Open
Description
Issue for tracking and coordinating mlx backend work:
mlx.math
-
fft -
fft2 -
rfft -
irfft -
stft -
istft -
logsumexpmlx - add missing convert_to_tensor #19578 -
qr -
segment_summlx - implement segment_sum and segment_max #19652 -
segment_maxmlx - implement segment_sum and segment_max #19652 -
erfinvfeat(math): support erfinv on mlx #19628
mlx.numpy
-
einsum -
bincount -
nonzero -
cross -
vdot -
nan_to_num -
copy -
roll -
medianImplementedmedian(...)function. #19568 Implement missing functions in mlx backend #19574 -
meshgridImplement missing functions in mlx backend #19574 -
conjugate -
arctan2Added arctan2 operation #19759 -
quantile -
imag -
real -
select -
argpartitionmlx - add argpartition to numpy #19680 -
slogdet -
select -
vectorize -
correlate -
diagmlx - fix diag and diagonal in numpy #19714 -
diagonalmlx - fix diag and diagonal in numpy #19714
mlx.image
-
rgb_to_grayscalemlx - add rgb_to_grayscale #19609 -
resize- mlx - image.resize addcrop_to_aspect_ratioargument #19699
mlx.nn
-
max_pool -
avg_pool -
conv -
depthwise_conv -
separable_conv -
conv_transpose -
ctc_loss
mlx.rnn
-
rnn -
lstm -
gru
mlx.linalg
-
cholesky -
det -
eig -
eigh -
inv -
lu_factor -
normmlx - add linalg.norm #19698 -
qr -
solve -
solve_triangular -
svd
mlx.core
- np.ndarray of i64 is being cast to i32 in mlx during conversion if dtype is not passed
- [BUG] mlx crashes with msg - uncaught exception of type std::invalid_argument: [Scatter::eval_gpu] Does not support int64 ml-explore/mlx#1076
- [BUG]
np.ndarrayof bfloat16 using ml_dtypes is being interpreted as complex64 ml-explore/mlx#1075 - [BUG] arithmetic operations with numpy arrays are not commutative ml-explore/mlx#1066
- [Feature] arctan2 ml-explore/mlx#1065