v0.14.25

Flux v0.14.25

Diff since v0.14.24

Merged pull requests:

• reintroduce FluxCUDAAdaptor etc.. to smooth out the transition (#2512) (@CarloLucibello)

v0.14.24

Flux v0.14.24

Diff since v0.14.23

Merged pull requests:

• deprecate properly GPU_BACKEND (#2511) (@CarloLucibello)

v0.14.23

Flux v0.14.23

Diff since v0.14.22

Merged pull requests:

• Support for lecun normal weight initialization (#2311) (@RohitRathore1)
• Some small printing upgrades (#2344) (@mcabbott)
• simplify test machinery (#2498) (@CarloLucibello)
• Correct dead link for "quickstart page" in README.md (#2499) (@zengmao)
• make gpu(x) = gpu_device()(x) (#2502) (@CarloLucibello)
• some cleanup (#2503) (@CarloLucibello)
• unbreak some data movement cuda tests (#2504) (@CarloLucibello)

Closed issues:

• Add support for lecun normal weight initialization (#2290)
• using Flux, cuDNN freezes, but using Flux, CUDA, cuDNN works (#2346)
• Problem with RNN and CUDA. (#2352)
• since new version: Flux throws error when for train! / update! even on quick start problem (#2358)
• Cannot take gradient of L2 regularization loss (#2441)
• Potential bug of RNN training flow (#2455)
• Problem with documentation (#2485)
• Flux has no Lecun Normalization weight init function? (#2491)
• Zygote fails to differentiate through Flux.params on julia v0.11 (#2497)
• ERROR: UndefVarError: ADAM not defined in Main in flux (#2507)

v0.14.22

Flux v0.14.22

Diff since v0.14.21

Merged pull requests:

• Bump actions/checkout from 4.2.0 to 4.2.1 (#2489) (@dependabot[bot])
• handle data movement with MLDataDevices.jl (#2492) (@CarloLucibello)
• remove some v0.13 deprecations (#2493) (@CarloLucibello)

Closed issues:

• use MLDataDevices.jl? (#2482)
• The dependency error about Flux->FluxMPIExt occurs when updating to Julia 1.11 (#2490)

v0.14.21

Flux v0.14.21

Diff since v0.14.20

Merged pull requests:

• Update ci.yml for macos-latest to use aarch64 (#2481) (@ViralBShah)
• Remove leading empty line in example (#2486) (@blegat)
• Bump actions/checkout from 4.1.7 to 4.2.0 (#2487) (@dependabot[bot])
• fix: CUDA package optional for FluxMPIExt (#2488) (@askorupka)

v0.14.20

Flux v0.14.20

Diff since v0.14.19

Merged pull requests:

• feat: Distributed data parallel training support (#2464) (@askorupka)
• Run Enzyme tests only on CUDA CI machine (#2478) (@pxl-th)
• Adapt to pending Enzyme breaking change (#2479) (@wsmoses)
• Update TagBot.yml (#2480) (@ViralBShah)
• Bump patch version (#2483) (@wsmoses)

v0.14.19

Flux v0.14.19

Diff since v0.14.18

Merged pull requests:

• Allow loading of ConvTranspose state without .outpad field (#2477) (@mcabbott)

Closed issues:

• Model saved under Flux v0.14.16 does not load on v0.14.17 (#2476)

v0.14.18

Flux v0.14.18

Diff since v0.14.17

Merged pull requests:

• Bump deps (#2475) (@pxl-th)

v0.14.17

Flux v0.14.17

Diff since v0.14.16

Merged pull requests:

• Add Enzyme train function (#2446) (@wsmoses)
• Bump actions/checkout from 4.1.5 to 4.1.7 (#2460) (@dependabot[bot])
• Add output padding for ConvTranspose (#2462) (@guiyrt)
• Fix ConvTranspose symmetric non-constant padding (#2463) (@paulnovo)
• CompatHelper: add new compat entry for Enzyme at version 0.12, (keep existing compat) (#2466) (@github-actions[bot])
• move enzyme to extension (#2467) (@CarloLucibello)
• Fix function _size_check() (#2472) (@gruberchr)
• Fix ConvTranspose output padding on AMDGPU (#2473) (@paulnovo)

Closed issues:

• Hoping to offer a version without cuda (#2155)
• ConvTranspose errors with symmetric non-constant pad (#2424)
• Create a flag to use Enzyme as the AD in training/etc. (#2443)
• Can't load a Fluxml trained & saved model. Getting ERROR: CUDA error: invalid device context (code 201, ERROR_INVALID_CONTEXT) (#2461)
• Requires deprecated cuNN.jl package (#2470)

v0.14.16

Flux v0.14.16

Diff since v0.14.15

Merged pull requests:

• Make sure first example in Custom Layers docs uses type parameter (#2415) (@BioTurboNick)
• Add GPU GC comment to Performance Tips (#2416) (@BioTurboNick)
• Fix some typos in docs (#2418) (@JoshuaLampert)
• fix component arrays test (#2419) (@CarloLucibello)
• Bump julia-actions/setup-julia from 1 to 2 (#2420) (@dependabot[bot])
• documentation update (#2422) (@CarloLucibello)
• remove public dropout (#2423) (@mcabbott)
• Allow BatchNorm on CUDA with track_stats=False (#2427) (@paulnovo)
• Bump actions/checkout from 4.1.2 to 4.1.3 (#2428) (@dependabot[bot])
• Add working downloads badge (#2429) (@pricklypointer)
• Bump actions/checkout from 4.1.3 to 4.1.4 (#2430) (@dependabot[bot])
• Add tip for non-CUDA users (#2434) (@micahscopes)
• Add hint for choosing a different GPU backend (#2435) (@micahscopes)
• Patch Flux._isleaf for abstract arrays with bitstype elements (#2436) (@jondeuce)
• Bump julia-actions/cache from 1 to 2 (#2437) (@dependabot[bot])
• Bump actions/checkout from 4.1.4 to 4.1.5 (#2438) (@dependabot[bot])
• Enzyme: bump version and mark models as working [test] (#2439) (@wsmoses)
• Enable remaining enzyme test (#2442) (@wsmoses)
• Bump AMDGPU to 0.9 (#2449) (@pxl-th)
• Do not install all GPU backends at once (#2453) (@pxl-th)
• CompatHelper: add new compat entry for BSON at version 0.3, (keep existing compat) (#2457) (@github-actions[bot])
• remove BSON dependence (#2458) (@CarloLucibello)

Closed issues:

• How to have a stable GPU memory while being performant? (#780)
• Why is Flux.destructure type unstable? (#2405)
• tests are failing due to ComponentArrays (#2411)
• Significant time spent moving medium-size arrays to GPU, type instability (#2414)
• Dense layers with shared parameters (#2432)
• why is my withgradient type unstable ? (#2456)