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Release notes
0.1.6
- Added activation type print in verbose mode
- Added fast and parallel CPU implementation for Swish, Relu, Add, Sub, Div, Min, Max, Tanh, Exp
- Removed duplicate profiler blocks for ops
- Improved scheduling on CPU for small batches of data
- Fixed compatibility with Unity 2019.2.x
0.1.5
- Added Transpose, MatMul and Indentity layer support for models exported from ONNX.
- Added BasicLSTM layer support for models exported from TF. Limited set of LSTM networks should work now.
- Added DepthwiseConv2D layer support. Most of the networks based on the MobileNet should work now.
- Added OneHot layer support for models exported from TF.
- Added optimized path for Conv2D, Dense and Transpose layers with single batch executions. Performance gain up to 100%.
- Fixed FMA performance issue on Metal GFX platforms.
- Added fast optimized path for Sigmoid and Mul layers on CPU.
- Fixed issue when worker is executed with different batch sizes.
- Added
pip
requirements file for Python dependencies, check ``Tools/requirements.txt```. - Added proof of concept Docker wrappers for running model conversion inside of Docker container. Check
Tools/docker-tensorflow-to-barracuda.sh
andTools/docker-onnx-to-barracuda.sh
. Currently it was tested only on Mac host. - Refactored model importers for easier integration with ML Agents.
- Fixed input shape determination for Keras sequential model.
- Added metadata about input shapes to model. Look for
Model.GetShapeByName()
. - Added API to query constant Tensors embedded into network, look for
Model.GetTensorByName()
. - Added reference implementations for Selu, Abs, Neg, Ceil, Floor, Clip, Rcp, Log layers.
- Added support for Mean, Square, StridedSlice and Border2D layers.
- Added support for Swish activation, now it is automatically detected in models.
- Fixed Tanh NaN issue when large argument is passed.
- RandomNormal and RandomUniform now supports either embedded shape constant OR previous tensor shape for input.
- Fixed Keras/TF/ONNX FusedBatchNorm/BatchNorm import and now it takes
epsilon
into account. - Now Barracuda will fallback to CSharpFast if compute shaders are not supported on the current platform.
- Improved compute kernel interop on Android.
- Implemented Pix2Pix model (.pict) importer.
0.1.4
- Implemented fast Conv2DTrans. Useful for GAN type networks.
- Fixed few ComputeBuffer handling issues.
- Simplified way to pass texture via
Tensor
constructor. - Documentation improvements.
- Added Unity Companion License as part of distribution.
- Fixed boundary checks for Compute Copy/Concat operations.
- Improved profiling experience, now each layer will be reported separately in Unity Profiler.
- Fixed Broadcast layer support in
ModelAnalyzer
. - Exp, Pow and other layers are now also implemented in Compute. Improves RL model inference performance on GPU.
- Added platform specific BLAS plugin support. Out of the box Barracuda ships with Apple Accelerate framework support for iOS and macOS.
- Added Burst BLAS plugin, greatly improves performance in Unity Editor where native OS BLAS is not available. It's packaged as separate package and requires to have Burst enabled.
- Improved memory handling, now less GC allocations should be made per inference execution.
0.1.3
- Improved Barracuda support for Unity Profiler.
- Cleaned up Barracuda APIs.
- Added direct
Texture
input support. Look forTextureAsTensorData
. The following types of texture supported as input:Texture2D
,Texture2DArray
,Texture3D
,RenderTexture
. - Added
Tensor
toRenderTexture
conversion. Look forTensorToRenderTexture
. - Autoencoder type networks can run completely on GPU now. Data roundtrip via CPU is not necessary anymore.
- Vertical flip is applied when converting between
Texture
andTensor
to match conventionts. To override this behavior look forTextureAsTensorData.Flip
enum. - Removed direct reference to WebCamTexture, now Barracuda compiles for Console targets.
- Fixed Conv2DTranspose layer support. Now GANs using Conv2DTranspose work properly.
- Added automated test for pix2pix GAN.
0.1.2
- Barracuda now is also available as preview package. Look for
com.unity.barracuda
in https://staging-packages.unity.com registry. - Conv2D layers are now up to 30x faster with
CSharpFast
backend (ComputeFast
remains best backend for convolutional networks). - Added profiler sample for
Fetch()
. - Fixed compilation issues on Xbox One.
- TexConv2D support was temporary disabled.
- Barracuda logging now can be configured via static fields of
Barracuda.D
class, it allows both disable specific logging levels or just disable stack trace collection (helps with performance when profiling). - Compute Concat implementation now will fall back to C# implementation instead of throwing exception when unsupported configuration is encountered.
- Fixed several
ComputeBuffer
release issues. - Added constructor for
Tensor
that allows to pass in data array. - Improved Flatten handling in TensorFlow models.
- Added helper func
ModelLoader.LoadFromStreamingAssets
. - Fixed .meta file packaging.
- Small docs improvements.
- Fixed unnecessary patching of Activation layers in
ModelLoader
. - Added output trimming at run-time. See for extra parameters Worker factory.
0.1.1
- First internal realease as drop-in package
- Compatibility with ML Agents models: 3DBall, PushBlock, GridWorld, Soccer.
0.1.0
- First internal build. Due some bugs encountered wasn't published.