Theano-1.0.2.tar.gz

.. _HISTORY: ================= Old Release Notes ================= Theano 1.0.1 (6th of December, 2017) ==================================== This is a maintenance release of Theano, version ``1.0.1``, with no new features, but some important bug fixes. We recommend that everybody update to this version. Highlights (since 1.0.0): - Fixed compilation and improved float16 support for topK on GPU - **NB**: topK support on GPU is experimental and may not work for large input sizes on certain GPUs - Fixed cuDNN reductions when axes to reduce have size ``1`` - Attempted to prevent re-initialization of the GPU in a child process - Fixed support for temporary paths with spaces in Theano initialization - Spell check pass on the documentation A total of 6 people contributed to this release since ``1.0.0``: - Frederic Bastien - Steven Bocco - Arnaud Bergeron - Sam Johnson - Edward Betts - Simon Lefrancois Theano 1.0.0 (15th of November, 2017) ===================================== This is a final release of Theano, version ``1.0.0``, with a lot of new features, interface changes, improvements and bug fixes. We recommend that everybody update to this version. Highlights (since 0.9.0): - Announcing that `MILA will stop developing Theano <https://groups.google.com/d/msg/theano-users/7Poq8BZutbY/rNCIfvAEAwAJ>`_ - conda packages now available and updated in our own conda channel ``mila-udem`` To install it: ``conda install -c mila-udem theano pygpu`` - Support NumPy ``1.13`` - Support pygpu ``0.7`` - Moved Python ``3.*`` minimum supported version from ``3.3`` to ``3.4`` - Added conda recipe - Replaced deprecated package ``nose-parameterized`` with up-to-date package ``parameterized`` for Theano requirements - Theano now internally uses ``sha256`` instead of ``md5`` to work on systems that forbid ``md5`` for security reason - Removed old GPU backend ``theano.sandbox.cuda``. New backend ``theano.gpuarray`` is now the official GPU backend - Make sure MKL uses GNU OpenMP - **NB**: Matrix dot product (``gemm``) with ``mkl`` from conda could return wrong results in some cases. We have reported the problem upstream and we have a work around that raises an error with information about how to fix it. - Improved elemwise operations - Speed-up elemwise ops based on SciPy - Fixed memory leaks related to elemwise ops on GPU - Scan improvements - Speed up Theano scan compilation and gradient computation - Added meaningful message when missing inputs to scan - Speed up graph toposort algorithm - Faster C compilation by massively using a new interface for op params - Faster optimization step, with new optional destroy handler - Documentation updated and more complete - Added documentation for RNNBlock - Updated ``conv`` documentation - Support more debuggers for ``PdbBreakpoint`` - Many bug fixes, crash fixes and warning improvements A total of 71 people contributed to this release since 0.9.0, see list below. Interface changes: - Merged duplicated diagonal functions into two ops: ``ExtractDiag`` (extract a diagonal to a vector), and ``AllocDiag`` (set a vector as a diagonal of an empty array) - Removed op ``ExtractDiag`` from ``theano.tensor.nlinalg``, now only in ``theano.tensor.basic`` - Generalized ``AllocDiag`` for any non-scalar input - Added new parameter ``target`` for MRG functions - Renamed ``MultinomialWOReplacementFromUniform`` to ``ChoiceFromUniform`` - Changed ``grad()`` method to ``L_op()`` in ops that need the outputs to compute gradient - Removed or deprecated Theano flags: - ``cublas.lib`` - ``cuda.enabled`` - ``enable_initial_driver_test`` - ``gpuarray.sync`` - ``home`` - ``lib.cnmem`` - ``nvcc.*`` flags - ``pycuda.init`` Convolution updates: - Implemented separable convolutions for 2D and 3D - Implemented grouped convolutions for 2D and 3D - Added dilated causal convolutions for 2D - Added unshared convolutions - Implemented fractional bilinear upsampling - Removed old ``conv3d`` interface - Deprecated old ``conv2d`` interface GPU: - Added a meta-optimizer to select the fastest GPU implementations for convolutions - Prevent GPU initialization when not required - Added disk caching option for kernels - Added method ``my_theano_function.sync_shared()`` to help synchronize GPU Theano functions - Added useful stats for GPU in profile mode - Added Cholesky op based on ``cusolver`` backend - Added GPU ops based on `magma library <http://icl.cs.utk.edu/magma/software/>`_: SVD, matrix inverse, QR, cholesky and eigh - Added ``GpuCublasTriangularSolve`` - Added atomic addition and exchange for ``long long`` values in ``GpuAdvancedIncSubtensor1_dev20`` - Support log gamma function for all non-complex types - Support GPU SoftMax in both OpenCL and CUDA - Support offset parameter ``k`` for ``GpuEye`` - ``CrossentropyCategorical1Hot`` and its gradient are now lifted to GPU - cuDNN: - Official support for ``v6.*`` and ``v7.*`` - Added spatial transformation operation based on cuDNN - Updated and improved caching system for runtime-chosen cuDNN convolution algorithms - Support cuDNN v7 tensor core operations for convolutions with runtime timed algorithms - Better support and loading on Windows and Mac - Support cuDNN v6 dilated convolutions - Support cuDNN v6 reductions for contiguous inputs - Optimized ``SUM(x^2)``, ``SUM(ABS(X))`` and ``MAX(ABS(X))`` operations with cuDNN reductions - Added new Theano flags ``cuda.include_path``, ``dnn.base_path`` and ``dnn.bin_path`` to help configure Theano when CUDA and cuDNN can not be found automatically - Extended Theano flag ``dnn.enabled`` with new option ``no_check`` to help speed up cuDNN importation - Disallowed ``float16`` precision for convolution gradients - Fixed memory alignment detection - Added profiling in C debug mode (with theano flag ``cmodule.debug=True``) - Added Python scripts to help test cuDNN convolutions - Automatic addition of cuDNN DLL path to ``PATH`` environment variable on Windows - Updated ``float16`` support - Added documentation for GPU float16 ops - Support ``float16`` for ``GpuGemmBatch`` - Started to use ``float32`` precision for computations that don't support ``float16`` on GPU New features: - Implemented truncated normal distribution with box-muller transform - Added ``L_op()`` overriding option for ``OpFromGraph`` - Added NumPy C-API based fallback implementation for ``[sd]gemv_`` and ``[sd]dot_`` - Implemented ``topk`` and ``argtopk`` on CPU and GPU - Implemented ``max()`` and ``min()`` functions for booleans and unsigned integers types - Added ``tensor6()`` and ``tensor7()`` in ``theano.tensor`` module - Added boolean indexing for sub-tensors - Added covariance matrix function ``theano.tensor.cov`` - Added a wrapper for `Baidu's CTC <https://github.com/baidu-research/warp-ctc>`_ cost and gradient functions - Added scalar and elemwise CPU ops for modified Bessel function of order 0 and 1 from ``scipy.special`` - Added Scaled Exponential Linear Unit (SELU) activation - Added sigmoid_binary_crossentropy function - Added tri-gamma function - Added ``unravel_index`` and ``ravel_multi_index`` functions on CPU - Added modes ``half`` and ``full`` for ``Images2Neibs`` ops - Implemented gradient for ``AbstractBatchNormTrainGrad`` - Implemented gradient for matrix pseudoinverse op - Added new prop `replace` for ``ChoiceFromUniform`` op - Added new prop ``on_error`` for CPU ``Cholesky`` op - Added new Theano flag ``deterministic`` to help control how Theano optimize certain ops that have deterministic versions. Currently used for subtensor Ops only. - Added new Theano flag ``cycle_detection`` to speed-up optimization step by reducing time spending in inplace optimizations - Added new Theano flag ``check_stack_trace`` to help check the stack trace during opti