jobs:
  cherrypick:
    name: Cherrypick to ${{ github.event.inputs.release_branch}} - ${{ github.event.inputs.git_commit }}
    runs-on: ubuntu-latest
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    steps:
    - name: Checkout code
      uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
      with:
        ref: ${{ github.event.inputs.release_branch }}

   * propagate cancellation) and {@link #toString()}. To access the futures' <i>values</i>, {@code
   * AggregateFuture} attaches listeners that hold references to one or more inputs. And in the case
   * of {@link CombinedFuture}, the user-supplied callback usually has its own references to inputs.
   */
  /*
   * In certain circumstances, this field might theoretically not be visible to an afterDone() call

  @SafeVarargs
  public static <T extends @Nullable Object> Iterator<T> concat(Iterator<? extends T>... inputs) {
    return concatNoDefensiveCopy(Arrays.copyOf(inputs, inputs.length));
  }

  /**
   * Combines multiple iterators into a single iterator. The returned iterator iterates across the
   * elements of each iterator in {@code inputs}. The input iterators are not polled until
   * necessary.
   *

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["header", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus",
        }
    ]
}
```

## Resumo

    private static final long serialVersionUID = 0;
  }

  /**
   * This is adapted from the regex suggested by {@link Double#valueOf(String)} for prevalidating
   * inputs. All valid inputs must pass this regex, but it's semantically fine if not all inputs
   * that pass this regex are valid -- only a performance hit is incurred, not a semantics bug.
   */
  @GwtIncompatible // regular expressions
  static final

        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,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],

            // * if autoapply is enabled, and an end date was chosen, apply the selection
            // * if single date picker mode, and time picker isn't enabled, apply the selection immediately
            // * if one of the inputs above the calendars was focused, cancel that manual input
            //

            if (this.endDate || date.isBefore(this.startDate, 'day')) { //picking start
                if (this.timePicker) {

   * that gets messy here, and we already have null tests for Range.
   */

  /*
   * These generators also rely on consecutive integer inputs (not necessarily in order, but no
   * holes).
   */

  // SetCreationTester has some tests that pass in duplicates. Dedup them.

   * input element is mapped to one cell in the returned table, with the rows, columns, and values
   * generated by applying the specified functions. If multiple inputs are mapped to the same row
   * and column pair, they will be combined with the specified merging function in encounter order.
   *
   * <p>The returned {@code Collector} will throw a {@code NullPointerException} at collection time

   * that gets messy here, and we already have null tests for Range.
   */

  /*
   * These generators also rely on consecutive integer inputs (not necessarily in order, but no
   * holes).
   */

  // SetCreationTester has some tests that pass in duplicates. Dedup them.