revilokeb
revilokeb
/ gist:d9d90998edd7c1dc6ac7
Created
March 18, 2016 11:17
Packer example for building deepdetect
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| { | |
| "variables": { | |
| "aws_access_key": "", | |
| "aws_secret_key": "" | |
| }, | |
| "builders": [{ | |
| "type": "amazon-ebs", | |
| "access_key": "{{user `aws_access_key`}}", | |
| "secret_key": "{{user `aws_secret_key`}}", | |
| "region": "eu-west-1", |
revilokeb
/ create_new_deepdetect_AMI.txt
Last active
April 3, 2016 17:58
Shell script to automatically create public AMI deepdetect_revilokeb_TIMESTAMP
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| #!/bin/bash | |
| PATH_TO_PACKER/packer build -var 'aws_access_key=MY_AWS_KEY' -var 'aws_secret_key=MY_AWS_SECRET_KEY' PATH_TO_PACKER_JSON/dede.json 2>&1 | sudo tee PATH_TO_OUTPUT/output.txt | |
| ami_name=`tail -2 PATH_TO_OUTPUT/output.txt | head -2 | awk 'match($0, /ami-.*/) { print substr($0, RSTART, RLENGTH) }'` | |
| aws ec2 modify-image-attribute --image-id $ami_name --launch-permission "{\"Add\":[{\"Group\":\"all\"}]}" |
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| { | |
| "variables": { | |
| "aws_access_key": "", | |
| "aws_secret_key": "" | |
| }, | |
| "builders": [{ | |
| "type": "amazon-ebs", | |
| "access_key": "{{user `aws_access_key`}}", | |
| "secret_key": "{{user `aws_secret_key`}}", | |
| "region": "eu-west-1", |
revilokeb
/ inception_resnet_v2_train_val_2ndtry.txt
Created
April 24, 2016 19:44
Caffe train_val for learning inception-resnet-v2 - 2ndtry
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| name: "Inception_Resnet2_Imagenet" | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { |
revilokeb
/ inception_resnet_v2_solver_2ndtry.txt
Created
April 24, 2016 19:47
Caffe solver for learning inception-resnet-v2 - 2ndtry
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| net: "/inception_resnet_v2_train_test_2ndtry.prototxt" | |
| test_iter: 25000 | |
| test_interval: 40000 | |
| test_initialization: false | |
| iter_size: 1 | |
| type: "RMSProp" | |
| rms_decay: 0.9 | |
| delta: 1.0 | |
| display: 500 | |
| average_loss: 1000 |
revilokeb
/ wide_residual_net_28_10_caffe
Created
June 7, 2016 21:01
Caffe train_val for training wide residual net wrn_28_10 on CIFAR10
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| name: "wrn_28_10" | |
| layer { | |
| name: "Data1" | |
| type: "Data" | |
| top: "Data1" | |
| top: "Data2" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { |
revilokeb
/ wide_residual_net_28_10_solver_caffe
Created
June 7, 2016 21:05
Caffe solver for training wide residual net wrn_28_10
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| net: "MY_PATH/wrn_28_10_train_val.prototxt" | |
| test_iter: 157 | |
| test_interval: 390 | |
| test_initialization: false | |
| iter_size: 1 | |
| #type: "RMSProp" | |
| #rms_decay: 0.9 | |
| #delta: 1.0 | |
| type: "Nesterov" | |
| display: 390 |
revilokeb
/ wide_residual_net_28_10_dropout_caffe
Created
June 10, 2016 05:59
caffe train_val for training wide residual nets with dropout wrn_28_10_dropout
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| name: "wrn_28_10_dropout" | |
| layer { | |
| name: "Data1" | |
| type: "Data" | |
| top: "Data1" | |
| top: "Data2" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { |
revilokeb
/ setup_tf_serving_cuda_docker_v0.1
Last active
March 14, 2018 23:57
Setting up Tensorflow Serving with CUDA 7.5 / cuDNN5 on Docker - error "missing dependency ... eigen3/Eigen/Core..."
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| # Create docker image with TF serving on GPU | |
| # Ubuntu 14.04 LTS with nvidia-docker (https://github.com/NVIDIA/nvidia-docker) | |
| # docker: docker bash | |
| # host: bash on host machine | |
| #host, pull nvidia-docker latest | |
| nvidia-docker pull nvidia/cuda | |
| #docker, start docker bash | |
| nvidia-docker run --rm -ti -v /myhosthome:/mydockerhome nvidia/cuda:latest bash |
revilokeb
/ setup_tf_serving_cuda_docker_v0.2
Last active
October 16, 2017 06:42
Setting up Tensorflow Serving with CUDA 7.5 / cuDNN5 on Docker based on TF Serving commit from May 2016
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| # Create docker image with TF serving on GPU | |
| # Ubuntu 14.04 LTS with nvidia-docker (https://github.com/NVIDIA/nvidia-docker) | |
| # docker: docker bash | |
| # host: bash on host machine | |
| #host, pull nvidia-docker latest | |
| nvidia-docker pull nvidia/cuda | |
| #docker, start docker bash | |
| nvidia-docker run --rm -ti -v /myhosthome:/mydockerhome nvidia/cuda:latest bash |
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