}

                final String inputStrings = line;
                final String input = unescape(inputStrings);

                if (input.length() > 0) {
                    id++;
                    final StopwordsItem item = new StopwordsItem(id, input);
                    if (updater != null) {
                        final StopwordsItem newItem = updater.write(item);

        }

        for (final Pattern pattern : includedDocPathPatterns) {
            if (pattern.matcher(input).matches()) {
                return Constants.TRUE;
            }
        }

        for (final Pattern pattern : excludedDocPathPatterns) {
            if (pattern.matcher(input).matches()) {
                return Constants.FALSE;
            }
        }

        return Constants.TRUE;

    }

        md5.reset();
        md5.update(ipad);
    }

    protected void engineUpdate(byte b) {
        md5.update(b);
    }

    protected void engineUpdate(byte[] input, int offset, int len) {
        md5.update(input, offset, len);
    }

    }


    @Override
    protected void engineUpdate ( byte b ) {
        this.md5.update(b);
    }


    @Override
    protected void engineUpdate ( byte[] input, int offset, int len ) {
        this.md5.update(input, offset, len);
    }

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

  }
};

// An abstract operation describes an operation by its type, name, and
// attributes. It can be "executed" by the context with some input tensors.
// It is allowed to reusing the same abstract operation for multiple execution
// on a given context, with the same or different input tensors.
class TracingOperation : public AbstractOperation {
 protected:
  explicit TracingOperation(AbstractOperationKind kind)

      if (MappedRange.InlineDelta.MAX_VALUE >= abs(codePointDelta)) {
        return MappedRange.InlineDelta(mapping.rangeStart, codePointDelta)
      }
    }
  }
  return null
}

/**
 * Inputs must have applied [withoutSectionSpans].
 */
internal fun sections(mappings: List<Mapping>): Map<Int, List<MappedRange>> {
  val result = mutableMapOf<Int, MutableList<MappedRange>>()

  for (mapping in mappings) {

                                        <th style="width: 25%"><la:message
                                                key="labels.dict_stopwords_source"/></th>
                                        <td>${f:h(input)}<la:hidden property="input"/></td>
                                    </tr>
                                    </tbody>
                                </table>
                            </div>

package com.google.common.math;

import java.math.BigInteger;
import java.util.Random;

/**
 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying
 * the order of magnitude of the generated values uniformly at random.
 *
 * @author Louis Wasserman
 */

    }

    protected EditBody createEditBody(final SynonymItem entity, final String dictId) {
        final EditBody body = new EditBody();
        body.id = entity.getId();
        body.dictId = dictId;
        body.inputs = entity.getInputsValue();
        body.outputs = entity.getOutputsValue();
        return body;
    }