AWS-Marketplace Python (#1056)

* aws-marketplace python flow

* edit readme

* edit readme

examples/aws-marketplace/README.md

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+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
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+software distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+
+# **Getting Started With DeepSparse via the AWS Marketplace**
+
+Neural Magic’s DeepSparse is an inference runtime that can be deployed directly from the AWS Marketplace. DeepSparse supports more than 60 different EC2 instance types and sizes, allowing you to quickly deploy the infrastructure that works best for your use case, based on cost and performance.
+
+An EC2 instance integrated with DeepSparse can be launched via the AWS console or programmatically via Python. For the console workflow, follow the guide in our [blog](https://neuralmagic.com/blog/neural-magics-deepsparse-inference-runtime-now-available-in-the-aws-marketplace/). If you are interested in configuring and launching an instance with DeepSparse in Python, follow the step-by-step guide below. 
+
+You will need access to the [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) version 2.X that is [configured](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-quickstart.html) and the [Boto3](https://github.com/boto/boto3) library.
+
+
+## Step 1: Subscribe to DeepSparse
+[Subscribe](https://aws.amazon.com/marketplace/pp/prodview-zx6s55xbdjgoa) to the DeepSparse Inference Runtime from the AWS Marketplace.
+
+
+## Step 2: Configure your DeepSparse Runtime
+
+Once you click *Continue to Subscribe*, you are directed to a page to complete selections for: 
+
+- Fulfillment option 
+- Software version 
+- AWS Region
+
+
+At this point, you may continue the instance configuration in the AWS console by clicking the *Continue to Launch* button or by running the following code snippet on your local machine. This code snippet launches an EC2 instance and returns the Public IPv4 DNS so you can SSH into the instance after it finishes staging. 
+
+```python
+import boto3
+
+ec2_client = boto3.client('ec2')
+
+def launch_ec2_instance(instance_name: str, image_id: str):
+
+    response = ec2_client.run_instances(
+        ImageId=image_id,  # Replace with your desired AMI ID
+        InstanceType='c6i.xlarge',  # Replace with your desired instance type
+        MinCount=1,
+        MaxCount=1,
+        SecurityGroupIds=['<sg-xxxxxxx>'],  # Replace with your desired security group ID(s)
+        SubnetId='<subnet-xxxxxxxx>',  # Replace with your desired subnet ID
+        KeyName='<key-name>',  # Replace with your key pair name
+    )
+
+    instance_id = response['Instances'][0]['InstanceId']
+    ec2_client.create_tags(Resources=[instance_id], Tags=[{'Key': 'Name', 'Value': instance_name}])
+    return instance_id
+
+
+def wait_until_running(instance_id):
+    waiter = ec2_client.get_waiter('instance_running')
+    waiter.wait(InstanceIds=[instance_id])
+    print("Instance is running.")
+
+
+def get_public_ipv4_dns(instance_id):
+    response = ec2_client.describe_instances(InstanceIds=[instance_id])
+    public_ipv4_dns = response['Reservations'][0]['Instances'][0]['PublicDnsName']
+    print("Public IPv4 DNS:", public_ipv4_dns)
+    return public_ipv4_dns
+
+
+if __name__ == "__main__":
+    instance_id = launch_ec2_instance('DeepSparse', 'ami-036b9037247505961')
+    wait_until_running(instance_id)
+    get_public_ipv4_dns(instance_id)
+
+```
+
+**The AMI ID *ami-036b9037247505961* used in the example above assumes a configuration of software `version 1.3.2` in the `US East (N. Virginia)` region. If you prefer to enter different values in the configuration page, use the AMI id shown  and paste it into the code snippet**:
+
+![Alt Text](./img/ami-pic.png)
+
+
+If you need guidance on how to select existing Security Group ids, run the following AWS CLI command and paste the appropriate `GroupId` value in the `SecurityGroupIds` argument.
+
+```bash
+aws ec2 describe-security-groups --query 'SecurityGroups[*].{GroupName: GroupName, GroupId: GroupId, VpcId: VpcId}'
+```
+If you need guidance on how to select existing Subnet ids, run the following AWS CLI command, and paste the appropriate id in the `SubnetId` argument.
+
+```bash
+aws ec2 describe-subnets --filters "Name=vpc-id,Values=vpc-042da23c75d628d10" "Name=default-for-az,
+Values=true" --query 'Subnets[].SubnetId'
+```
+
+## **Step 3: SSH Into the Instance**
+
+After running the code snippet, your Public IPv4 DNS will be printed out in theterminal and should look like this: `ec2-18-234-83-194.compute-1.amazonaws.com`. Pass the IPv4 into the following CLI command to SSH into your running instance:
+
+```bash
+ssh -i path/to/your/sshkey.pem ec2-user@public-ipv4-dns
+```
+
+## **Step 4: Run DeepSparse**
+
+Once logged into the instance, you can use the DeepSparse features such as benchmarking, pipelines, and the server. Here's an example of benchmarking a pruned-quantized version of BERT trained on SQuAD:
+
+```bash
+deepsparse.benchmark
+zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned95_obs_quant-none -i [64,128] -b 64 -nstreams 1 -s sync
+```