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CHANGELOG.md

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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

  • Tidy up cgo flags

[Nofix]

  • ctype long caused compiling error in MacOS as noted on #44. Not working on linux box.

[0.9.1]

  • [#111, #112, #113] Fixed concurrency memory leak
  • #118 Fixed incorrect cbool conversion

[0.9.0]

  • Upgrade libtorch v2.1.0

[0.8.0]

  • Upgrade libtorch v2.0.0
  • Upgrade Go version 1.20
  • Switched to use hybrid of Go garbage collection and manually memory management
  • Fixed #100 #102
  • Fixed incorrect indexing at dutil/Dataset.Next()
  • Added nn.MSELoss()
  • reworked ts.Format()
  • Added conv2d benchmark
  • Fixed #88 memory leak at example/char-rnn
  • Added missing tensor Stride() and MustDataPtr(), IsMkldnn, MustIsMkldnn, IsContiguous, MustIsContiguous
  • Added ts New()

[0.7.0]

  • Added WsName and BsName fields to nn.LayerNorm.Config
  • [#70] Upgraded to libtorch 1.11
  • Added API Path.Remove(); Path.MustRemove()

[0.6.2]

  • Fixed dutil/MapDataset
  • [#69] change package name tensor -> ts for easy coding.
  • [#68] simplify VarStore struct and adde more APIs for VarStore and Optimizer
  • Fixed pickle with zero data length
  • Added gotch.CleanCache() API.

[0.6.1]

  • Fixed wrong cacheDir and switch off logging.
  • Added more pickle classes to handle unpickling

[0.6.0]

  • Added subpackage pickle. Now we can load directly Python Pytorch pretrained model without any Python script conversion.
  • Added gotch.CachePath() and gotch.ModelUrls
  • Remove Travis CI for now.
  • fixed tensor.OfSlice() throw error due to "Unsupported Go type" (e.g. []float32)
  • added nn.Path.Paths() method
  • added nn.VarStore.Summary() method
  • fixed incorrect tensor method ts.Meshgrid -> Meshgrid
  • added new API ConstantPadNdWithVal ato_constant_pad_nd with padding value.
  • fixed "nn/rnn NewLSTM() clashed weight names"
  • fixed some old API at vision/aug/function.go
  • fixed tensor.OfSlice() not supporting []int data type
  • fixed make tensor.ValueGo() returning []int instead of []int32
  • added more building block modules: Dropout, MaxPool2D, Parameter, Identity
  • added nn.BatchNorm.Forward() with default training=true
  • added exposing tensor.Ctensor()
  • added API tensor.FromCtensor()
  • [#67]: fixed incorrect type casting at atc_cuda_count

[0.5.0]

  • Upgraded to libtorch 1.10
  • #58 Fixed incorrect converting IValue from CIValue case 1 (Tensor).

[0.4.5]

  • Added Conv3DConfig and Conv3DConfig Option
  • Added missing Tensor methods APIs those return multiple tensors (e.g. tensor.Svd).

[0.4.4]

  • Dropped libtch dummy_cuda_dependency() and fake_cuda_dependency() as libtorch ldd linking Okay now.

[0.4.3]

  • Export nn/scheduler DefaultSchedulerOptions()

[0.4.2]

  • Added nn/scheduler NewLRScheduler()
  • Added nn/conv config options

[0.4.1]

  • fixed cuda error undefined reference to 'at::cuda::warp_size()'

[0.4.0]

  • Update libtorch to 1.9. Generated 1716 APIs. There are APIs naming changes ie. Name1 change to NameDim or NameTensor.

[0.3.14]

  • Fixed temporary fix huge number of learning group returned from C at libtch/tensor.go AtoGetLearningRates
  • Fixed incorrect nn.AdamWConfig and some documentation.
  • Fixed - reworked on vision.ResNet and vision.DenseNet to fix incorrect layers and memory leak
  • Changed dutil.DataLoader.Reset() to reshuffle when resetting DataLoader if flag is true
  • Changed dutil.DataLoader.Next(). Deleted case batch size == 1 to make consistency by always returning items in a slice []element dtype even with batchsize = 1.
  • Added nn.CrossEntropyLoss and nn.BCELoss
  • Fixed tensor.ForwardIs return Tuple and TensorList instead of always returning TensorList
  • Changed exporting augment options and make ColorJitter forward output dtype uint8 for chaining with other augment options.
  • #45 Fixed init/RandInt incorrect initialization
  • #48 Fixed init/RandInit when init with mean = 0.0.

[0.3.13]

  • Fixed multiple memory leakage at vision/image.go
  • Fixed memory leakage at dutil/dataloader.go
  • Fixed multiple memory leakage at efficientnet.go
  • Added dataloader.Len() method
  • Fixed deleting input tensor inside function at tensor/other.go tensor.CrossEntropyForLogits and tensor.AccuracyForLogits
  • Added warning to varstore.LoadPartial when mismatched tensor shapes between source and varstore.
  • Fixed incorrect message mismatched tensor shape at nn.Varstore.Load
  • Fixed incorrect y -> x at vision/aug/affine.go getParam func
  • Fixed double free tensor at vision/aug/function.go Equalize func.
  • Changed vision/aug all input image should be uint8 (Byte) dtype and transformed output has the same dtype (uint8) so that Compose() can compose any transformer options.
  • Fixed wrong result of aug.RandomAdjustSharpness
  • Fixed memory leak at aug/function.getAffineGrid
  • Changed vision/aug and correct ColorJitter
  • Changed vision/aug and correct Resize
  • Changed dutil/sampler to accept batchsize from 1.
  • Fixed double free in vision/image.go/resizePreserveAspectRatio

[0.3.12]

Skip this tag

[0.3.11]

Same as [0.3.10]

[0.3.10]

  • Update installation at README.md
  • [#38] fixed JIT model
  • Added Optimizer Learning Rate Schedulers
  • Added AdamW Optimizer

[0.3.9]

  • #24, #26: fixed memory leak.
  • #30: fixed varstore.Save() randomly panic - segmentfault
  • #32: nn.Seq Forward return nil tensor if length of layers = 1
  • [#36]: resolved image augmentation

[0.3.8]

Fixed

  • #20: fixed IValue.Value() method return []interface{} instead of []Tensor

[0.3.7]

Added

  • Added trainable JIT Module APIs and example/jit-train. Now, a Python Pytorch model .pt can be loaded then continue training/fine-tuning in Go.

[0.3.6]

Added

  • Added dutil sub-package that serves Pytorch DataSet and DataLoader concepts

[0.3.5]

Added

  • Added function gotch.CudaIfAvailable(). NOTE that: device := gotch.NewCuda().CudaIfAvailable() will throw error if CUDA is not available.

Changed

  • Switched back to install libtorch inside gotch library as go init() function is triggered after cgo called.

[0.3.4]

Added

  • #4 Automatically download and install Libtorch and setup environment variables.

[0.3.2]

Added

  • #6: Go native tensor print using fmt.Formatter interface. Now, a tensor can be printed out like: fmt.Printf("%.3f", tensor) (for float type)

[0.3.3]

Fixed

  • nn/sequential: fixed missing case number of layers = 1 causing panic
  • nn/varstore: fixed(nn/varstore): fixed nil pointer at LoadPartial due to not break loop

[0.3.1]

Changed

  • Changed to use map[string]*Tensor at nn/varstore.go
  • Changed to use *Path argument of NewLayerNorm method at nn/layer-norm.go
  • Lots of clean-up return variables i.e. retVal, err

[0.3.0]

Changed

  • Updated to Pytorch C++ APIs v1.7.0
  • Switched back to lib.AtoAddParametersOld as the ato_add_parameters has not been implemented correctly. Using the updated API will cause optimizer stops working.

[0.2.0]

Changed

  • Convert all APIs to using Pointer Receiver

Added

  • Added drawing image label at example/yolo example
  • Added some example images and README files for example/yolo and example/neural-style-transfer

[0.1.10]

Added

  • Added tensor.SaveMultiNew

[0.1.9]

Changed

  • Reverse changes #10 to original.

[0.1.8]

Changed

  • #10: ts.Drop() and ts.MustDrop() now can call multiple times without panic