clause.NamedExpr{SQL: result.SQL, Vars: result.Vars}.Build(stmt)
			if stmt.SQL.String() != result.Result {
				t.Errorf("generated SQL is not equal, expects %v, but got %v", result.Result, stmt.SQL.String())
			}

			if !reflect.DeepEqual(result.ExpectedVars, stmt.Vars) {
				t.Errorf("generated vars is not equal, expects %v, but got %v", result.ExpectedVars, stmt.Vars)
			}
		})
	}
}

func TestExpression(t *testing.T) {

		} else if results.RowsAffected != 2 {
			t.Fatalf("rows affected expects: %v, got %v", 1, results.RowsAffected)
		} else if u1.ID == 0 {
			t.Fatalf("ID expects : not equal 0, got %v", u1.ID)
		} else if u2.ID == 0 {
			t.Fatalf("ID expects : not equal 0, got %v", u2.ID)
		}

		var gotUsers []user
		results = DB.Where("id in (?, ?)", u1.ID, u2.ID).Order("id asc").Select("id, name").Find(&gotUsers)
		if results.Error != nil {

			set +e # don't exit if this fails
			${MC} rm -r --force myminio/$BUCKET
			set -e # reset `e` as active
		else
			echo "Bucket '$BUCKET' does not exist, skipping purge."
		fi
	fi

	# Create the bucket if it does not exist and set objectlocking if enabled (NOTE: versioning will be not changed if OBJECTLOCKING is set because it enables versioning to the Buckets created)
	if ! checkBucketExists $BUCKET; then
		if [ ! -z $OBJECTLOCKING ]; then

            throw new DocGenerationException("Parsing non-Java files is not supported: $sourceFile")
        }
        try {
            new JavaParser().parse(sourceFile).getResult().get().accept(new SourceMetaDataVisitor(), repository)
        } catch (Exception e) {
            throw new DocGenerationException("Could not parse '$sourceFile'.", e)
        }
    }

   
   
   *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.

   * operation. This may be incremented not in conjunction with {@code missCount} if the load occurs
   * as a result of a refresh or if the cache loader returned more items than was requested. {@code
   * missCount} may also be incremented not in conjunction with this (nor {@link
   * #loadExceptionCount}) on calls to {@code getIfPresent}.
   */

   * operation. This may be incremented not in conjunction with {@code missCount} if the load occurs
   * as a result of a refresh or if the cache loader returned more items than was requested. {@code
   * missCount} may also be incremented not in conjunction with this (nor {@link
   * #loadExceptionCount}) on calls to {@code getIfPresent}.
   */

 *     #removalListener}. Cache keys may not be null.
 * @param <V> the most general value type this builder will be able to create caches for. This is
 *     normally {@code Object} unless it is constrained by using a method like {@link
 *     #removalListener}. Cache values may not be null.
 * @author Charles Fry
 * @author Kevin Bourrillion
 * @since 10.0
 */
@GwtCompatible

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package cmd

import "errors"

// errErasureReadQuorum - did not meet read quorum.
var errErasureReadQuorum = errors.New("Read failed. Insufficient number of drives online")

// errErasureWriteQuorum - did not meet write quorum.

        user_dict = db[username]
        return UserInDB(**user_dict)


def authenticate_user(fake_db, username: str, password: str):
    user = get_user(fake_db, username)
    if not user:
        return False
    if not verify_password(password, user.hashed_password):
        return False
    return user


def create_access_token(data: dict, expires_delta: timedelta | None = None):
    to_encode = data.copy()