columnKeyToIndex = table.columnKeyToIndex;
    @SuppressWarnings("unchecked")
    @Nullable V[][] copy = (@Nullable V[][]) new Object[rowList.size()][columnList.size()];
    array = copy;
    for (int i = 0; i < rowList.size(); i++) {
      arraycopy(table.array[i], 0, copy[i], 0, table.array[i].length);
    }
  }

  private abstract static class ArrayMap<K, V extends @Nullable Object>

// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package cmd

import (
	"bytes"
	"context"
	"encoding/hex"
	"fmt"
	"io"
	"math/rand"

   * mapping in the underlying map and determine which satisfy the filter. When a live view is
   * <i>not</i> needed, it may be faster to copy the filtered map and use the copy.
   *
   * <p><b>Warning:</b> {@code keyPredicate} must be <i>consistent with equals</i>, as documented at
   * {@link Predicate#apply}. Do not provide a predicate such as {@code

   * mapping in the underlying map and determine which satisfy the filter. When a live view is
   * <i>not</i> needed, it may be faster to copy the filtered map and use the copy.
   *
   * <p><b>Warning:</b> {@code keyPredicate} must be <i>consistent with equals</i>, as documented at
   * {@link Predicate#apply}. Do not provide a predicate such as {@code

    Builder(ValueGraphBuilder<N, V> graphBuilder) {
      // The incidentEdgeOrder for immutable graphs is always stable. However, we don't want to
      // modify this builder, so we make a copy instead.
      this.mutableValueGraph =
          graphBuilder.copy().incidentEdgeOrder(ElementOrder.<N>stable()).build();
    }

    /**
     * Adds {@code node} if it is not already present.
     *

Copyright 2009-${year} the 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,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,

# 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 2020 the original author or authors.
 *
 * 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 (C) 2012 The Guava Authors
 *
 * 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

/*
 * Copyright (C) 2012 The Guava Authors
 *
 * 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