Individual Contributors

If you wish to be acknowledged for your contributions, please list your name with a short description of your contribution(s) below. For example:

Jane Smith: Added the foo and bar ops.

MLX was developed with contributions from the following individuals:

Nripesh Niketan: Added softsign, softmax, hardswish, logsoftmax activation functions. Added dropout3d ops. Added LogicalAnd and LogicalOR ops. Added clip_grad_norm along with tree_reduce. Added cross. Added orthogonal initializer.
Juarez Bochi: Fixed bug in cross attention.
Justin Deschenaux: Sine, Cosine, arange, randint, truncated normal, bernoulli, lion optimizer, Dropout2d, linear and logistic regression python example.
Diogo Da Cruz: Added tri, tril, triu, tensordot, inner, outer, tile, StreamContext, stream, safetensors support, einsum, and einsum_path.
Gabrijel Boduljak: Added mlx.core.linalg, implemented norm method and InstanceNorm layer. Implemented pooling layers and Upsample.
Hinrik Snær Guðmundsson: Added atleast_1d, atleast_2d, atleast_3d ops.
Luca Arnaboldi: Added Ceil and Floor ops; implemented pickling, copy and deepcopy for mlx arrays.
Brian Keene & Atila Orhon, with Argmax Inc.: Added fast.scaled_dot_product_attention
AmirHossein Razlighi: Added chaining support for some of the ops in nn.Module. Comparison works for non array objects in mlx.core.array. Exception handling for invalid operations in mlx.core.array.
Gleb Pobudzey: Added the where primitive, and groups in 1D and 2D convolutions.
Paul Paczuski: Improved stability of BCE loss calculation
Max-Heinrich Laves: Added conv_transpose1d, conv_transpose2d, and conv_transpose3d ops.
Gökdeniz Gülmez: Added the Muon (MomentUm Orthogonalized by Newton-schulz) optimizer, and the ReLU² activation function.

Organizations

MLX has received contributions from the following companies:

NVIDIA Corporation & Affiliates

Third-Party Software

MLX leverages several third-party software, listed here together with their license copied verbatim.

PocketFFT

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