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**4. Approved**

    // can do its work.
    //
    // Rather than re-entering and delegating Accumulate like this, we could
    // instead allow ForwardAccumulator some control over the current tape set
    // (so it can deactivate itself and activate its GradientTape). Currently
    // that is managed by the language binding and would require relatively
    // messy callbacks.
    call_state_.top().backward_tape->RecordOperation(

    branches:
      - r2.**
  schedule:
    - cron: '0 8 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash

        StandardizedConv2D(tf.keras.layers.Conv2D): def call(self, inputs):
        mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,

    tags:
      - v2.**
  schedule:
    - cron: '0 4 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash