Lux: Explicit Parameterization of Deep Neural Networks in Julia

Lux v0.5.61

Diff since v0.5.60

Merged pull requests:

• refactor: bring Optimisers.jl into main deps (#754) (@avik-pal)
• refactor: drop the AMDGPU extension (#755) (@avik-pal)
• rearrange code in extensions (#756) (@avik-pal)
• fix: use proper qualified accesses for modules (#757) (@avik-pal)
• docs: remove redundant old preferences (#759) (@avik-pal)
• feat: allow multiple @return (#760) (@avik-pal)
• Making all eltypes Float32 in Fitting a Polynomial using MLP (#761) (@Sleort)
• docs: fix inline math rendering (#762) (@avik-pal)
• refactor: use the faster get_device_type (#763) (@avik-pal)
• refactor: move ForwardDiff.jl into main deps (#764) (@avik-pal)
• test: set st to training (#765) (@avik-pal)
• chore(deps): bump crate-ci/typos from 1.23.1 to 1.23.2 (#766) (@dependabot[bot])
• Update docstring dropout (#770) (@dmetivie)
• chore: recommend GH Discussions for Q/A (#774) (@avik-pal)

Closed issues:

• Broadcast Layer (#426)
• Add improper qualified accesses checks (#667)
• Feature request: TimeDistributed Layer (#758)