[구글 클라우드] TensorFlow 스케일링 - AI Platform Training 서비스 활용

 

(source : GCP qwiklabs)

- Jupyter Notebook 실습 코드  

e_ai_platform.html

0.30MB

 

- Jupyter Notebook 실습 코드 : 정답 포함

e_ai_platform_solution.html

0.31MB

 

 

TensorBoard 설정 + AI Platform Notebooks 생성

 

1.  Cloud Shell에서, TensorBoard를 지원하는 Cloud AI Platform Notebook 인스턴스를 생성

export IMAGE_FAMILY="tf-1-14-cpu" 
export ZONE="us-west1-b" 
export INSTANCE_NAME="tf-tensorboard-1" 
export INSTANCE_TYPE="n1-standard-4" 
gcloud compute instances create "${INSTANCE_NAME}" \ 
     --zone="${ZONE}" \ 
     --image-family="${IMAGE_FAMILY}" \ 
     --image-project=deeplearning-platform-release \ 
     --machine-type="${INSTANCE_TYPE}" \ 
     --boot-disk-size=200GB \ 
     --scopes=https://www.googleapis.com/auth/cloud-platform \ 
     --metadata="proxy-mode=project_editors"

 

2. Navigation Menu > AI Platform > Notebooks 클릭

 

3. 인스턴스 생성 : NEW INSTANCE 클릭 

- Tensorflow Enterprise 1.15 > Without GPUs 선택

 

4. 팝업창이 뜨면 딥러닝 VM 이름을 입력/확인 하고 Create 클릭

 

(VM 생성까지 2~3분 정도 소요될 수 있음)

 

5. Open JupyterLab 클릭 > JupyterLab Window가 새창으로 열림

 

 

Scaling TensorFlow with AI Platform Training Service

 

 

training-data-analyst > courses > machine_learning > deepdive > 03_tensorflow > labs > e_ai_platform 실행

(정답확인) training-data-analyst > courses > machine_learning > deepdive > 03_tensorflow > e_ai_platform