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Makefile
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Makefile
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#INSTANCE_NAME := XXXX
#GCP_PROJECT_ID := XXXX
GCP_ZONE := us-east1-d
MACHINE_TYPE := n1-standard-8
ACCELERATOR := type=nvidia-tesla-k80,count=1
BOOT_DISK_SIZE := 200GB
DOCKER_IMAGE_GPU := tf-1.4-gpu
DOCKER_IMAGE_CPU := tf-1.4-cpu
JUPYTER_PORT := 18888
GCP_INSTANCE_SCOPES := default,bigquery,cloud-platform,storage-rw
create-instance: check-instance-name check-gcp-project-id check-gcp-zone
./bin/create-instance.sh \
$(INSTANCE_NAME) \
$(GCP_PROJECT_ID) \
$(GCP_ZONE) \
$(MACHINE_TYPE) \
$(ACCELERATOR) \
$(BOOT_DISK_SIZE) \
$(GCP_INSTANCE_SCOPES)
create-instance-cpu: check-instance-name check-gcp-project-id check-gcp-zone
./bin/create-instance-cpu.sh \
$(INSTANCE_NAME) \
$(GCP_PROJECT_ID) \
$(GCP_ZONE) \
$(MACHINE_TYPE) \
$(BOOT_DISK_SIZE) \
$(GCP_INSTANCE_SCOPES)
delete-instance: check-instance-name check-gcp-project-id check-gcp-zone
gcloud compute instances delete $(INSTANCE_NAME) --project $(GCP_PROJECT_ID) --zone $(GCP_ZONE)
run-jupyter: check-instance-name check-gcp-project-id check-gcp-zone
$(eval COMMAND := sudo nvidia-docker kill jupyter \
|| true \
&& sudo nvidia-docker run -it --rm -d -v /src:/src -p 8888:8888 \
--name jupyter yuiskw/google-cloud-deep-learning-kit:$(DOCKER_IMAGE_GPU))
./bin/execute-over-ssh.sh $(INSTANCE_NAME) $(GCP_PROJECT_ID) $(GCP_ZONE) "$(COMMAND)"
run-jupyter-cpu: check-instance-name check-gcp-project-id check-gcp-zone
$(eval COMMAND := sudo docker kill jupyter \
|| true \
&& sudo docker run -it --rm -d -v /src:/src -p 8888:8888 \
--name jupyter yuiskw/google-cloud-deep-learning-kit:$(DOCKER_IMAGE_CPU))
./bin/execute-over-ssh.sh $(INSTANCE_NAME) $(GCP_PROJECT_ID) $(GCP_ZONE) "$(COMMAND)"
upload-files: check-instance-name check-gcp-project-id check-gcp-zone check-from
gcloud compute scp $(FROM) $(INSTANCE_NAME):/src \
--project $(GCP_PROJECT_ID) \
--zone $(GCP_ZONE) \
--compress \
--recurse
download-outputs: check-instance-name check-gcp-project-id check-gcp-zone check-to
-mkdir -p "$(TO)"
gcloud compute scp $(INSTANCE_NAME):/src/outputs/* $(TO) \
--project $(GCP_PROJECT_ID) \
--zone $(GCP_ZONE) \
--recurse
pip-install: check-instance-name check-gcp-project-id check-gcp-zone
# Copy requirements.txt to your instance
gcloud compute scp ./requirements.txt $(INSTANCE_NAME):/src/requirements.txt \
--project $(GCP_PROJECT_ID) \
--zone $(GCP_ZONE)
# Pip install to Docker
$(eval COMMAND := sudo nvidia-docker exec jupyter pip install -r /src/requirements.txt)
./bin/execute-over-ssh.sh $(INSTANCE_NAME) $(GCP_PROJECT_ID) $(GCP_ZONE) "$(COMMAND)"
ssh-tunnel: check-instance-name check-gcp-project-id check-gcp-zone check-jupyter-port
gcloud compute ssh $(INSTANCE_NAME) \
--project $(GCP_PROJECT_ID) \
--zone $(GCP_ZONE) \
--ssh-flag="-L" \
--ssh-flag="$(JUPYTER_PORT):localhost:8888"
check-instance-name:
ifndef INSTANCE_NAME
$(error INSTANCE_NAME is undefined)
endif
check-gcp-project-id:
ifndef GCP_PROJECT_ID
$(error GCP_PROJECT_ID is undefined)
endif
check-gcp-zone:
ifndef GCP_ZONE
$(error GCP_ZONE is undefined)
endif
check-jupyter-port:
ifndef JUPYTER_PORT
$(error JUPYTER_PORT is undefined)
endif
check-from:
ifndef FROM
$(error FROM is undefined)
endif
check-to:
ifndef TO
$(error TO is undefined)
endif