let summary = "Outputs random values from a uniform distribution.";

  let description = [{
The generated values follow a uniform distribution in the range `[0, 1)`. The
lower bound 0 is included in the range, while the upper bound 1 is excluded.
  }];

  let arguments = (ins

At the same time, this behavior can be confusing for users as they can experience a failing test in a successful build.
To make the two APIs more uniform, we made `TestLauncher` also fail the build, which is a potential breaking change.
To continue the test execution even if a test task failed, Tooling API clients should explicitly pass `--continue` to the build.

    *   Improve error message when attempting to use `None` in data-dependent
        control flow.
    *   Add `RaggedTensor.numpy()`.
    *   Update `RaggedTensor.__getitem__` to preserve uniform dimensions & allow
        indexing into uniform dimensions.
    *   Update `tf.expand_dims` to always insert the new dimension as a
        non-ragged dimension.
    *   Update `tf.embedding_lookup` to use `partition_strategy` and `max_norm`

n-color.svg\" style=\"height: 50px\"> Istio</a>\n  </div>\n  <div style=\"position: absolute; bottom: 0; right: 0; font-size: 15px\">\n    Istio is an <a href=\"https://github.com/istio/istio\" target=\"_blank\">open platform</a> that provides a uniform way to <a href=\"https://istio.io/docs/concepts/security/\" target=\"_blank\">secure</a>,\n    <a href=\"https://istio.io/docs/concepts/traffic-management/\" target=\"_blank\">connect</a>, and \n    <a href=\"https://istio.io/docs/concepts/observability/\"...

      loc, builder->getI32IntegerAttr(upper_limit));

  return builder->create<mhlo::RngOp>(loc, lower, upper, shape_tensor,
                                      ::mlir::mhlo::RngDistribution::UNIFORM);
}

using WhileBodyFnType = llvm::function_ref<void(
    Location loc, Value iteration, ArrayRef<Value> old_values,
    SmallVectorImpl<Value> *new_values, OpBuilder *builder)>;