v0.13.17

Flux v0.13.17

Diff since v0.13.16

Closed issues:

• Metal GPU acceleration on Apple Silicon (#1304)
• Docs Revamp (#2174)
• Add Tutorial Image Segmentation using Metalhead's UNet (#2192)
• Flux.state binding does not exist (#2256)
• "failed to start primary task" with Julia 1.9 and nthreads(:interactive) > 0 (#2257)
• Error message (#2259)
• GPU/CUDA memory leak (#2261)

Merged pull requests:

• [CI] Separate julia-nightly from common matrix generator (#2254) (@skyleaworlder)
• Bump thollander/actions-comment-pull-request from 2.3.1 to 2.4.0 (#2264) (@dependabot[bot])
• add outdated version banner to the docs (#2267) (@CarloLucibello)
• initial Metal support (#2270) (@CarloLucibello)

v0.13.16

Flux v0.13.16

Diff since v0.13.15

Closed issues:

• Failed to precompile Flux (#2231)
• need help from an expert (#2233)
• Conv layer throws TaskFailedException when internal parameters are BigFloat (#2243)
• Code block in documentation not rendering properly (#2248)
• Regularisation looks to slow down gradient function by factor 500 (#2253)

Merged pull requests:

• Add EmbeddingBag (#2031) (@mcognetta)
• Remove greek-letter keyword arguments (#2139) (@mcabbott)
• Speed-up normalization layers (#2220) (@pxl-th)
• Print the state of Dropout etc. (#2222) (@mcabbott)
• Float32 warning bug fix (#2226) (@ashwani-rathee)
• Remove type restrictions for recurrent cells (#2234) (@darsnack)
• Fix Conv transfer to AMDGPU (#2235) (@pxl-th)
• add Flux.state(x) (#2239) (@CarloLucibello)
• fix perf issue loadmodel! (#2241) (@CarloLucibello)
• gpu(::DataLoader), take III (#2245) (@mcabbott)
• Update NEWS (#2247) (@mcabbott)
• fix indent in recurrent.jl (#2249) (@mcabbott)
• rm StatsBase (#2251) (@mcabbott)
• Remove greek-letter keyword from normalise (#2252) (@mcabbott)

v0.13.15

Flux v0.13.15

Diff since v0.13.14

Closed issues:

• MethodError from show on custom layer, using @functor with no fields (#2208)
• Simple L2 regularisation with Flux.params excruciatingly slow (#2211)
• Quick start tutorial doesn't work; Flux.setup not defined (#2217)
• Migrating to new explicit-style Flux (#2221)
• should f16,f32, ... convert integer or boolean arrays? (#2225)
• Creation of Adversarial Examples (#2229)

Merged pull requests:

• Add a logistic regression example to the Getting Started section (#2021) (@Saransh-cpp)
• MultiHeadAttention implementation (#2146) (@CarloLucibello)
• Use consistent spelling for optimise (#2203) (@jeremiahpslewis)
• Fix a bug in show (#2210) (@mcabbott)
• Create dependabot.yml (#2212) (@CarloLucibello)
• Bump thollander/actions-comment-pull-request from 1.0.1 to 2.3.1 (#2213) (@dependabot[bot])
• manual gradient checks for RNN - implicit and explicit gradients (#2215) (@jeremiedb)
• doc entry for MultiHeadAttention (#2218) (@CarloLucibello)
• fix some documenter warnings (#2219) (@CarloLucibello)
• example code have a little mistake (#2223) (@jaco267)
• Update 2020-09-15-deep-learning-flux.md (#2224) (@natema)
• Fix link to ParameterSchedulers.jl docs (#2227) (@white-alistair)
• f16,f32,.. don't convert int arrays + handle complex (#2228) (@CarloLucibello)
• doc: Syntax in GAN tutorial (#2230) (@musoke)

v0.13.14

Flux v0.13.14

Diff since v0.13.13

Closed issues:

• loadmodel! example in the docs doesn't work (#2191)
• ConvTranspose can cause Julia crash on GPU (#2193)
• Flattern removal (#2195)
• Flux v0.13.13 gpu crashes (#2199)
• FLux and Lux upon using: ERROR: LoadError: ArgumentError: invalid version string: local (#2202)
• UndefVarError: #flatten not defined with existing model (#2204)

Merged pull requests:

• Add AMDGPU extension (#2189) (@pxl-th)
• fixed BSON loadmodel! documentation and added a test case (#2194) (@jonathanBieler)
• reintroduce flatten (#2196) (@CarloLucibello)
• fix various deprecation warnings (#2197) (@ExpandingMan)
• CompatHelper: add new compat entry for Preferences at version 1, (keep existing compat) (#2198) (@github-actions[bot])
• reintegrate has_cudnn check (#2200) (@CarloLucibello)
• remove comment on not importing losses in Flux's namespace (#2201) (@CarloLucibello)
• dummy implementation of flatten (#2205) (@CarloLucibello)
• tiny change to docstring of gpu function (#2206) (@GSmithApps)

v0.13.13

Flux v0.13.13

Diff since v0.13.12

Closed issues:

• Normalization layers promote eltype (#1562)
• Recurrent cell eltype restriction breaks outputsize (#1565)
• Performance regression with graph neural networks (#1577)
• Opaque error caused by Float64 input to RNN (#1972)
• Binding Flux.setup does not exist (#2169)
• Un-intended behaviour? Should Flux be able to reduce StaticArrays? (#2180)
• Custom model can not be trained (#2187)

Merged pull requests:

• Match layer output to weights (#2156) (@mcabbott)
• Add friendly size check (#2176) (@mcabbott)
• Add f16 (#2184) (@mcabbott)
• remove Flux.flatten in favor of MLUtils.flatten (#2188) (@CarloLucibello)

v0.13.12

Flux v0.13.12

Diff since v0.13.11

Closed issues:

• Delta neural networks inference (#2129)
• [Bug] Embedding forward pass breaks for onehotbatch with multiple batch dimensions (#2160)
• MethodError: no method matching when training LSTMs even when loss function is working corrently (#2168)
• Type instability with Flux.update! when loss function involves extra arguments (#2175)

Merged pull requests:

• Un-deprecate track_stats for InstanceNorm (#2149) (@ToucheSir)
• Move dropout to NNlib (#2150) (@mcabbott)
• Use NNlib's within_gradient (#2152) (@mcabbott)
• Export rand32 and friends (#2157) (@mcabbott)
• Remove piratical array conversion rule (#2167) (@ToucheSir)
• update: actions node 12 => node 16 (#2173) (@skyleaworlder)
• cuda 4.0 compat (#2177) (@CarloLucibello)

v0.13.11

Flux v0.13.11

Diff since v0.13.10

Closed issues:

• Deprecate track_stats=true for GroupNorm and InstanceNorm (#2006)
• cpu(x) errors for x isa CuArray{<:CartesianIndex} (#2116)
• Constructing a Chain from a dictionary (#2142)
• Method error when using Flux.setup with Embedding layer (#2144)
• Method Error when using Flux.withgradient (#2148)

Merged pull requests:

• fix cpu(x) for immutable arrays (#2117) (@CarloLucibello)
• Fix two bugs re setup (#2145) (@mcabbott)
• CompatHelper: bump compat for MLUtils to 0.4, (keep existing compat) (#2147) (@github-actions[bot])

v0.13.10

Flux v0.13.10

Diff since v0.13.9

Closed issues:

• remove Bors (#1843)
• Only generate and upload coverage for one matrix entry (#1939)
• [Discussion]: Revamped Getting Started guide (#2012)
• Using users provided weight matrix to build LSTM layers (#2130)

Merged pull requests:

• Re-write training docs (#2114) (@mcabbott)
• Move doc sections to "guide" + "reference" (#2115) (@mcabbott)
• Allow ForwardDiff in BatchNorm's track_stats (#2127) (@mcabbott)
• Fix last block in quickstart.md (#2131) (@simonschnake)
• Delete bors.toml (#2133) (@CarloLucibello)
• Docs for onecold (#2134) (@nathanielvirgo)
• [ISSUE 1939] Update workflow, to only generate coverage for a specific entry (#2136) (@skyleaworlder)

v0.13.9

Flux v0.13.9

Diff since v0.13.8

Closed issues:

• Iteration over params(m) in explicit mode gives no gradient (#2091)
• Flux.Optimise.update! updating grads instead of params? (#2121)
• Flux.reset! triggers a BoundsError (#2124)

Merged pull requests:

• Remove train! from quickstart example (#2110) (@mcabbott)
• Re-organise "built-in layers" section (#2112) (@mcabbott)
• Narrower version of @non_differentiable params (#2118) (@mcabbott)
• allow non-tuple data in the new train! (#2119) (@CarloLucibello)
• fix train! test (#2123) (@CarloLucibello)
• Move 5 tutorials from fluxml.github.io (#2125) (@mcabbott)
• Remove Flux.Data module (#2126) (@mcabbott)
• CompatHelper: bump compat for Functors to 0.4, (keep existing compat) (#2128) (@github-actions[bot])

v0.13.8

Flux v0.13.8

Diff since v0.13.7

Closed issues:

• using Flux is broken on the Julia nightly (#2097)
• Chain(Parallel(...), ...) (#2100)
• Apparent memory leak when using Distributed? (#2102)
• [API] Preventing errors from misplaced optimizer objects (#2106)

Merged pull requests:

• Safer gradients (by copying before mutating) & less piracy (by removing ArrayInterface) (#2098) (@mcabbott)
• Allow OneHotArrays.jl v0.2 (#2109) (@mcabbott)