Lux: Explicit Parameterization of Deep Neural Networks in Julia

Lux v1.13.0

Diff since v1.12.4

Merged pull requests:

• fix: try increasing the samples in CI (#1309) (@avik-pal)
• fix: restrict dispatch types for cublaslt (#1311) (@avik-pal)
• chore: bump julia-actions/julia-format from 3 to 4 (#1313) (@dependabot[bot])
• feat: use 3rd order derivatives using Reactant (#1315) (@avik-pal)
• allow SelectDim to take arbitrary views (#1318) (@ExpandingMan)
• chore: bump crate-ci/typos from 1.31.1 to 1.32.0 (#1320) (@dependabot[bot])
• docs: fix wrong function names in RNG admonition in interface.md (#1325) (@KristianHolme)
• CompatHelper: bump compat for DocumenterVitepress to 0.2 for package docs, (keep existing compat) (#1328) (@github-actions[bot])
• CompatHelper: bump compat for Interpolations to 0.16 for package CIFAR10, (keep existing compat) (#1329) (@github-actions[bot])
• docs: lstm encoder decoder using Reactant (#1331) (@avik-pal)
• feat: lower embedding to direct indexing (#1332) (@avik-pal)
• fix: indexing (#1333) (@avik-pal)

Closed issues:

• Per-Layer Profiling (#864)
• Integration of oneDNN for CPU operations (#1013)
• Convolutional VAE for MNIST using Reactant failed to produce right results (#1274)
• GPU Inefficiency in Gradient Computation with Custom Recurrence (#1284)
• dense operations fail on views on nvidia due to missing method (#1308)
• Gradient of while loop with Reactant seems broken (#1316)
• getting concatenating and splitting working with Reactant/Enzyme (#1317)
• LuxLib doing LinearAlgebra.mul! on non-arrays can cause fallback to errors (#1322)
• gpu_device(device_id) attaches to first/zeroth device regardless of device_id (#1330)