Release TensorFlow v0.12.0 RC0 · tensorflow/tensorflow · GitHub

#TensorFlow RC12 has embedding visualization built into Tensorboard.

  • Large cleanup to add second order gradient for ops with C++ gradients and improve existing gradients such that most ops can now be differentiated multiple times.
  • TensorFlow now builds and runs on Microsoft Windows (tested on Windows 10, Windows 7, and Windows Server 2016).
  • Improve trace, matrix_set_diag , matrix_diag_part and their gradients to work for rectangular matrices.
  • Added a new library for library of matrix-free (iterative) solvers for linear equations, linear least-squares, eigenvalues and singular values in tensorflow/contrib/solvers.
  • C API: Type TF_SessionWithGraph has been renamed to TF_Session , indicating its preferred use in language bindings for TensorFlow.

tensorflow – Computation using data flow graphs for scalable machine learning

@deliprao: #TensorFlow RC12 has embedding visualization built into Tensorboard.

TensorFlow now builds and runs on Microsoft Windows (tested on Windows 10, Windows 7, and Windows Server 2016). Supported languages include Python (via a pip package) and C++. CUDA 8.0 and cuDNN 5.1 are supported for GPU acceleration. Known limitations include: It is not currently possible to load a custom op library. The GCS and HDFS file systems are not currently supported. The following ops are not currently implemented: DepthwiseConv2dNative, DepthwiseConv2dNativeBackpropFilter, DepthwiseConv2dNativeBackpropInput, Dequantize, Digamma, Erf, Erfc, Igamma, Igammac, Lgamma, Polygamma, QuantizeAndDequantize, QuantizedAvgPool, QuantizedBatchNomWithGlobalNormalization, QuantizedBiasAdd, QuantizedConcat, QuantizedConv2D, QuantizedMatmul, QuantizedMaxPool, QuantizeDownAndShrinkRange, QuantizedRelu, QuantizedRelu6, QuantizedReshape, QuantizeV2, RequantizationRange, and Requantize.

now by default writes out in the new V2 format. It significantly reduces the peak memory required and latency incurred during restore.

Added a new library for library of matrix-free (iterative) solvers for linear equations, linear least-squares, eigenvalues and singular values in tensorflow/contrib/solvers. Initial version has lanczos bidiagonalization, conjugate gradients and CGLS.

Large cleanup to add second order gradient for ops with C++ gradients and improve existing gradients such that most ops can now be differentiated multiple times.

Visualization of embeddings in TensorBoard.

was used.

to the call.

etc.

submodule.

Python interfaces were removed.

respectively.

function.

handling of negative arguments.

Fixed bug causing incorrect number of threads to be used for multi-threaded benchmarks.

on multi-core CPUs.

and their gradients to work for rectangular matrices.

Support for SVD of complex valued matrices.

Release TensorFlow v0.12.0 RC0 · tensorflow/tensorflow · GitHub