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[HARDWARE] VTA Specialised Accelerator Stack #1423
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* [DOCS] Initial docs * update instruction
* code refactoring * code refactoring * code refactoring * code refactoring * fixing macro * refactoring, tests, makefile * style - making sure lint test pass * prefixed macros with VTA, fixed bugs
* VTA python library * Python unit tests * End to end example with Resnet18 * README instructions * Bug fixes
…e#20) * Hardware generation fixes/sweep, auto scheduling for VTA conv2d * Hardware generation fixes/sweep, auto scheduling for VTA conv2d * derive hw spec from config file * up to date hardware spec
* [RUNTIME] Simplify dynamic library and code path. * reword the readme
…gration. (apache#28) * Migrate to json based config. Move gemm test to integration. * temp checkin * checkin example json
apache#35) * removing programming out of end to end example for now * updating TOPI library to use gemm tensor intrinsic * bug fix, autoschedule in TOPI conv lib * removing the deprecated GEVM intrinsic * refactoring, fixed lint test * fix for integer division bug * python3 bug fix for non matching types due to float division * comment
* fix graph transform for batch dimension * fix * fix
* bug fix for new drivers in new PYNQ image v2.1 * updating instructions for resnet inference * updated the instructions for starting the RPC server * deriving host/port from env for unit tests
This PR introduces VTA, a custom deep learning accelerator back-end to VTA. Approved! |
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@tmoreau89 This PR need rebase merge and I will do this once get approved