} else {
                    throw new IOException("Reconnect failed: " + response.getStatus());
                }
                
            } catch (Exception e) {
                log.debug("Reconnect attempt {} failed: {}", attempt + 1, e.getMessage());
                
                // Retry
                return attemptReconnect(file, info, attempt + 1).join();
            }
        });
    }

	ext     string
}

// record will record the profile and store it as the base.
func (p *profilerWrapper) record(profileType string, debug int, recordName string) {
	var buf bytes.Buffer
	if p.records == nil {
		p.records = make(map[string][]byte)
	}
	err := pprof.Lookup(profileType).WriteTo(&buf, debug)
	if err != nil {
		return
	}
	p.records[recordName] = buf.Bytes()
}

     */
    public synchronized void putToInfoMap(final String key, final String value) {
        if (infoMap == null) {
            infoMap = Collections.synchronizedMap(new LinkedHashMap<>());
        }
        logger.debug("infoMap: {}={} => {}", key, value, infoMap);
        infoMap.put(key, value);
    }

    /**
     * Updates crawling information parameters for the specified session.

Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)
are skipped, and any checks implemented inside the shape inference code are not
executed.

        if (name == null || dataStore == null) {
            throw new IllegalArgumentException("name or dataStore is null.");
        }
        if (logger.isDebugEnabled()) {
            logger.debug("Loaded {}", name);
        }
        dataStoreMap.put(name.toLowerCase(Locale.ROOT), dataStore);
        dataStoreMap.put(dataStore.getClass().getSimpleName().toLowerCase(Locale.ROOT), dataStore);
    }

    /**

        this.rdmaProvider = RdmaProviderFactory.getProvider(context.getConfig());
        this.bufferManager = new RdmaBufferManager(rdmaProvider);
        this.statistics = new RdmaStatistics();

        log.debug("Created RDMA transport with provider: {}", rdmaProvider.getClass().getSimpleName());
    }

    /**
     * Establishes RDMA connection to the remote server.
     *
     * @throws IOException if connection fails

import java.util.List;
import java.util.Map;

import org.apache.commons.io.FileUtils;
import org.codelibs.core.collection.Maps;
import org.codelibs.fess.unit.UnitFessTestCase;
import org.codelibs.sai.internal.ir.debug.ObjectSizeCalculator;

import com.google.common.collect.Lists;

public class MemoryUtilTest extends UnitFessTestCase {

    public void test_byteCountToDisplaySize() {

                    if (tempFile.exists() && !tempFile.delete()) {
                        logger.warn("Failed to delete {}.", tempFile.getAbsolutePath());
                    }
                    logger.debug("Failed to copy {}", filename, e);
                    throwValidationError(messages -> messages.addErrorsFailedToInstallPlugin(GLOBAL, filename), this::asListHtml);
                }
                new Thread(() -> {

        }
        if (!isAlgorithmSupported(algorithm)) {
            throw new CIFSException("Unsupported compression algorithm: " + algorithm);
        }
        if (length < MIN_COMPRESSION_SIZE) {
            log.debug("Data too small for compression ({} bytes), returning uncompressed", length);
            byte[] result = new byte[length];
            System.arraycopy(data, offset, result, 0, length);
            return result;
        }

Lets start the lambda handler.

```
python lambda_handler.py
 * Serving Flask app 'webhook'
 * Debug mode: off
WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
 * Running on http://127.0.0.1:5000
Press CTRL+C to quit
```