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edit aws_marketplace/using-open-source-model-packages/pytorch-ic-model/using-image-classification-models.ipynb
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aws_marketplace/using-open-source-model-packages/pytorch-ic-model/using-image-classification-models.ipynb

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"\n",
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"This notebook is compatible only with those image classification model packages which this notebook is linked to.\n",
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"\n",
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"#### Pre-requisites:\n",
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"## Pre-requisites:\n",
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"1. **Note**: This notebook contains elements which render correctly in Jupyter interface. Open this notebook from an Amazon SageMaker Notebook Instance or Amazon SageMaker Studio.\n",
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"1. Ensure that IAM role used has **AmazonSageMakerFullAccess**\n",
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"1. To deploy this ML model successfully, ensure that:\n",
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" 1. **aws-marketplace:Subscribe** \n",
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" 2. or your AWS account has a subscription to this image classification model. If so, skip step: [Subscribe to the model package](#1.-Subscribe-to-the-model-package)\n",
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"\n",
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"#### Contents:\n",
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"## Contents\n",
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"1. [Subscribe to the model package](#1.-Subscribe-to-the-model-package)\n",
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"2. [Create an endpoint and perform real-time inference](#2.-Create-an-endpoint-and-perform-real-time-inference)\n",
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" 1. [Create an endpoint](#A.-Create-an-endpoint)\n",
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" 2. [Unsubscribe to the listing (optional)](#B.-Unsubscribe-to-the-listing-(optional))\n",
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" \n",
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"\n",
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"#### Usage instructions\n",
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"## Usage instructions\n",
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"You can run this notebook one cell at a time (By using Shift+Enter for running a cell).\n",
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"\n",
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"**Note** - This notebook requires you to follow instructions and specify values for parameters, as instructed."
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 1. Subscribe to the model package"
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"## 1. Subscribe to the model package"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 2. Create an endpoint and perform real-time inference"
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"## 2. Create an endpoint and perform real-time inference"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### A. Create an endpoint"
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"### A. Create an endpoint"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### B. Prepare input file for performing real-time inference\n",
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"### B. Prepare input file for performing real-time inference\n",
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"In this step, we will download class_id_to_label_mapping from S3 bucket. The mapping files has been downloaded from [TensorFlow](https://storage.googleapis.com/download.tensorflow.org/data/ImageNetLabels.txt). [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0)."
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]
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},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### C. Query endpoint that you have created with the opened images"
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"### C. Query endpoint that you have created with the opened images"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### D. Delete the endpoint"
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"### D. Delete the endpoint"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 3. Perform batch inference"
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"## 3. Perform batch inference"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 4. Clean-up"
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"## 4. Clean-up"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### A. Delete the model"
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"### A. Delete the model"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### B. Unsubscribe to the listing (optional)"
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"### B. Unsubscribe to the listing (optional)"
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]
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},
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{

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