final int start = bufferIndex;

        this.capabilities = SMBUtil.readInt4(buffer, bufferIndex);
        bufferIndex += 4;

        System.arraycopy(buffer, bufferIndex, this.serverGuid, 0, 16);
        bufferIndex += 16;

        this.securityMode = SMBUtil.readInt2(buffer, bufferIndex);
        this.dialect = SMBUtil.readInt2(buffer, bufferIndex + 2);

            descr = DESCR.getBytes("ASCII");
        } catch (final UnsupportedEncodingException uee) {
            return 0;
        }

        writeInt2(NET_SHARE_ENUM, dst, dstIndex);
        dstIndex += 2;
        System.arraycopy(descr, 0, dst, dstIndex, descr.length);
        dstIndex += descr.length;
        writeInt2(0x0001, dst, dstIndex);
        dstIndex += 2;
        writeInt2(maxDataCount, dst, dstIndex);
        dstIndex += 2;

import java.util.ArrayList;
import java.util.List;

import org.apache.maven.execution.MavenSession;
import org.apache.maven.project.MavenProject;

/**
 * Collects basic settings to access the repository system.
 *
 */
public class DefaultRepositoryRequest implements RepositoryRequest {

    private boolean offline;

    private boolean forceUpdate;

    private ArtifactRepository localRepository;

import java.io.IOException;
import java.io.PrintStream;
import java.util.function.Consumer;

public class LoggingOutputStream extends FilterOutputStream {

    static final byte[] LINE_SEP = System.lineSeparator().getBytes();

    final EolBaos buf;
    final Consumer<String> consumer;

    public LoggingOutputStream(Consumer<String> consumer) {
        this(new EolBaos(), consumer);
    }

        Iterator iter = set.iterator();
        assertTrue(set.size() == 4, "Set size should be 4, is " + set.size());

        while (iter.hasNext()) {
            Artifact artifact = (Artifact) iter.next();
            System.out.println("Artifact: " + artifact.getDependencyConflictId() + " " + artifact.getVersion()
                    + " Optional=" + (artifact.isOptional() ? "true" : "false"));
            assertTrue(

---
name: TensorFlow Lite Converter Issue
about: Use this template for reporting issues during model conversion to TFLite
labels: 'TFLiteConverter'

---

### 1. System information

- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installation (pip package or built from source):
- TensorFlow library (version, if pip package or github SHA, if built from source):

### 2. Code

        .addHeader("content-type: text/plain")
        .addHeader("content-length", "3")
        .build(),
    )
    val sentAt = System.currentTimeMillis()
    val recordedResponse = executeSynchronously("/", "User-Agent", "SyncApiTest")
    val receivedAt = System.currentTimeMillis()
    recordedResponse
      .assertCode(200)
      .assertSuccessful()
      .assertHeaders(
        Headers

}

// SetUsersSysType - sets the users system type, regular or LDAP.
func (sys *IAMSys) SetUsersSysType(t UsersSysType) {
	sys.usersSysType = t
}

// GetUsersSysType - returns the users system type for this IAM
func (sys *IAMSys) GetUsersSysType() UsersSysType {
	return sys.usersSysType
}

// NewIAMSys - creates new config system object.
func NewIAMSys() *IAMSys {
	return &IAMSys{

                } else if (LogStream.level > 1) {
                    log.println("unknown resolver method: " + s);
                }
            }
            resolveOrder = new int[i];
            System.arraycopy(tmp, 0, resolveOrder, 0, i);
        }
    }

    int getNextNameTrnId() {
        if ((++nextNameTrnId & 0xFFFF) == 0) {
            nextNameTrnId = 1;
        }
        return nextNameTrnId;

        String[] validScopes;
        if (isDependencyManagement) {
            validScopes = new String[] {"provided", "compile", "runtime", "test", "system", "import"};
        } else {
            validScopes = new String[] {"provided", "compile", "runtime", "test", "system"};
        }

        List<String> values = Arrays.asList(validScopes);

        if (values.contains(scope)) {
            return true;