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   <p>#singa-incubating-1.0.0 Release Notes</p>
 <hr class="docutils" />
 <p>SINGA is a general distributed deep learning platform for training big deep
 learning models over large datasets. It is designed with an intuitive
 programming model based on the layer abstraction. SINGA supports a wide variety
 of popular deep learning models.</p>
 <p>This release includes following features:</p>
 <ul class="simple">
 <li>Core abstractions including Tensor and Device<ul>
 <li>[SINGA-207]  Update Tensor functions for matrices</li>
 <li>[SINGA-205]  Enable slice and concatenate operations for Tensor objects</li>
 <li>[SINGA-197]  Add CNMem as a submodule in lib/</li>
 <li>[SINGA-196]  Rename class Blob to Block</li>
 <li>[SINGA-194]  Add a Platform singleton</li>
 <li>[SINGA-175]  Add memory management APIs and implement a subclass using CNMeM</li>
 <li>[SINGA-173]  OpenCL Implementation</li>
 <li>[SINGA-171]  Create CppDevice and CudaDevice</li>
 <li>[SINGA-168]  Implement Cpp Math functions APIs</li>
 <li>[SINGA-162]  Overview of features for V1.x</li>
 <li>[SINGA-165]  Add cross-platform timer API to singa</li>
 <li>[SINGA-167]  Add Tensor Math function APIs</li>
 <li>[SINGA-166]  light built-in logging for making glog optional</li>
 <li>[SINGA-164]  Add the base Tensor class</li>
 </ul>
 </li>
 </ul>
 <ul class="simple">
 <li>IO components for file read/write, network and data pre-processing<ul>
 <li>[SINGA-233]  New communication interface</li>
 <li>[SINGA-215]  Implement Image Transformation for Image Pre-processing</li>
 <li>[SINGA-214]  Add LMDBReader and LMDBWriter for LMDB</li>
 <li>[SINGA-213]  Implement Encoder and Decoder for CSV</li>
 <li>[SINGA-211]  Add TextFileReader and TextFileWriter for CSV files</li>
 <li>[SINGA-210]  Enable checkpoint and resume for v1.0</li>
 <li>[SINGA-208]  Add DataIter base class and a simple implementation</li>
 <li>[SINGA-203]  Add OpenCV detection for cmake compilation</li>
 <li>[SINGA-202]  Add reader and writer for binary file</li>
 <li>[SINGA-200]  Implement Encoder and Decoder for data pre-processing</li>
 </ul>
 </li>
 </ul>
 <ul class="simple">
 <li>Module components including layer classes, training algorithms and Python binding<ul>
 <li>[SINGA-235]  Unify the engines for cudnn and singa layers</li>
 <li>[SINGA-230]  OpenCL Convolution layer and Pooling layer</li>
 <li>[SINGA-222]  Fixed bugs in IO</li>
 <li>[SINGA-218]  Implementation for RNN CUDNN version</li>
 <li>[SINGA-204]  Support the training of feed-forward neural nets</li>
 <li>[SINGA-199]  Implement Python classes for SGD optimizers</li>
 <li>[SINGA-198]  Change Layer::Setup API to include input Tensor shapes</li>
 <li>[SINGA-193]  Add Python layers</li>
 <li>[SINGA-192]  Implement optimization algorithms for Singa v1 (nesterove, adagrad, rmsprop)</li>
 <li>[SINGA-191]  Add &#8220;autotune&#8221; for CudnnConvolution Layer</li>
 <li>[SINGA-190]  Add prelu layer and flatten layer</li>
 <li>[SINGA-189]  Generate python outputs of proto files</li>
 <li>[SINGA-188]  Add Dense layer</li>
 <li>[SINGA-187]  Add popular parameter initialization methods</li>
 <li>[SINGA-186]  Create Python Tensor class</li>
 <li>[SINGA-184]  Add Cross Entropy loss computation</li>
 <li>[SINGA-183]  Add the base classes for optimizer, constraint and regularizer</li>
 <li>[SINGA-180]  Add Activation layer and Softmax layer</li>
 <li>[SINGA-178]  Add Convolution layer and Pooling layer</li>
 <li>[SINGA-176]  Add loss and metric base classes</li>
 <li>[SINGA-174]  Add Batch Normalization layer and Local Response Nomalization layer.</li>
 <li>[SINGA-170]  Add Dropout layer and CudnnDropout layer.</li>
 <li>[SINGA-169]  Add base Layer class for V1.0</li>
 </ul>
 </li>
 </ul>
 <ul class="simple">
 <li>Examples<ul>
 <li>[SINGA-232]  Alexnet on Imagenet</li>
 <li>[SINGA-231]  Batchnormlized VGG model for cifar-10</li>
 <li>[SINGA-228]  Add Cpp Version of Convolution and Pooling layer</li>
 <li>[SINGA-227]  Add Split and Merge Layer and add ResNet Implementation</li>
 </ul>
 </li>
 <li>Documentation<ul>
 <li>[SINGA-239]  Transfer documentation files of v0.3.0 to github</li>
 <li>[SINGA-238]  RBM on mnist</li>
 <li>[SINGA-225]  Documentation for installation and Cifar10 example</li>
 <li>[SINGA-223]  Use Sphinx to create the website</li>
 </ul>
 </li>
 <li>Tools for compilation and some utility code<ul>
 <li>[SINGA-229]  Complete install targets</li>
 <li>[SINGA-221]  Support for Travis-CI</li>
 <li>[SINGA-217]  build python package with setup.py</li>
 <li>[SINGA-216]  add jenkins for CI support</li>
 <li>[SINGA-212]  Disable the compilation of libcnmem if USE_CUDA is OFF</li>
 <li>[SINGA-195]  Channel for sending training statistics</li>
 <li>[SINGA-185]  Add CBLAS and GLOG detection for singav1</li>
 <li>[SINGA-181]  Add NVCC supporting for .cu files</li>
 <li>[SINGA-177]  Add fully cmake supporting for the compilation of singa_v1</li>
 <li>[SINGA-172]  Add CMake supporting for Cuda and Cudnn libs</li>
 </ul>
 </li>
 </ul>


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	<p>#singa-incubating-1.0.0 Release Notes</p>
	<hr class="docutils" />
	<p>SINGA is a general distributed deep learning platform for training big deep
	learning models over large datasets. It is designed with an intuitive
	programming model based on the layer abstraction. SINGA supports a wide variety
	of popular deep learning models.</p>
	<p>This release includes following features:</p>
	<ul class="simple">
	<li>Core abstractions including Tensor and Device<ul>
	<li>[SINGA-207] Update Tensor functions for matrices</li>
	<li>[SINGA-205] Enable slice and concatenate operations for Tensor objects</li>
	<li>[SINGA-197] Add CNMem as a submodule in lib/</li>
	<li>[SINGA-196] Rename class Blob to Block</li>
	<li>[SINGA-194] Add a Platform singleton</li>
	<li>[SINGA-175] Add memory management APIs and implement a subclass using CNMeM</li>
	<li>[SINGA-173] OpenCL Implementation</li>
	<li>[SINGA-171] Create CppDevice and CudaDevice</li>
	<li>[SINGA-168] Implement Cpp Math functions APIs</li>
	<li>[SINGA-162] Overview of features for V1.x</li>
	<li>[SINGA-165] Add cross-platform timer API to singa</li>
	<li>[SINGA-167] Add Tensor Math function APIs</li>
	<li>[SINGA-166] light built-in logging for making glog optional</li>
	<li>[SINGA-164] Add the base Tensor class</li>
	</ul>
	</li>
	</ul>
	<ul class="simple">
	<li>IO components for file read/write, network and data pre-processing<ul>
	<li>[SINGA-233] New communication interface</li>
	<li>[SINGA-215] Implement Image Transformation for Image Pre-processing</li>
	<li>[SINGA-214] Add LMDBReader and LMDBWriter for LMDB</li>
	<li>[SINGA-213] Implement Encoder and Decoder for CSV</li>
	<li>[SINGA-211] Add TextFileReader and TextFileWriter for CSV files</li>
	<li>[SINGA-210] Enable checkpoint and resume for v1.0</li>
	<li>[SINGA-208] Add DataIter base class and a simple implementation</li>
	<li>[SINGA-203] Add OpenCV detection for cmake compilation</li>
	<li>[SINGA-202] Add reader and writer for binary file</li>
	<li>[SINGA-200] Implement Encoder and Decoder for data pre-processing</li>
	</ul>
	</li>
	</ul>
	<ul class="simple">
	<li>Module components including layer classes, training algorithms and Python binding<ul>
	<li>[SINGA-235] Unify the engines for cudnn and singa layers</li>
	<li>[SINGA-230] OpenCL Convolution layer and Pooling layer</li>
	<li>[SINGA-222] Fixed bugs in IO</li>
	<li>[SINGA-218] Implementation for RNN CUDNN version</li>
	<li>[SINGA-204] Support the training of feed-forward neural nets</li>
	<li>[SINGA-199] Implement Python classes for SGD optimizers</li>
	<li>[SINGA-198] Change Layer::Setup API to include input Tensor shapes</li>
	<li>[SINGA-193] Add Python layers</li>
	<li>[SINGA-192] Implement optimization algorithms for Singa v1 (nesterove, adagrad, rmsprop)</li>
	<li>[SINGA-191] Add “autotune” for CudnnConvolution Layer</li>
	<li>[SINGA-190] Add prelu layer and flatten layer</li>
	<li>[SINGA-189] Generate python outputs of proto files</li>
	<li>[SINGA-188] Add Dense layer</li>
	<li>[SINGA-187] Add popular parameter initialization methods</li>
	<li>[SINGA-186] Create Python Tensor class</li>
	<li>[SINGA-184] Add Cross Entropy loss computation</li>
	<li>[SINGA-183] Add the base classes for optimizer, constraint and regularizer</li>
	<li>[SINGA-180] Add Activation layer and Softmax layer</li>
	<li>[SINGA-178] Add Convolution layer and Pooling layer</li>
	<li>[SINGA-176] Add loss and metric base classes</li>
	<li>[SINGA-174] Add Batch Normalization layer and Local Response Nomalization layer.</li>
	<li>[SINGA-170] Add Dropout layer and CudnnDropout layer.</li>
	<li>[SINGA-169] Add base Layer class for V1.0</li>
	</ul>
	</li>
	</ul>
	<ul class="simple">
	<li>Examples<ul>
	<li>[SINGA-232] Alexnet on Imagenet</li>
	<li>[SINGA-231] Batchnormlized VGG model for cifar-10</li>
	<li>[SINGA-228] Add Cpp Version of Convolution and Pooling layer</li>
	<li>[SINGA-227] Add Split and Merge Layer and add ResNet Implementation</li>
	</ul>
	</li>
	<li>Documentation<ul>
	<li>[SINGA-239] Transfer documentation files of v0.3.0 to github</li>
	<li>[SINGA-238] RBM on mnist</li>
	<li>[SINGA-225] Documentation for installation and Cifar10 example</li>
	<li>[SINGA-223] Use Sphinx to create the website</li>
	</ul>
	</li>
	<li>Tools for compilation and some utility code<ul>
	<li>[SINGA-229] Complete install targets</li>
	<li>[SINGA-221] Support for Travis-CI</li>
	<li>[SINGA-217] build python package with setup.py</li>
	<li>[SINGA-216] add jenkins for CI support</li>
	<li>[SINGA-212] Disable the compilation of libcnmem if USE_CUDA is OFF</li>
	<li>[SINGA-195] Channel for sending training statistics</li>
	<li>[SINGA-185] Add CBLAS and GLOG detection for singav1</li>
	<li>[SINGA-181] Add NVCC supporting for .cu files</li>
	<li>[SINGA-177] Add fully cmake supporting for the compilation of singa_v1</li>
	<li>[SINGA-172] Add CMake supporting for Cuda and Cudnn libs</li>
	</ul>
	</li>
	</ul>


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