# 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 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. * 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 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.