*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.

	errInvalidTrimArg           = errors.New("Trim argument is invalid - this should not happen")
	errInvalidSubstringIndexLen = errors.New("Substring start index or length falls outside the string")
)

const (
	percent    rune = '%'
	underscore rune = '_'
	runeZero   rune = 0
)

func evalSQLLike(text, pattern string, escape rune) (match bool, err error) {
	s := []rune{}

			secretKey:          credentials.SecretKey,
			expectedRespStatus: http.StatusLengthRequired,
		},
		// Test case - 4.
		// setting the readSeeker to `nil`, bucket policy parser will fail.
		{
			bucketName:         bucketName,
			bucketPolicyReader: nil,

			policyLen:          10,
			accessKey:          credentials.AccessKey,
			secretKey:          credentials.SecretKey,

	if ok {
		if b.bucket != bucket {
			logger.Info("getBucket: newly cached bucket %s does not match this bucket %s", b.bucket, bucket)
			debug.PrintStack()
		}
		return b
	}

	// New bucket. If we fail return the transient bucket.
	b = newBucketMetacache(bucket, true)
	m.buckets[bucket] = b
	return b
}

// deleteBucketCache will delete the bucket cache if it exists.

	// Storage operations.

	// Returns true if disk is online and its valid i.e valid format.json.
	// This has nothing to do with if the drive is hung or not responding.
	// For that individual storage API calls will fail properly. The purpose
	// of this function is to know if the "drive" has "format.json" or not
	// if it has a "format.json" then is it correct "format.json" or not.
	IsOnline() bool

// for each op.
// TODO(srbs): We need to define `ZerosLike` here to keep the compiler happy.
// Figure out a way to avoid this.
// TODO(srbs): Should ZerosLike check-fail instead of returning nullptr?
class TapeTensor {
 public:
  explicit TapeTensor(AbstractTensorHandle* handle);
  TapeTensor(const TapeTensor& other);
  ~TapeTensor();

  int64_t GetID() const;

	sys, ok := fi.Sys().(*syscall.Stat_t)
	if !ok {
		return nil
	}
	h.Uid = int(sys.Uid)
	h.Gid = int(sys.Gid)
	if doNameLookups {
		// Best effort at populating Uname and Gname.
		// The os/user functions may fail for any number of reasons
		// (not implemented on that platform, cgo not enabled, etc).
		if u, ok := userMap.Load(h.Uid); ok {
			h.Uname = u.(string)
		} else if u, err := user.LookupId(strconv.Itoa(h.Uid)); err == nil {

  else:
    importlib.import_module("keras.src.optimizers")
except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied

failed_count_site2=$(./s3-check-md5 -versions -access-key minioadmin -secret-key minioadmin -endpoint http://site2-nginx:9002 -bucket testbucket 2>&1 | grep FAILED | wc -l)

## we do not need to fail here, since we are going to test
## upgrading to master, healing and being able to recover
## the last version.
if [ $failed_count_site1 -ne 0 ]; then
	echo "failed with multipart on site1 uploads ${failed_count_site1}"
fi

./mc cp /tmp/data/defpartsize minio1/test-bucket/defpartsize --enc-c "minio1/test-bucket/defpartsize=${TEST_MINIO_ENC_KEY}" --insecure

# Below should fail as compression and SSEC used at the same time
# DISABLED: We must check the response header to see if compression was actually applied