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Add region check for llama2 deployment notebook. (#2843)

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* Add region check for LLaMA2 deployment notebook.

* Lint
This commit is contained in:
dstnluong-google
2024-04-04 12:48:48 +00:00
committed by GitHub
parent d5b1b83d9a
commit 2f5eef2c17
1 changed files with 18 additions and 12 deletions
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notebooks/community/model_garden/model_garden_pytorch_llama2_deployment.ipynb
+18 -12
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@@ -117,9 +117,21 @@
"# prefer using your own GCS bucket, please change the value yourself below.\n",
"now = datetime.now().strftime(\"%Y%m%d%H%M%S\")\n",
"BUCKET_URI = \"gs://\" # @param {type:\"string\"}\n",
"assert BUCKET_URI.startswith(\"gs://\"), \"BUCKET_URI must start with `gs://`.\"\n",
"\n",
"if BUCKET_URI is None or BUCKET_URI.strip() == \"\" or BUCKET_URI == \"gs://\":\n",
" BUCKET_URI = f\"gs://{PROJECT_ID}-tmp-{now}\"\n",
" ! gsutil mb -l {REGION} {BUCKET_URI}\n",
"else:\n",
" assert BUCKET_URI.startswith(\"gs://\"), \"BUCKET_URI must start with `gs://`.\"\n",
" BUCKET_NAME = \"/\".join(BUCKET_URI.split(\"/\")[:3])\n",
" shell_output = ! gsutil ls -Lb {BUCKET_NAME} | grep \"Location constraint:\" | sed \"s/Location constraint://\"\n",
" bucket_region = shell_output[0].strip().lower()\n",
" if bucket_region != REGION:\n",
" raise ValueError(\n",
" \"Bucket region %s is different from notebook region %s\"\n",
" % (bucket_region, REGION)\n",
" )\n",
"print(f\"Using this GCS Bucket: {BUCKET_URI}\")\n",
"\n",
"STAGING_BUCKET = os.path.join(BUCKET_URI, \"temporal\")\n",
"MODEL_BUCKET = os.path.join(BUCKET_URI, \"llama2\")\n",
@@ -129,18 +141,12 @@
"print(\"Initializing Vertex AI API.\")\n",
"aiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=STAGING_BUCKET)\n",
"\n",
"# Gets the default BUCKET_URI and SERVICE_ACCOUNT if they were not specified by the user.\n",
"SERVICE_ACCOUNT = None\n",
"# Gets the default SERVICE_ACCOUNT.\n",
"shell_output = ! gcloud projects describe $PROJECT_ID\n",
"project_number = shell_output[-1].split(\":\")[1].strip().replace(\"'\", \"\")\n",
"SERVICE_ACCOUNT = f\"{project_number}-compute@developer.gserviceaccount.com\"\n",
"print(\"Using this default Service Account:\", SERVICE_ACCOUNT)\n",
"\n",
"# Create a unique GCS bucket for this notebook, if not specified by the user\n",
"if BUCKET_URI.strip().startswith(f\"gs://{PROJECT_ID}-tmp-\"):\n",
" ! gsutil mb -l {REGION} {BUCKET_URI}\n",
"\n",
"print(f\"Using this GCS Bucket: {BUCKET_URI}\")\n",
"\n",
"# Provision permissions to the SERVICE_ACCOUNT with the GCS bucket\n",
"BUCKET_NAME = \"/\".join(BUCKET_URI.split(\"/\")[:3])\n",
@@ -152,9 +158,9 @@
"# @markdown The original models from Meta are converted into the Hugging Face format for serving in Vertex AI.\n",
"# @markdown Accept the model agreement to access the models:\n",
"# @markdown 1. Open the [LLaMA2 model card](https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/139) from [Vertex AI Model Garden](https://cloud.google.com/model-garden).\n",
"# @markdown 2. Review the agreement on the model card page.\n",
"# @markdown 2. Review and accept the agreement in the pop-up window on the model card page. If you have previously accepted the model agreement, there will not be a pop-up window on the model card page and this step is not needed.\n",
"# @markdown 3. After accepting the agreement of LLaMA2, a `gs://` URI containing LLaMA2 pretrained and finetuned models will be shared.\n",
"# @markdown 4. Paste the link in the `VERTEX_AI_MODEL_GARDEN_LLAMA2` field below.\n",
"# @markdown 4. Paste the URI in the `VERTEX_AI_MODEL_GARDEN_LLAMA2` field below.\n",
"# @markdown 5. The LLaMA2 models will be copied into `BUCKET_URI`.\n",
"\n",
"\n",
@@ -339,7 +345,7 @@
" accelerator_count=accelerator_count,\n",
" max_model_len=max_model_len,\n",
")\n",
"# @markdown Please click \"Show Code\" to see more details."
"# @markdown Click \"Show Code\" to see more details."
]
},
{
@@ -388,7 +394,7 @@
"for prediction in response.predictions:\n",
" print(prediction)\n",
"\n",
"# @markdown Please click \"Show Code\" to see more details."
"# @markdown Click \"Show Code\" to see more details."
]
},
{