tensorflow - machine learning framework

	Commit message (Collapse)	Author	Age
*	[XLA] Convert XLA to use xla::se as a namespace alias for ::stream_executor.	Justin Lebar	2018-04-17
\| \| \| \|	PiperOrigin-RevId: 193301997
*	Reset the DAZ bit when entering the XLA CPU/GPU compiler	Sanjoy Das	2018-02-16
\| \| \| \| \| \| \| \| \| \|	In an ideal world this won't make a difference since the compiler should be disciplined about not leaking host-level optimization artifacts into generated code. However, I think this provides some defense-in-depth in preventing non-obvious denormal behavior on the host side from messing up floating point constants etc. we want to embed into generated code. PiperOrigin-RevId: 186061140
*	Error out when building XLA's CPU and GPU backends with fast-math	Sanjoy Das	2018-02-15
\| \| \| \| \| \| \| \| \| \|	In an ideal world this won't make a difference since the compiler should be disciplined about not leaking host-level optimization artifacts into generated code. However, I think this provides some defense-in-depth in preventing fast-math optimization on the host side from messing up floating point constants etc. we want to embed into generated code. PiperOrigin-RevId: 185941549
*	[XLA] Add a DeviceAllocator* argument to compilation.	Justin Lebar	2018-01-26
\| \| \| \| \| \| \| \|	In a later change, the GPU backend will use this allocator to reserve scratch memory when trying out different convolution algorithms during compilation. PiperOrigin-RevId: 183469579
*	Add a Compiler::BuildExecutable interface that compiles the given Hlo module ↵	A. Unique TensorFlower	2017-11-17
\| \| \| \| \| \|	without optimizations. PiperOrigin-RevId: 176158846
*	[XLA:CPU/GPU] Implement multi-module compilation for the CPU and GPU backends	Sanjoy Das	2017-11-13
	For CPU and GPU this is a simple wrapper around the single-module Compile method since the CPU and GPU backends do not perform cross-module optimizations and analyses. PiperOrigin-RevId: 175631791