libraryDependencies += "org.codelibs.fess" % "fess-suggest" % "2.1.4-SNAPSHOT"

libraryDependencies += "org.apache.httpcomponents" % "httpclient" % "4.3.1"

libraryDependencies += "org.codehaus.groovy" % "groovy-all" % "2.4.0"

            allowEmpty = false,
            description = "The test project to use. E.g. largeJavaMultiProject"
        )
        param("env.PERFORMANCE_CHANNEL", "adhoc")
        param("checks", "all")
        text("runs", "40", display = ParameterDisplay.PROMPT, allowEmpty = false)
        text("warmups", "10", display = ParameterDisplay.PROMPT, allowEmpty = false)
        text(
            "scenario",
            "",

 * mask of the ACE, the whole access check fails. If the ACE is an "allow"
 * ACE and <i>all</i> of the bits in the desired access bits match bits in
 * the access mask of the ACE, the access check is successful. Otherwise,
 * more ACEs are evaluated until all desired access bits (combined)
 * are "allowed". If all of the desired access bits are not "allowed"
 * the then same process is repeated for inherited ACEs.
 * <p>

type httpListener struct {
	opts        TCPOptions
	listeners   []net.Listener    // underlying TCP listeners.
	acceptCh    chan acceptResult // channel where all TCP listeners write accepted connection.
	ctx         context.Context
	ctxCanceler context.CancelFunc
}

// start - starts separate goroutine for each TCP listener.  A valid new connection is passed to httpListener.acceptCh.

# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which
# drops all the bazel dependencies for each py_test; this makes all the tests
# use the wheel's TensorFlow installation instead of the one made available

message RollingUpdateStatefulSetStrategy {
  // Partition indicates the ordinal at which the StatefulSet should be partitioned
  // for updates. During a rolling update, all pods from ordinal Replicas-1 to
  // Partition are updated. All pods from ordinal Partition-1 to 0 remain untouched.
  // This is helpful in being able to do a canary based deployment. The default value is 0.
  // +optional
  optional int32 partition = 1;

Copyright(C) 2009-2016 CodeLibs Project. All Rights Reserved.

License: Apache-2.0
 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,

## Scope

This Code of Conduct applies to all content on tensorflow.org, TensorFlow’s GitHub organization, or any other official TensorFlow web presence allowing for community interactions, as well as at all official TensorFlow events, whether offline or online.

///

/// note

Notice that the input model is still validated.

So, if you want to receive partial updates that can omit all the attributes, you need to have a model with all the attributes marked as optional (with default values or `None`).

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