*TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

    # the default MCP is assumed.
    configSource:
      subscribedResources: []
    # The following is used to limit how long a sidecar can be connected
    # to a pilot. It balances out load across pilot instances at the cost of
    # increasing system churn.
    keepaliveMaxServerConnectionAge: 30m
    # Additional labels to apply to the deployment.
    deploymentLabels: {}
    ## Mesh config settings

	MOVD	$-0x10000(RSP), RSP           // MOVD	$-65536(RSP), RSP           // ff4340d1
	MOVW	R1, R2
	MOVW	ZR, R1
	MOVW	R1, ZR
	MOVD	R1, R2
	MOVD	ZR, R1

// store and load
//
// LD1/ST1
	VLD1	(R8), [V1.B16, V2.B16]                          // 01a1404c
	VLD1.P	(R3), [V31.H8, V0.H8]                           // 7fa4df4c
	VLD1.P	(R8)(R20), [V21.B16, V22.B16]                   // 15a1d44c

                        description: Maximum % of hosts in the load balancing pool
                          for the upstream service that can be ejected.
                        format: int32
                        type: integer
                      minHealthPercent:
                        description: Outlier detection will be enabled as long as
                          the associated load balancing pool has at least min_health_percent

  command: server http://minio{1...4}/data{1...3}
  env_file:
    - ./minio.env
  expose:
    - "9000"
    - "9001"

# starts 4 docker containers running minio server instances.
# using nginx reverse proxy, load balancing, you can access
# it through port 9000.
services:
  minio1:
    <<: *minio-common
    hostname: minio1
    volumes:
      - data1-1:/data1
      - data1-2:/data2
      - data1-3:/data3

  healthcheck:
    test: ["CMD", "mc", "ready", "local"]
    interval: 5s
    timeout: 5s
    retries: 5

# starts 4 docker containers running minio server instances.
# using nginx reverse proxy, load balancing, you can access
# it through port 9000.
services:
  minio1:
    <<: *minio-common
    hostname: minio1
    volumes:
      - cdata1-1:/cdata1
      - cdata1-2:/cdata2

  minio2:

//
// floating point conditional branch
//
//	LBRA rel
label4:
	BFPT	1(PC)	// BFPT 1(PC)			// 4501000100000000
	BFPT	label4	// BFPT 24			// 4501fffd00000000

//inst:
//
// load ints and bytes
//
//	LMOVV rreg ',' rreg
//	{
//		outcode(int($1), &$2, 0, &$4);
//	}
	MOVV	R25, R17	// 00198825
	MOVV	R1, R2		// 00011025
	MOVV	LO, R1		// 00000812
	MOVV	HI, R1		// 00000810

    # the default MCP is assumed.
    configSource:
      subscribedResources: []

    # The following is used to limit how long a sidecar can be connected
    # to a pilot. It balances out load across pilot instances at the cost of
    # increasing system churn.
    keepaliveMaxServerConnectionAge: 30m

    # Additional labels to apply to the deployment.
    deploymentLabels: {}

    ## Mesh config settings

	LAX	R7, R8, (R9)          // eb87900000f7
	LAXG	R10, R11, (R12)       // ebbac00000e7
	LAO	R1, R2, (R3)          // eb21300000f6
	LAOG	R4, R5, (R6)          // eb54600000e6

	// load and store multiple
	LMG	n-8(SP), R3, R4         // eb34f0100004
	LMG	-5(R5), R3, R4          // eb345ffbff04
	LMY	n-8(SP), R3, R4         // 9834f010
	LMY	4096(R1), R3, R4        // eb3410000198

s-for-loadbalancer-service ## #loadBalancerSourceRa: # - 10.10.10.0/24 loadBalancerSourceRa: [] ## service.externalTrafficPolic minio service external traffic policy ## ref http://kubernetes.io/docs/tasks/access-application-cluster/create-external-load-balancer/#preserving-the-client-source-ip ## externalTrafficPolic: Cluster ## Configure Ingress based on the documentation here: https://kubernetes.io/docs/concepts/services-networking/ingress/ ## ingress: enabled: false ingressClassName: ~ labels:...