name: 'Requeue stale team-triage items'
on:
  schedule:
    # Execute every day at 00:05 to avoid conflicts with other workflows
    - cron: '5 0 * * *'

permissions: {}

jobs:
  requeue:
    permissions:
      issues: write
      pull-requests: write
    runs-on: ubuntu-latest
    steps:
      - uses: actions/stale@v10
        with:
          operations-per-run: 50
          remove-stale-when-updated: false

name: IDE Experience team notifier
run-name: Notify the IDE Experience team about new RCs for manual testing
on:
  push:
    tags:
      - 'v*.*.*-RC1'

permissions: {}

jobs:
  send-slack-notification:
    runs-on: ubuntu-latest
    steps:
      - name: Send Slack notification about new RCs for manual testing
        id: slack
        uses: slackapi/slack-github-action@v2.1.1
        with:

platforms/core-execution/build-cache-http/                  @gradle/bt-cortex @gradle/dv-integrations-team
platforms/core-execution/build-cache-packaging/             @gradle/bt-cortex @gradle/dv-integrations-team
platforms/core-execution/build-cache-spi/                   @gradle/bt-cortex @gradle/dv-integrations-team
platforms/core-execution/hashing/                           @gradle/bt-cortex @gradle/dv-integrations-team

just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After

            Please report it to @gradle/bt-support team
          days-before-issue-close: -1
          close-issue-message: >
            **BUG!** This issue should not be closed by the "stale" workflow.
            Please report it to @gradle/bt-support team
          close-issue-reason: not_planned

          # PULL REQUESTS -----------------------------------------------------

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

#     mkl:          Enable full mkl support.
#     nogcp:        Disable GCS support.
#     nonccl:       Disable nccl support.
#
#
# Remote build execution options (only configured to work with TF team projects for now.)
#     rbe_base:                       General RBE options shared by all flavors.
#     rbe_linux:                      General RBE options used on all linux builds.

        has been moved to the GitHub repository
        [keras-team/keras](http://github.com/keras-team/keras). The API
        endpoints for `tf.keras` stay unchanged, but are now backed by the
        `keras` PIP package. All Keras-related PRs and issues should now be
        directed to the GitHub repository.
        [keras-team/keras](http://github.com/keras-team/keras).

low-level edwards25519 // operations can use filippo.io/edwards25519, an extended version of this // package repackaged as an importable module. // // (Note that filippo.io/edwards25519 and github.com/gtank/ristretto255 are not // maintained by the Go team and are not covered by the Go 1 Compatibility Promise.) package edwards25519 golang.org/fips140@v1.0.0/fips140/v1.0.0/edwards25519/edwards25519.go // Copyright (c) 2017 The Go Authors. All rights reserved. // Use of this source code is governed by...