i,
|
||||
// According to the identity above, lapack will write Vᵀᵀ as U.
|
||||
/* u = */ vt.data<float>() + N * N * i,
|
||||
/* ldu = */ &ldu,
|
||||
// According to the identity above, lapack will write Uᵀ as Vᵀ.
|
||||
/* vt = */ u.data<float>() + M * M * i,
|
||||
/* ldvt = */ &ldvt,
|
||||
/* work = */ static_cast<float*>(scratch.buffer.raw_ptr()),
|
||||
/* lwork = */ &lwork,
|
||||
/* iwork = */ static_cast<int*>(iwork.buffer.raw_ptr()),
|
||||
/* info = */ &info);
|
||||
|
||||
if (info != 0) {
|
||||
std::stringstream ss;
|
||||
ss << "svd_impl: sgesvdx_ failed with code " << info;
|
||||
throw std::runtime_error(ss.str());
|
||||
}
|
||||
|
||||
if (ns != K) {
|
||||
std::stringstream ss;
|
||||
ss << "svd_impl: expected " << K << " singular values, but " << ns
|
||||
<< " were computed.";
|
||||
throw std::runtime_error(ss.str());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void SVD::eval_cpu(
|
||||
const std::vector<array>& inputs,
|
||||
std::vector<array>& outputs) {
|
||||
if (!(inputs[0].dtype() == float32)) {
|
||||
throw std::runtime_error("[SVD::eval] only supports float32.");
|
||||
}
|
||||
svd_impl(inputs[0], outputs[0], outputs[1], outputs[2]);
|
||||
}
|
||||
|
||||
} // namespace mlx::core
|
||||
Reference in New Issue
Block a user