[VTA] Support for batched inference#3661
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jroesch merged 12 commits intoapache:masterfrom Jul 30, 2019
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Aug 9, 2019
* fix in IR pass to support padding on 6-d tensors * support for both N>1 and N==1 for padding * batch size > 1 tuning and base config * output formatting * batch conv2d * print all category results * revert to single-batch config * pick record best * fix conv test * improving reporting * address batching bug in fast simulator * fix
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* fix in IR pass to support padding on 6-d tensors * support for both N>1 and N==1 for padding * batch size > 1 tuning and base config * output formatting * batch conv2d * print all category results * revert to single-batch config * pick record best * fix conv test * improving reporting * address batching bug in fast simulator * fix
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Mar 29, 2020
* fix in IR pass to support padding on 6-d tensors * support for both N>1 and N==1 for padding * batch size > 1 tuning and base config * output formatting * batch conv2d * print all category results * revert to single-batch config * pick record best * fix conv test * improving reporting * address batching bug in fast simulator * fix
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This PR addresses some bugs that occur when setting
LOG_BATCHto a value greater than 0 (i.e. batch size greater than 1).In addition, TOPHUB schedules were updated: tlc-pack/tophub@102b9b4
And a bitstream was added to test batched inference in hardware: uwsampl/vta-distro@e28d9d5
To reproduce in sim, set
vta_config.jsonto:To run on
pynq, setTARGETtopynq.