tensorflow - machine learning framework

	Commit message (Collapse)	Author	Age
*	Complement cmake script to compile tensorflow with mkl and mkldnn on Windows ↵	Tang, Wenyi	2018-04-17
\| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \|	(#16936) * Add build batch for windows * Automaticaly find python, cuda, mkl runtimes in PATH * auto select cmake generator * Add external library mkldnn. Add options for mkl and mkldnn * fix syntax error in make.bat * Fix errorlevel syntex bug in make.bat * Add /arch:avx2 flags to enable avx2 on windows * Revert to keep `tensprflow_WIN_CPU_SIMD_OPTIONS` unchanged, add an option `tensorflow_ENABLE_MKL_SUPPORT` to include MKL compilation. Still specify SIMD flags by setting `tensorflow_WIN_CPU_SIMD_OPTIONS` to such as '/arch:AVX2' * Fix a mistake of CUDA path in make.bat * resolve conflict in mkl_cpu_allocator.h * Improve error detection * Use where /Q to detect cmd environment * fix "ELSE IF" the syntax error in make.bat * update README.md, wrap windows based codes by #ifdef _WIN32 * unistd.h is not needed in mkl_cpu_allocator.h any more in master branch * Remove inline of kMaxLimitStr, which causes compile error in VS2015 * Add static_cast in to fix compile error * remove make.bat * Removed make.bat description part
*	Adding Intel Conv2D kernel implementation alongwith required Graph passes	Niranjan Hasabnis	2017-02-27
	This commit contains 4 main components: 1) Intel-optimized kernel implementation for Conv2D op Implementation in kernels/mkl_conv_ops.* 2) Graph passes required to enable Conv2D optimized implementation Implementation in graph/mkl_. We also need a new op, MklToTf op. Its implementation is in kernels/mkl_tfconv_op.cc. 3) Utility functions used in kernel implementation Implementation is in common_runtime/mkl_layer_registry and util/mkl_util.h 4) BUILD changes for Conv2D, graph passes and utility functions