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"""
This script is a simple FashionMNIST training script which uses MXNet's.
It has been orchestrated with SageMaker Debugger hook to allow saving tensors during training.
Here, the hook has been created using its constructor to allow running this locally for your experimentation.
When you want to run this script in SageMaker, it is recommended to create the hook from json file.
Please see scripts in either /examples/tensorflow/sagemaker_byoc or /examples/tensorflow/sagemaker_official_container
folder based on your use case.
"""
# Standard Library
import argparse

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#!/bin/bash

###
# 
# The following script queries AWS CloudTrail for any events matching $USERNAME which occurred with the permissions
# associated with $ROLE_ARN.  All events that have occcurred as of $START_TIME (Unix timestamp in seconds) will
# be retrieved and the IAM actions of those events printed to STDOUT in a sorted and de-duplicated list.
#
# Sample Output:
#

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#!/bin/bash
#
# This script takes about 5 minutes to run and will delay the availability of
# your SageMaker notebook.
# v1.3, release 05may2020
#
# THIS SCRIPT INSTALLS:
# - THEIA IDE w/ Jupyter Server proxy
# - UPGRADES JUPYTERLAB
# - INSTALL VOILA (https://github.com/voila-dashboards/voila)

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#!/bin/bash

set -e

sudo -u ec2-user -i <<'EOP'
## INSTALL THEIA IDE FROM SOURCE
EC2_HOME=/home/ec2-user
mkdir ${EC2_HOME}/theia && cd ${EC2_HOME}/theia
### begin by installing NVM, NodeJS v10, and Yarn
curl -o- https://raw.githubusercontent.com/creationix/nvm/v0.33.5/install.sh | bash

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AWSTemplateFormatVersion: 2010-09-09
Description: Amazon EKS - Node Group
Parameters:
  KeyName:
    Description: The EC2 Key Pair to allow SSH access to the instances
    Type: 'AWS::EC2::KeyPair::KeyName'
  NodeImageId:
    Description: AMI id for the node instances.
    Type: 'AWS::EC2::Image::Id'
  NodeInstanceType:

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###
#
# CloudFormation Template to create EKS Worker Nodes without access to an IGW
#
# The following CloudFormation template is based upon the AWS-provided CloudFormation template for creating 
# EKS worker nodes in your VPC.  It differs in that it has user-data modified to configure a node to operate 
# within a VPC that has no IGW.  
#
# To use this template you will need a VPC with an EKS cluster already deployed and private access enabled. 
# You will also need a web proxy configured to allow the worker nodes access to the AWS EKS service API.  This

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{
    "TrainingJobName": "cli-t-job",
    "HyperParameters": {
        "sagemaker_submit_directory": "s3://sagemaker-eu-west-2-776347453069/sagemaker-scikit-learn-2019-06-19-13-21-02-471/source/sourcedir.tar.gz",
        "sagemaker_program": "sklearn_abalone_featurizer.py",
        "sagemaker_enable_cloudwatch_metrics": "false",
        "sagemaker_container_log_level": "20",
        "sagemaker_job_name": "sagemaker-scikit-learn-2019-06-19-13-21-02-471",
        "sagemaker_region": "eu-west-2"
    },

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import pandas as pd
import numpy as np
import argparse
from sklearn import preprocessing
import pickle
import os
from io import StringIO
from sagemaker_containers.beta.framework import (
    content_types, encoders, env, modules, transformer, worker)

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##
## AMI created using 
## curl -sL https://rpm.nodesource.com/setup_11.x | bash -
## yum install -y git nodejs
## git clone https://github.com/socketio/socket.io.git
##
## cd socket.io
## npm install
## cd examples/chat
## npm install