# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

/*
 * Copyright 2012-2025 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

                    multimap.put("foo", 17);
                    multimap.put("bar", 32);
                    multimap.put("foo", 16);
                    multimap = filterKeys(multimap, not(equalTo("foo")));
                    return filterKeys(multimap, not(equalTo("bar")));
                  }
                })
            .named("Multimaps.filterKeys[Multimaps.filterKeys[ListMultimap], Predicate]")
            .withFeatures(

   * infinite {@code double} values are considered infinitely far away. For example, 2^2000 is not
   * representable as a double, but {@code roundToDouble(BigDecimal.valueOf(2).pow(2000), HALF_UP)}
   * will return {@code Double.MAX_VALUE}, not {@code Double.POSITIVE_INFINITY}.
   *
   * <p>For the case of {@link RoundingMode#HALF_EVEN}, this implementation uses the IEEE 754

myString("foo" + "bar")  // "foobar" of type myString
string([]byte{'a'})      // not a constant: []byte{'a'} is not a constant
(*int)(nil)              // not a constant: nil is not a constant, *int is not a boolean, numeric, or string type
int(1.2)                 // illegal: 1.2 cannot be represented as an int
string(65.0)             // illegal: 65.0 is not an integer constant
</pre>

<p>

        bool((must, should, mustNot, filter) -> {
            filteredLambda.callback(must, filter);
        }, opLambda);
    }

    public void not(OperatorCall<UserCQ> notLambda) {
        not(notLambda, null);
    }

    public void not(final OperatorCall<UserCQ> notLambda, final ConditionOptionCall<BoolQueryBuilder> opLambda) {
        bool((must, should, mustNot, filter) -> notLambda.callback(mustNot), opLambda);

    install|upgrade)

        # Create fess group if not existing
        if ! getent group "$FESS_GROUP" > /dev/null 2>&1 ; then
            echo -n "Creating $FESS_GROUP group..."
            addgroup --quiet --system "$FESS_GROUP"
            echo " OK"
        fi

        # Create fess user if not existing
        if ! id $FESS_USER > /dev/null 2>&1 ; then

        bool((must, should, mustNot, filter) -> {
            filteredLambda.callback(must, filter);
        }, opLambda);
    }

    public void not(OperatorCall<LabelTypeCQ> notLambda) {
        not(notLambda, null);
    }

    public void not(final OperatorCall<LabelTypeCQ> notLambda, final ConditionOptionCall<BoolQueryBuilder> opLambda) {
        bool((must, should, mustNot, filter) -> notLambda.callback(mustNot), opLambda);

//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the
//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.
//   - The number of `input_tensors` should be the same as the number of items

    /**
     * Shuts down the Fess application.
     *
     * @param args command line arguments (not used)
     */
    public static void shutdown(final String[] args) {
        System.exit(0);
    }

    /**
     * Checks if the lasta.env system property is not set.
     *
     * @return true if lasta.env is not set, false otherwise
     */
    private static boolean isNoneEnv() {