# Contributor Covenant Code of Conduct

## Our Pledge

In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to making participation in our project and
our community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, gender identity and expression, level of experience,
nationality, personal appearance, race, religion, or sexual identity and
orientation.

# TensorFlow Code of Conduct

In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to make participation in our project and our
community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, gender identity and expression, level of
experience, nationality, personal appearance, race, religion, or sexual identity
and orientation.

## Our Standards

1024* drives in total.

- *If total number of nodes are of odd number then GCD algorithm provides affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards nodes which leads to next...

  behaviors behind a consistent user interface is much, much more difficult if
  the system can't tell whether it has access to the network required by these
  operations.

  Offline mode really means anticipating a lack of network connectivity, and as
  a result turning off certain services provided by m2 and providing a coherent
  way of predicting and reporting when network-related failures will take place.

        succeeds 'help'
    }

    @Issue("https://github.com/gradle/gradle/issues/26461")
    def "when anticipating configurations to be created from sourcesets, their usage is reset (creation = #description)"() {
        given:
        settingsFile """
            include 'resolver', 'producer'
        """

Kubelet has adopted structured logging, thanks to community effort in accomplishing this within the release timeline. Structured logging in the project remains an ongoing effort -- for folks interested in participating, [keep an eye / chime in to the mailing list discussion](https://groups.google.com/g/kubernetes-dev/c/y4WIw-ntUR8).

### Storage Capacity Tracking

	// need wait for those resources to be detached by the Kubelet. In general, resources
	// the Kubelet exclusively owns must be released prior to a pod being reported terminal,
	// while resources that have participanting components above the API use the pod's
	// transition to a terminal phase (or full deletion) to release those resources.
	if transitioningToTerminalPhase {
		if couldHaveRunningContainers {

input: the input to the reduction
data: the value of the reduction across all `num_devices` devices.
reduction: the reduction operation to perform.
num_devices: The number of devices participating in this reduction.
shared_name: Identifier that shared between ops of the same reduction.
  }];

  let arguments = (ins
    TensorOf<[TF_Float16, TF_Float32, TF_Float64, TF_Int32, TF_Int64]>:$input,

	errServerClosedIdle = errors.New("http: server closed idle connection")
)

// transportReadFromServerError is used by Transport.readLoop when the
// 1 byte peek read fails and we're actually anticipating a response.
// Usually this is just due to the inherent keep-alive shut down race,
// where the server closed the connection at the same time the client
// wrote. The underlying err field is usually io.EOF or some