Vertex AI での TensorFlow を使用した機械学習 のレビュー

Perez Jacob · 1年以上前にレビュー済み

Sharma Shantanu · 1年以上前にレビュー済み

Tirchas Panagiotis · 1年以上前にレビュー済み

unable finish this lab last step due to CalledProcessError: Command 'b'# note TF_VERSION set in 1st cell, but ENDPOINT_NAME is being changed\n# TF_VERSION=2-6\nENDPOINT_NAME=flights_xai\nTIMESTAMP=$(date +%Y%m%d-%H%M%S)\nMODEL_NAME=${ENDPOINT_NAME}-${TIMESTAMP}\nEXPORT_PATH=$(gsutil ls ${OUTDIR}/export | tail -1)\necho $EXPORT_PATH\n# create the model endpoint for deploying the model\nif [[ $(gcloud beta ai endpoints list --region=$REGION \\\n --format=\'value(DISPLAY_NAME)\' --filter=display_name=${ENDPOINT_NAME}) ]]; then\n echo "Endpoint for $MODEL_NAME already exists"\nelse\n # create model endpoint\n echo "Creating Endpoint for $MODEL_NAME"\n gcloud beta ai endpoints create --region=${REGION} --display-name=${ENDPOINT_NAME}\nfi\nENDPOINT_ID=$(gcloud beta ai endpoints list --region=$REGION \\\n --format=\'value(ENDPOINT_ID)\' --filter=display_name=${ENDPOINT_NAME})\necho "ENDPOINT_ID=$ENDPOINT_ID"\n# delete any existing models with this name\nfor MODEL_ID in $(gcloud beta ai models list --region=$REGION --format=\'value(MODEL_ID)\' --filter=display_name=${MODEL_NAME}); do\n echo "Deleting existing $MODEL_NAME ... $MODEL_ID "\n gcloud ai models delete --region=$REGION $MODEL_ID\ndone\n# upload the model using the parameters docker conatiner image, artifact URI, explanation method, \n# explanation path count and explanation metadata JSON file `explanation-metadata.json`. \n# Here, you keep number of feature permutations to `10` when approximating the Shapley values for explanation.\ngcloud beta ai models upload --region=$REGION --display-name=$MODEL_NAME \\\n --container-image-uri=us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.${TF_VERSION}:latest \\\n --artifact-uri=$EXPORT_PATH \\\n --explanation-method=sampled-shapley --explanation-path-count=10 --explanation-metadata-file=explanation-metadata.json\nMODEL_ID=$(gcloud beta ai models list --region=$REGION --format=\'value(MODEL_ID)\' --filter=display_name=${MODEL_NAME})\necho "MODEL_ID=$MODEL_ID"\n# deploy the model to the endpoint\ngcloud beta ai endpoints deploy-model $ENDPOINT_ID \\\n --region=$REGION \\\n --model=$MODEL_ID \\\n --display-name=$MODEL_NAME \\\n --machine-type=n1-standard-2 \\\n --min-replica-count=1 \\\n --max-replica-count=1 \\\n --traffic-split=0=100\n'' returned non-zero exit status 1.

Chang Hsin-Wen · 1年以上前にレビュー済み

There are no resources available at the specified region to complete the lab.

García Nava José Luis · 1年以上前にレビュー済み

Imaeda Takashi · 1年以上前にレビュー済み

I could not create the notebook instance: I got an error saying that not enough resources were availaible

Spalla Davide · 1年以上前にレビュー済み

Initial instructions to do with creating the notebook are out of date. The region you're instructed to use didn't work. Other instructions are out of date. It's more a series of things to paste in than anything instructive of what you're doing and why

Robinson Llewellyn · 1年以上前にレビュー済み

임 규보 · 1年以上前にレビュー済み

Balliva Pablo · 1年以上前にレビュー済み

Unable to create the notebook

El Helou Georges · 1年以上前にレビュー済み

Azhar (azharthegeek) Muhammad · 1年以上前にレビュー済み

unable find TensorFlow Enterprise 2.6 under Vertex AI workbench

Chang Hsin-Wen · 1年以上前にレビュー済み

Riggs Cait · 1年以上前にレビュー済み

Theres not enough ressources to do this Lab! It was step 1 and encountered the first error... sad.

Jusufovic Amar · 1年以上前にレビュー済み

could not deploy the instance on us central becaouse of lack of resources in such location.

Miguel Tapia García Jorge · 1年以上前にレビュー済み

I could access my model endpoint but the checks did not work at Task 6.

Rajan Vijay · 1年以上前にレビュー済み

there were technical issues at first with setting up lab environment, took like 30 mins to do so

Shevardenidze Georgy · 1年以上前にレビュー済み

R. Pasia Erwin · 1年以上前にレビュー済み

Too many bugs

Cardoso Danilo · 1年以上前にレビュー済み

ENVIRONMENT ISSUES

Tawde Apurva · 1年以上前にレビュー済み

very bad not working

Gupta Akash · 1年以上前にレビュー済み

Grandi Sauro · 1年以上前にレビュー済み

Merezhko Nikita · 1年以上前にレビュー済み

Raghavan Pradheepan · 1年以上前にレビュー済み