From 6e65bb640a5430b3043b75759c29b0a66808e45c Mon Sep 17 00:00:00 2001 From: Siju Date: Thu, 13 Dec 2018 12:09:44 +0530 Subject: [PATCH] Update README.md chnage to change --- tensorflow/lite/java/ovic/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tensorflow/lite/java/ovic/README.md b/tensorflow/lite/java/ovic/README.md index 368c486f4f1..a50d3130c0b 100644 --- a/tensorflow/lite/java/ovic/README.md +++ b/tensorflow/lite/java/ovic/README.md @@ -137,7 +137,7 @@ If you are adding a detection model, simply modify `modelPath` and `testImagePat * Adjust the benchmark parameters when needed: -You can chnage the length of each experiment, and the processor affinity below. `BIG_CORE_MASK` is an integer whose binary encoding represents the set of used cores. This number is phone-specific. For example, Pixel 2 has 8 cores: the 4 little cores are represented by the 4 less significant bits, and the 4 big cores by the 4 more significant bits. Therefore a mask value of 16, or in binary `00010000`, represents using only the first big core. The mask 32, or in binary `00100000` uses the second big core and should deliver identical results as the mask 16 because the big cores are interchangeable. +You can change the length of each experiment, and the processor affinity below. `BIG_CORE_MASK` is an integer whose binary encoding represents the set of used cores. This number is phone-specific. For example, Pixel 2 has 8 cores: the 4 little cores are represented by the 4 less significant bits, and the 4 big cores by the 4 more significant bits. Therefore a mask value of 16, or in binary `00010000`, represents using only the first big core. The mask 32, or in binary `00100000` uses the second big core and should deliver identical results as the mask 16 because the big cores are interchangeable. ``` /** Wall time for each benchmarking experiment. */