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75 lines
2.1 KiB
C++
75 lines
2.1 KiB
C++
// Copyright © 2023-2024 Apple Inc.
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#include "mlx/allocator.h"
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#include "mlx/backend/cpu/copy.h"
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#include "mlx/backend/cpu/lapack.h"
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#include "mlx/linalg.h"
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#include "mlx/primitives.h"
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namespace mlx::core {
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void cholesky_impl(const array& a, array& factor, bool upper) {
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// Lapack uses the column-major convention. We take advantage of the fact that
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// the matrix should be symmetric:
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// (A)ᵀ = A
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// and that a column-major lower triangular matrix is a row-major upper
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// triangular matrix, so uplo is the opposite of what we would expect from
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// upper
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char uplo = (upper) ? 'L' : 'U';
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// The decomposition is computed in place, so just copy the input to the
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// output.
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copy(
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a,
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factor,
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a.flags().row_contiguous ? CopyType::Vector : CopyType::General);
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const int N = a.shape(-1);
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const size_t num_matrices = a.size() / (N * N);
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float* matrix = factor.data<float>();
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for (int i = 0; i < num_matrices; i++) {
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// Compute Cholesky factorization.
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int info;
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MLX_LAPACK_FUNC(spotrf)
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(
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/* uplo = */ &uplo,
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/* n = */ &N,
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/* a = */ matrix,
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/* lda = */ &N,
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/* info = */ &info);
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// TODO: We do nothing when the matrix is not positive semi-definite
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// because throwing an error would result in a crash. If we figure out how
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// to catch errors from the implementation we should throw.
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if (info < 0) {
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std::stringstream msg;
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msg << "[cholesky] Cholesky decomposition failed with error code "
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<< info;
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throw std::runtime_error(msg.str());
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}
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// Zero out the upper/lower triangle while advancing the pointer to the
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// next matrix at the same time.
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for (int row = 0; row < N; row++) {
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if (upper) {
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std::fill(matrix, matrix + row, 0);
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} else {
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std::fill(matrix + row + 1, matrix + N, 0);
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}
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matrix += N;
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}
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}
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}
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void Cholesky::eval_cpu(const std::vector<array>& inputs, array& output) {
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if (inputs[0].dtype() != float32) {
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throw std::runtime_error("[Cholesky::eval] only supports float32.");
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}
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cholesky_impl(inputs[0], output, upper_);
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}
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} // namespace mlx::core
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