*/
  }

  /**
   * Called before runInterruptibly - if true, runInterruptibly and afterRanInterruptibly will not
   * be called.
   */
  abstract boolean isDone();

  /**
   * Do interruptible work here - do not complete Futures here, as their listeners could be
   * interrupted.
   */
  @ParametricNullness
  abstract T runInterruptibly() throws Exception;

/// note

FastAPI will know that the value of `q` is not required because of the default value `= None`.

The `str | None` (Python 3.10+) or `Union` in `Union[str, None]` (Python 3.8+) is not used by FastAPI to determine that the value is not required, it will know it's not required because it has a default value of `= None`.

	flag.Parse()

	if sourceEndpoint == "" {
		log.Fatalln("source Endpoint is not provided")
	}

	if sourceAccessKey == "" {
		log.Fatalln("source Access key is not provided")
	}

	if sourceSecretKey == "" {
		log.Fatalln("source Secret key is not provided")
	}

	if sourceBucket == "" && sourcePrefix != "" {

/**
 * Implementation of {@link Multimap} using hash tables.
 *
 * <p>The multimap does not store duplicate key-value pairs. Adding a new key-value pair equal to an
 * existing key-value pair has no effect.
 *
 * <p>Keys and values may be null. All optional multimap methods are supported, and all returned
 * views are modifiable.
 *
 * <p>This class is not threadsafe when any concurrent operations update the multimap. Concurrent

		// If not orchestrated
		// and not setup in reverse proxy
		if !orchestrated && !reverseProxy {
			// Check whether same path is not used in endpoints of a host on different port.
			// Only verify this on baremetal setups, DNS is not available in orchestrated
			// environments so we can't do much here.

    /**
     * Returns a media type for this string.
     *
     * @throws IllegalArgumentException if this is not a well-formed media type.
     */
    @JvmStatic
    @JvmName("get")
    fun String.toMediaType(): MediaType = commonToMediaType()

    /** Returns a media type for this, or null if this is not a well-formed media type. */
    @JvmStatic
    @JvmName("parse")

/*
 * Copyright (C) 2015 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 is distributed on an "AS IS" BASIS,

 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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,

		} 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 {

   
   
   *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.