projects/vision-ai-edge-platform/pipelines/segmentation/deeplabv3plus/notebooks/launch_trainer.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Launch a Visual Inspection AI Model Training Job\n",
    "\n",
    "Contributors: michaelmenzel@google.com"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Copyright 2024 Google LLC\n",
    "\n",
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    https://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define project id and location for the pipeline\n",
    "PROJECT_ID = 'visual-inspection-demo-2184'\n",
    "LOCATION = 'us-central1'\n",
    "\n",
    "# A staging bucket for the pipeline and training program\n",
    "STAGING_BUCKET='gs://viai-demo-data-us-central1/ml-trainings/viai-segmentation-deeplabv3'\n",
    "# The service account that the pipeline and training program acts as\n",
    "SERVICE_ACCOUNT = '1047381110578-compute@developer.gserviceaccount.com'\n",
    "\n",
    "# The dataset id in Vertex to use for model training\n",
    "DATASET_ID = '1850063553663336448'\n",
    "\n",
    "# Container image for the training program\n",
    "CONTAINER_LOCATION = 'us'\n",
    "CONTAINER_NAME = 'trainer'\n",
    "CONTAINER_REPO = 'visual-inspection-ml-training'\n",
    "CONTAINER_TAG = 'latest'\n",
    "CONTAINER_URI = f'{CONTAINER_LOCATION}-docker.pkg.dev/{PROJECT_ID}/{CONTAINER_REPO}/segmentation-deeplabv3plus-{CONTAINER_NAME}:{CONTAINER_TAG}'\n",
    "\n",
    "# Experiment to log metrics and parameters from the model training\n",
    "EXPERIMENT = f'{PROJECT_ID}-viai-segmentation-deeplabv3'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Install dependencies:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --upgrade -q google-cloud-aiplatform[autologging]==1.65.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import libraries and initialize the Vertex AI client:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "from google.cloud import aiplatform\n",
    "\n",
    "TIMESTAMP = datetime.now().strftime('%Y%m%d%H%M%S')\n",
    "JOB_NAME = f'{EXPERIMENT}-{TIMESTAMP}'\n",
    "\n",
    "aiplatform.init(project=PROJECT_ID, \n",
    "                location=LOCATION,\n",
    "                staging_bucket=STAGING_BUCKET)#, experiment=EXPERIMENT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Launch a custom job with the training container:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vertex_ai_custom_job = aiplatform.CustomContainerTrainingJob(\n",
    "    display_name=JOB_NAME,\n",
    "    container_uri=CONTAINER_URI,\n",
    "    model_serving_container_image_uri='us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-13:latest'\n",
    ")\n",
    "vertex_ai_custom_job.run(\n",
    "    machine_type='n1-standard-8',\n",
    "    replica_count=1,\n",
    "    accelerator_type = 'NVIDIA_TESLA_V100',\n",
    "    accelerator_count = 1,\n",
    "    dataset=aiplatform.ImageDataset(DATASET_ID, location=LOCATION),\n",
    "    annotation_schema_uri='gs://google-cloud-aiplatform/schema/dataset/annotation/image_segmentation_1.0.0.yaml',\n",
    "    args=[f'--experiment={EXPERIMENT}',\n",
    "          '--loss-function=dice_focal',\n",
    "          '--num-epochs=200',\n",
    "          '--batch-size=16',\n",
    "          '--patience-epochs=50'],\n",
    "    restart_job_on_worker_restart=True,\n",
    "    service_account=SERVICE_ACCOUNT,\n",
    "    sync=False\n",
    ")"
   ]
  }
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