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# Install script of Caffe2 and Detectron on AWS EC2 | |
# | |
# Tested environment: | |
# - AMI: Deep Learning Base AMI (Ubuntu) Version 6.0 - ami-ce3673b6 (CUDA is already installed) | |
# - Instance: p3.2xlarge (V100 * 1) | |
# - Caffe2: https://github.com/pytorch/pytorch/commit/731273b8d61dfa2aa8b2909f27c8810ede103952 | |
# - Detectron: https://github.com/facebookresearch/Detectron/commit/cd447c77c96f5752d6b37761d30bbdacc86989a2 | |
# | |
# Usage: | |
# Launch a fresh EC2 instance, put this script on the /home/ubuntu/, and run the following command. |
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#include <iostream> | |
#include <random> | |
#include <chrono> | |
#include <x86intrin.h> | |
#include <cassert> | |
// Runtime evaluation for squared Eucliden distance functions | |
// - fvec_L2_sqr_ref: naive reference impl from Faiss | |
// - fvec_L2_sqr_sse: SSE impl from Faiss | |
// - fvec_L2_sqr_avx: AVX impl from Faiss |
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# Test for faiss with optuna using siftsmall data | |
# | |
# (1) install libs: | |
# $ pip install optuna | |
# $ conda install faiss-cpu -c pytorch | |
# | |
# (2) Put the following util scripts in the same directory | |
# https://github.com/matsui528/rii/blob/master/examples/benchmark/util.py | |
# | |
# (3) download siftsmall data |
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Host abci | |
HostName es1 | |
User aaaXXXXXxx | |
ProxyCommand ssh -W %h:%p [email protected] |
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name: Run python test on an EC2 GPU instance | |
on: [push] | |
jobs: | |
build: | |
runs-on: ubuntu-latest | |
steps: | |
- name: Configure AWS credentials | |
uses: aws-actions/configure-aws-credentials@v1 |