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199 | 199 | " name=\"ProcessingInstanceCount\", default_value=1\n",
|
200 | 200 | ")\n",
|
201 | 201 | "\n",
|
202 |
| - "model_approval_status = ParameterString(\n", |
203 |
| - " name=\"ModelApprovalStatus\",\n", |
204 |
| - " default_value=\"PendingManualApproval\" # ModelApprovalStatus can be set to a default of \"Approved\" if you don't want manual approval.\n", |
205 |
| - ")\n", |
206 |
| - "\n", |
207 | 202 | "input_data = ParameterString(\n",
|
208 | 203 | " name=\"InputDataUrl\",\n",
|
209 | 204 | " default_value=s3_raw_data\n",
|
|
583 | 578 | " inference_instances=[\"ml.t2.medium\", \"ml.m5.large\"],\n",
|
584 | 579 | " transform_instances=[\"ml.m5.large\"],\n",
|
585 | 580 | " model_package_group_name=model_package_group_name,\n",
|
586 |
| - " approval_status=model_approval_status,\n", |
587 | 581 | " model_metrics=model_metrics,\n",
|
588 | 582 | " )\n",
|
589 | 583 | " \n",
|
|
677 | 671 | " name=pipeline_name,\n",
|
678 | 672 | " parameters=[\n",
|
679 | 673 | " processing_instance_count,\n",
|
680 |
| - " model_approval_status,\n", |
681 | 674 | " input_data,\n",
|
682 | 675 | " input_annotation,\n",
|
683 | 676 | " class_selection\n",
|
|
817 | 810 | "# ProcessingInstanceType=\"ml.m5.xlarge\",\n",
|
818 | 811 | "# TrainingInstanceCount=1,\n",
|
819 | 812 | "# TrainingInstanceType=\"ml.c5.4xlarge\",#\"ml.p3.2xlarge\",#\n",
|
820 |
| - " ModelApprovalStatus=\"PendingManualApproval\",\n", |
821 | 813 | " AnnotationFileName=\"classes.txt\",\n",
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822 | 814 | " ClassSelection=\"13, 17, 35, 36\"\n",
|
823 | 815 | " )\n",
|
|
909 | 901 | "kernelspec": {
|
910 | 902 | "display_name": "Python 3 (Data Science)",
|
911 | 903 | "language": "python",
|
912 |
| - "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/datascience-1.0" |
| 904 | + "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:eu-west-1:470317259841:image/datascience-1.0" |
913 | 905 | },
|
914 | 906 | "language_info": {
|
915 | 907 | "codemirror_mode": {
|
|
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