steps:
    - name: Checkout repository
      uses: actions/checkout@v4
      # Checkout must run before the caching key is computed using the `hashFiles` method

    - name: Cache Gradle Modules
      uses: actions/cache@v4
      with:
        path: |
          ~/.gradle/caches/modules-2/
          ~/.gradle/caches/build-cache-1/

	StartTime time.Time   `msg:"startTs"` // Time at which rebalance-start was issued
	EndTime   time.Time   `msg:"stopTs"`  // Time at which rebalance operation completed or rebalance-stop was called
	Status    rebalStatus `msg:"status"`  // Current state of rebalance operation. One of Started|Stopped|Completed|Failed.
}

// rebalanceMeta contains information pertaining to an ongoing rebalance operation.
type rebalanceMeta struct {

      // meant that sometimes a too-large threshold is calculated. However, this new threshold is
      // independent of the initial capacity, except that it won't be lower than the threshold
      // computed from that capacity. Because the internal table is only allocated on the first
      // write, we won't see copying because of the new threshold. So it is always OK to use the
      // calculation here.

	The fields are compared in source order, and comparison stops as
	soon as two field values differ (or all fields have been compared).
	</li>

	<li>
	Array types are comparable if their array element types are comparable.
	Two array values are equal if their corresponding element values are equal.
	The elements are compared in ascending index order, and comparison stops

build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current

*   TF Core:

    *   Corrected higher-order gradients of control flow constructs (`tf.cond`,
        `tf.while_loop`, and compositions like `tf.foldl`) computed with
        `tf.GradientTape` inside a `tf.function`.
    *   Changed the default step size in `gradient_checker_v2.compute_gradients`
        to be exactly representable as a binary floating point numbers. This

computer or modifying a private copy.  Propagation includes copying,
distribution (with or without modification), making available to the
public, and in some countries other activities as well.

  To "convey" a work means any kind of propagation that enables other
parties to make or receive copies.  Mere interaction with a user through

  TF_Status* s = TF_NewStatus();
  TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s);
  TF_DeleteStatus(s);
  return NULL;
}

// A compute function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void compute(void* kernel, TF_OpKernelContext* ctx) {
  TF_Tensor* input;
  TF_Status* s = TF_NewStatus();
  TF_GetInput(ctx, 0, &input, s);
  TF_DeleteTensor(input);

   */
  public static Equivalence<Object> equals() {
    return Equals.INSTANCE;
  }

  /**
   * Returns an equivalence that uses {@code ==} to compare values and {@link
   * System#identityHashCode(Object)} to compute the hash code. {@link Equivalence#equivalent}
   * returns {@code true} if {@code a == b}, including in the case that a and b are both null.
   *
   * @since 13.0
   * @since 4.0 (in Equivalences)
   */

## 0.101.0

### Features

* ✨ Enable Pydantic's serialization mode for responses, add support for Pydantic's `computed_field`, better OpenAPI for response models, proper required attributes, better generated clients. PR [#10011](https://github.com/tiangolo/fastapi/pull/10011) by [@tiangolo](https://github.com/tiangolo).

### Refactors