发布于 2016-11-30 01:33:06 | 392 次阅读 | 评论: 0 | 来源: 网友投递
这里有新鲜出炉的TensorFlow 官方文档中文版，程序狗速度看过来！
TensorFlow 机器学习系统
TensorFlow 是谷歌的第二代机器学习系统，按照谷歌所说，在某些基准测试中，TensorFlow的表现比第一代的DistBelief快了2倍。
主要新特性和改进：
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.
Go: Experimental API in Go to create and execute graphs (https://godoc.org/github.com/tensorflow/tensorflow/tensorflow/go)
New checkpoint format becomes the default in tf.train.Saver. Old V1 checkpoints continue to be readable; controlled by the write_version argument, tf.train.Saver 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.
Added gradients for matrix_solve_ls and self_adjoint_eig.
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.
Added a solver for ordinary differential equations, tf.contrib.integrate.odeint.
New contrib module for tensors with named axes, tf.contrib.labeled_tensor.
Visualization of embeddings in TensorBoard.
API的重大改变：
BusAdjacency enum replaced with a protocol buffer DeviceLocality. PCI bus indexing now starts from 1 instead of 0, and bus_id==0 is used where previously BUS_ANY was used.
Env::FileExists and FileSystem::FileExists now return a tensorflow::Status intead of a bool. Any callers to this function can be converted to a bool by adding .ok() to the call.
C API: Type TF_SessionWithGraph has been renamed to TF_Session, indicating its preferred use in language bindings for TensorFlow. What was previously TF_Session has been renamed toTF_DeprecatedSession.
C API: Renamed TF_Port to TF_Output.
C API: The caller retains ownership of TF_Tensor objects provided to TF_Run, TF_SessionRun,TF_SetAttrTensor etc.
Renamed tf.image.per_image_whitening() to tf.image.per_image_standardization()
Move Summary protobuf constructors to tf.summary submodule.
Deprecate histogram_summary, audio_summary, scalar_summary, image_summary, merge_summary, and merge_all_summaries.
Combined batch_* and regular version of linear algebra and FFT ops. The regular op now handles batches as well. All batch_* Python interfaces were removed.
tf.all_variables, tf.VARIABLES and tf.initialize_all_variables renamed totf.global_variables, tf.GLOBAL_VARIABLES and tf.global_variable_initializers respectively.
重大修复和其他更新
Use threadsafe version of lgamma function.
Fix tf.sqrt handling of negative arguments.
Fixed bug causing incorrect number of threads to be used for multi-threaded benchmarks.
Performance optimizations for batch_matmul on multi-core CPUs.
Improve trace, matrix_set_diag, matrix_diag_part and their gradients to work for rectangular matrices.
Support for SVD of complex valued matrices
更多详情请点击更新日志。
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