MLX compatibility: linalg functions

Abierto
#473 4 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
30/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
python
Área
testing-qa, tooling

Línea de trabajo

Empieza ejecutando los nodos de prueba enumerados, incluidos test_cholesky, test_eigh, test_matmul, test_qr y test_vecdot, y agrupa sus fallos según correspondan a una API ausente o a un comportamiento incompatible. Usa la tabla de comparación como alcance; terminado significa que los fallos de compatibilidad de MLX indicados están resueltos y que las pruebas afectadas pasan.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

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Array API MLX Analog Status Notes Test Node Result
linalg.cholesky(x, /, *, upper=False) linalg.cholesky(a, /, *, upper: bool = False, stream=None) incompatible MLX rejects complex64 inputs and only supports float32 and float64, while the test generates supported complex inputs. test_cholesky Failed
linalg.det(x, /) linalg.det(a, /, *, stream=None) incompatible MLX does not support complex inputs; complex64 raises ValueError. test_det Failed
linalg.diagonal(x, /, *, offset=0) No MLX analog missing mlx.core.linalg has no diagonal attribute. test_diagonal Failed
linalg.eigh(x, /) linalg.eigh(a, /, *, stream=None) incompatible Multiple issues: MLX fails while generating some batched symmetric matrices due to broadcasting, rejects empty/non-square matrix cases expected by the tests, and returns a plain tuple instead of the required namedtuple with eigenvalues and eigenvectors. test_eigh Failed
linalg.eigvalsh(x, /) linalg.eigvalsh(a, /, *, stream=None) incompatible MLX fails for some batched symmetric matrices due to broadcasting and rejects empty/non-square matrix cases generated by the tests. test_eigvalsh Failed
linalg.eig(x, /) linalg.eig(a, /, *, stream=None) incompatible MLX returns a plain tuple instead of the required namedtuple with eigenvalues and eigenvectors. test_eig Failed
linalg.inv(x, /) linalg.inv(a, /, *, stream=None) incompatible MLX rejects complex64 inputs and only supports float32 and float64. test_inv Failed
linalg.matmul(x1, x2, /) No mlx.core.linalg.matmul analog missing mlx.core.linalg has no matmul attribute. test_linalg_matmul Failed
matmul(x1, x2, /) matmul(a, b, /, *, stream=None) incompatible MLX rejects integer inputs such as uint16, requiring inexact/floating-point result types. test_matmul Failed
linalg.matrix_norm(x, /, *, keepdims=False, ord="fro") No MLX analog missing mlx.core.linalg has no matrix_norm attribute. test_matrix_norm Failed
linalg.matrix_power(x, n, /) No MLX analog missing mlx.core.linalg has no matrix_power attribute. test_matrix_power Failed
linalg.matrix_rank(x, /, *, rtol=None) No MLX analog missing mlx.core.linalg has no matrix_rank attribute. test_matrix_rank Failed
linalg.matrix_transpose(x, /) No mlx.core.linalg.matrix_transpose analog missing mlx.core.linalg has no matrix_transpose attribute. test_linalg_matrix_transpose Failed
matrix_transpose(x, /) matrix_transpose(a, /, *, stream=None) incompatible MLX produces an incorrect output shape for empty arrays with rank greater than two; (0, 1, 1) becomes (1, 1, 0) instead of swapping only the last two axes. test_matrix_transpose Failed
linalg.outer(x1, x2, /) No MLX analog missing mlx.core.linalg has no outer attribute. test_outer Failed
linalg.pinv(x, /, *, rtol=None) linalg.pinv(a, /, *, stream=None) incompatible MLX lacks the rtol keyword and also rejects complex64 inputs, supporting only float32 and float64. test_pinv Failed
linalg.qr(x, /, *, mode="reduced") linalg.qr(a, /, *, stream=None) incompatible MLX lacks the mode keyword, returns a plain tuple instead of a namedtuple with Q and R, and rejects complex64 inputs. test_qr Failed
linalg.slogdet(x, /) linalg.slogdet(a, /, *, stream=None) incompatible MLX returns a plain tuple instead of the required namedtuple with sign and logabsdet, and does not support complex inputs. test_slogdet Failed
linalg.solve(x1, x2, /) linalg.solve(a, b, /, *, stream=None) incompatible MLX fails on an empty-array case with a take_along_axis dimension mismatch. test_solve Failed
linalg.svd(x, /, *, full_matrices=True) linalg.svd(a, compute_uv: bool = True, *, stream=None) incompatible MLX exposes compute_uv instead of the Array API's full_matrices keyword and returns a plain tuple instead of a namedtuple with U, S, and Vh. test_svd Failed
linalg.svdvals(x, /) No MLX analog missing mlx.core.linalg has no svdvals attribute. test_svdvals Failed
linalg.tensordot(x1, x2, /, *, axes=2) No mlx.core.linalg.tensordot analog missing mlx.core.linalg has no tensordot attribute. test_linalg_tensordot Failed
tensordot(x1, x2, /, *, axes=2) tensordot(a, b, /, *, axes=2, stream=None) incompatible MLX fails for integer inputs because its implementation reaches matmul, which only supports inexact/floating-point types. test_tensordot Failed
linalg.trace(x, /, *, offset=0, dtype=None) No MLX analog missing mlx.core.linalg has no trace attribute. test_trace Failed
linalg.vecdot(x1, x2, /, *, axis=-1) No mlx.core.linalg.vecdot analog missing mlx.core.linalg has no vecdot attribute. test_linalg_vecdot Failed
vecdot(x1, x2, /, *, axis=-1) vecdot(a, b, /, *, axis=-1, stream=None) incompatible MLX produces an incorrect promoted dtype for mixed integer inputs: uint8 and uint16 produce uint32, while the expected dtype is uint16. test_vecdot Failed
linalg.vecdot(x1, x2, /, *, axis=-1) No mlx.core.linalg.vecdot analog missing mlx.core.linalg.vecdot is missing, so the required conjugating vecdot behavior cannot be tested. test_vecdot_conj Failed
linalg.vector_norm(x, /, *, axis=None, keepdims=False, ord=2) No MLX analog missing mlx.core.linalg has no vector_norm attribute. test_vector_norm Failed
Lenguaje dominante
Python
Estrellas
131
Forks
49
Merge medio
2 d 8 h
PR fusionados (30 d)
6

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