Paddle/RELEASE.md

Release v0.10.0

New Features

• Support rectangle input for CNN.
• Support stride pooling for seqlastin and seqfirstin.
• Expose seq_concat_layer/seq_reshape_layer in trainer_config_helpers.
• Add dataset package
  • CIFAR, MNIST, IMDB, WMT14, CONLL05, movielens, imikolov.
• Add Priorbox layer for Single Shot Multibox Detection.
• Add smooth L1 cost.
• Add data reader creator and data reader decorator for v2 API.
• Add the cpu implementation of cmrnorm-projection.

Improvements

• Speedup the backward of average layer on GPU.
• Reorganize the catalog of doc/ and refine several docs.
• Add Travis-CI for checking dead links.
• Add a example for explaining sparse_vector.
• Add Relu in layer_math.py
• Simplify data processing flow for quick start.
• Support CUDNN Deconv.
• Add data feeder for v2 API.
• Support predicting the samples from sys.stdin for sentiment demo.
• Provide multi-proccess interface for image preprocessing.
• Add benchmark document for v1 API.
• Add Relu in layer_math.py.
• Add packages for automatically downloading public datasets.
• Rename Argument::sumCost to Argument::sum since Argument does not have to have any relationship with cost.
• Add a new TensorExpression implementation for matrix-related expression evaluations.
• Add Lazy Assignment for optimize the calculation of multiple expressions.
• Add Function to reconstruct the computation function.
  • PadFunc and PadGradFunc.
  • ContextProjectionForwardFunc and ContextProjectionBackwardFunc.
  • CosSimBackward and CosSimBackwardFunc.
  • CrossMapNormalFunc and CrossMapNormalGradFunc.
  • MulFunc.
• Add AutoCompare and FunctionCompare, which make it easier to write unittest for comparing gpu and cpu version of a function.
• Add libpaddle_test_main.a and remove the main function inside the test file.

Bug Fixes

• Add layer check for recurrent_group.
• Clang-format off on some cuda .cc files.
• Fix LogActivation which is not defined.
• Fix bug when run test_layerHelpers multiple times.
• Fix protobuf size limit on seq2seq demo.
• Fix bug for dataprovider converter in GPU mode.
• Fix bug in GatedRecurrentLayer which only occurs in predicting or job=test mode.
• Fix bug for BatchNorm when testing more than models in test mode.
• Fix unit test of paramRelu.
• Fix some warning about CpuSparseMatrix.
• Fix MultiGradientMachine error if trainer_count > batch_size.

Release v0.9.0

New Features:

• New Layers
  • bilinear interpolation layer.
  • spatial pyramid-pool layer.
  • de-convolution layer.
  • maxout layer.
• Support rectangle padding, stride, window and input for Pooling Operation.
• Add —job=time in trainer, which can be used to print time info without compiler option -WITH_TIMER=ON.
• Expose cost_weight/nce_layer in trainer_config_helpers
• Add FAQ, concepts, h-rnn docs.
• Add Bidi-LSTM and DB-LSTM to quick start demo @alvations
• Add usage track scripts.

Improvements

• Add Travis-CI for Mac OS X. Enable swig unittest in Travis-CI. Skip Travis-CI when only docs are changed.
• Add code coverage tools.
• Refine convolution layer to speedup and reduce GPU memory.
• Speed up PyDataProvider2
• Add ubuntu deb package build scripts.
• Make Paddle use git-flow branching model.
• PServer support no parameter blocks.

Bug Fixes

• add zlib link to py_paddle
• add input sparse data check for sparse layer at runtime
• Bug fix for sparse matrix multiplication
• Fix floating-point overflow problem of tanh
• Fix some nvcc compile options
• Fix a bug in yield dictionary in DataProvider
• Fix SRL hang when exit.

Release v0.8.0beta.1

New features:

• Mac OSX is supported by source code. #138

  • Both GPU and CPU versions of PaddlePaddle are supported.

• Support CUDA 8.0

• Enhance PyDataProvider2

  • Add dictionary yield format. PyDataProvider2 can yield a dictionary with key is data_layer's name, value is features.
  • Add min_pool_size to control memory pool in provider.

• Add deb install package & docker image for no_avx machines.

  • Especially for cloud computing and virtual machines

• Automatically disable avx instructions in cmake when machine's CPU don't support avx instructions.

• Add Parallel NN api in trainer_config_helpers.

• Add travis ci for Github

Bug fixes:

• Several bugs in trainer_config_helpers. Also complete the unittest for trainer_config_helpers
• Check if PaddlePaddle is installed when unittest.
• Fix bugs in GTX series GPU
• Fix bug in MultinomialSampler

Also more documentation was written since last release.

Release v0.8.0beta.0

PaddlePaddle v0.8.0beta.0 release. The install package is not stable yet and it's a pre-release version.