From cd9bcb3ce254d6defc4cdd2604f1679a931edec7 Mon Sep 17 00:00:00 2001 From: jiahangxu Date: Mon, 27 Jun 2022 05:17:20 -0400 Subject: [PATCH] complete v2.0 test --- docs/builder/build_kernel_latency_predictor.md | 2 +- setup.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/builder/build_kernel_latency_predictor.md b/docs/builder/build_kernel_latency_predictor.md index 2f0dfc4e..b9ef140d 100644 --- a/docs/builder/build_kernel_latency_predictor.md +++ b/docs/builder/build_kernel_latency_predictor.md @@ -244,7 +244,7 @@ predictor, data = build_predictor_for_kernel( ) ``` -In the experiment of nn-Meter, we set `init_sample_num` as 1000, `finegrained_sample_num` as 10, `iteration` as 5, and `error_threshold` as 0.1. +In the experiment of nn-Meter, we set default `init_sample_num` as 1000, `finegrained_sample_num` as 10, `iteration` as 5, and `error_threshold` as 0.1. nn-Meter also provided a end-to-end method for users to build a series of general latency predictors, named `nn_meter.builder.build_latency_predictor`. This method will build predictors for all kernels in `/configs/predictorbuild_config.yaml` according to their corresponding parameters. The parameters includes `INIT_SAMPLE_NUM`, `FINEGRAINED_SAMPLE_NUM`, `ITERATION`, and `ERROR_THRESHOLD`. Here is an example: diff --git a/setup.py b/setup.py index 296ae736..c0696fbe 100644 --- a/setup.py +++ b/setup.py @@ -5,7 +5,7 @@ setup( name='nn-meter', - version='2.0a1', + version='2.0', description='nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices.', long_description = open('README.md', encoding='utf-8').read(), long_description_content_type = 'text/markdown',