scratch_container_trainer.ipynb

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   "source": [
    "from sagemaker.estimator import Estimator\n",
    "\n",
    "job_name = \"scratch-container-ctr-prediction-\" + strftime(\"%Y%m%d-%H-%M-%S\", gmtime())\n",
    "\n",
    "hyperparameters = {\"rank\": 7, \"n_iter\": 12}\n",
    "\n",
    "enable_local_mode_training=False\n",
    "if enable_local_mode_training:\n",
    "    train_instance_type = \"local\"\n",
    "    inputs = {\"train\": f\"file://{train_file}\", \"test\": f\"file://{test_file}\"}\n",
    "else:\n",
    "    train_instance_type = \"ml.m5.large\"\n",
    "    inputs = {\"train\": s3_train_data, \"test\": s3_test_data}\n",
    "    \n",
    "estimator = Estimator(image_uri=f'{account}.dkr.ecr.ap-northeast-1.amazonaws.com/ctr-prediction-scratch-container:latest',\n",
    "                      role=role,\n",
    "                      instance_count=1,\n",
    "                      instance_type=train_instance_type,\n",
    "                      output_path=output_location,\n",
    "                      hyperparameters=hyperparameters,\n",
    "                      base_job_name=job_name)\n",
    "\n",
    "estimator.fit(inputs)\n"
   ]
  }
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