import okhttp3.internal.SuppressSignatureCheck
import okhttp3.internal.platform.Platform

/**
 * Example of using a hardware key to perform client auth.
 * Prefer recent JDK builds, and results are temperamental to slight environment changes.
 * Different instructions and configuration may be required for other hardware devices.
 *
 * Using a yubikey device as a SSL key store.
 * https://lauri.võsandi.com/2017/03/yubikey-for-ssh-auth.html
 *

       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).
     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   
   -----------------------------------------------------------------------------------------------
   
   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
   

# MinIO Erasure Code Quickstart Guide [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io)

MinIO protects data against hardware failures and silent data corruption using erasure code and checksums. With the highest level of redundancy, you may lose up to half (N/2) of the total drives and still be able to recover the data.

## What is Erasure Code?

TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

### Tenant isolation

Since any tenants or users providing models, graphs or checkpoints can execute
code in context of the TensorFlow service, it is important to design isolation

# Decommissioning

Decommissiong is a mechanism in MinIO to drain older pools (usually with old hardware) and migrate the content from such pools to a newer pools (usually better hardware). Decommissioning spreads the data across all pools - for example, if you decommission `pool1`, all the data from `pool1` spreads across `pool2` and `pool3`.

## Features

# Create hardware engg org unit
dn: ou=hwengg,dc=min,dc=io
objectClass: organizationalUnit
ou: hwengg

# Create people sub-org
dn: ou=people,ou=hwengg,dc=min,dc=io
objectClass: organizationalUnit
ou: people

# Create Alice, Bob and Cody in hwengg
dn: uid=alice1,ou=people,ou=hwengg,dc=min,dc=io
objectClass: inetOrgPerson
cn: Alice Smith
sn: Smith
uid: alice1
mail: ******@****.***
userPassword: {SSHA}Yeh2/IV/q/HjG2yzN3YdE9CAF3EJFCLu

# Create hardware engg org unit
dn: ou=hwengg,dc=min,dc=io
objectClass: organizationalUnit
ou: hwengg

# Create people sub-org
dn: ou=people,ou=hwengg,dc=min,dc=io
objectClass: organizationalUnit
ou: people

# Create Alice, Bob and Cody in hwengg
dn: uid=alice1,ou=people,ou=hwengg,dc=min,dc=io
objectClass: inetOrgPerson
cn: Alice Smith
sn: Smith
uid: alice1
mail: ******@****.***
userPassword: {SSHA}Yeh2/IV/q/HjG2yzN3YdE9CAF3EJFCLu

> NOTE:  While MinIO does not implement an upper boundary on buckets, your cluster's hardware has natural limits that depend on the workload and its scaling patterns. We strongly recommend [MinIO SUBNET](https://min.io/pricing) for architecture and sizing guidance for your production use case.

				// Following check is for situations
				// when Writes() scale higher than Reads()
				// - practically speaking this never happens
				// and should never happen - however it has
				// been seen recently due to hardware issues
				// causes Reads() to go slower than Writes().
				//
				// Send such results anyways as this shall
				// expose a problem underneath.
				if totalPut > throughputHighestPut {

import jcifs.internal.smb2.rdma.RdmaNegotiateResponse;

/**
 * TCP-based RDMA connection implementation.
 *
 * Uses regular TCP sockets to simulate RDMA operations.
 * This provides a fallback when real RDMA hardware is not available.
 */
public class TcpRdmaConnection extends RdmaConnection {

    private static final Logger log = LoggerFactory.getLogger(TcpRdmaConnection.class);

    private SocketChannel socketChannel;