// These calls are not under tests, the dashboards are, so we can be leniant here
					log.Warnf("requests failed: %v", err)
				}
			}
		case <-done:
			scopes.Framework.Infof("done sending traffic after %v rounds", times)
			return
		}
	}
}

// extractQueries pulls all prometheus queries out of a grafana dashboard
// Rather than importing the entire grafana API just for this test, do some shoddy json parsing

  (TF_IdentityOp $input)>;

// Implements TF Round on floats using basic operations. TF Round is specified
// as RoundHalfToEven to be compatible with Numpy.
def LowerRoundOpOnFloatTensor : Pat<
  (TF_RoundOp:$res TF_FloatTensor:$input),
  (TF_SelectV2Op
    (TF_EqualOp
      (TF_ConstOp:$zero (GetScalarOfFloatType<"0.0"> $input)),
      (TF_SelectV2Op:$rounded
        (TF_LogicalOrOp
          (TF_GreaterOp

	}
	if x.prec == 0 {
		return "zero precision finite number"
	}
	return ""
}

// round rounds z according to z.mode to z.prec bits and sets z.acc accordingly.
// sbit must be 0 or 1 and summarizes any "sticky bit" information one might
// have before calling round. z's mantissa must be normalized (with the msb set)
// or empty.
//

//	B) decrement use counts of the values' args.
func clobber(vv ...*Value) bool {
	for _, v := range vv {
		v.reset(OpInvalid)
		// Note: leave v.Block intact.  The Block field is used after clobber.
	}
	return true
}

// clobberIfDead resets v when use count is 1. Returns true.
// clobberIfDead is used by rewrite rules to decrement
// use counts of v's args when v is dead and never used.

			t.Error(tc.filename, err)
			continue
		}
		m1, err := Decode(&buf)
		if err != nil {
			t.Error(tc.filename, err)
			continue
		}
		if m0.Bounds() != m1.Bounds() {
			t.Errorf("%s, bounds differ: %v and %v", tc.filename, m0.Bounds(), m1.Bounds())
			continue
		}
		// Compare the average delta to the tolerance level.
		avgDelta := averageDelta(m0, m1)
		if avgDelta > tc.tolerance {

      int64_t num_elements = input_type.getNumElements();
      uint32_t u32_max = std::numeric_limits<uint32_t>::max();
      int rounds =
          std::ceil(exponent * std::log(num_elements) / std::log(u32_max));

      Value current = op.getValue();
      for (int i = 0; i < rounds; ++i) {
        auto keys =
            CreateRngUniform32(op.getLoc(), num_elements, /*lower_limit=*/0,

(or even be just another bound type parameter).
In a process of repeated simplification, the bound type parameters in each type
argument are substituted with the respective type arguments for those type
parameters until each type argument is free of bound type parameters.
</p>

<p>
If type arguments contain cyclic references to themselves
through bound type parameters, simplification and thus type
inference fails.

    TFL_TensorOf<[F32, I32, I64, I1, I8, UI8]>:$output
  );

  let hasOptions = 1;
}

def TFL_RoundOp: TFL_Op<"round", [
    Pure,
    TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Round operator";

  let description = [{
Rounds the values of a tensor to the nearest integer, element-wise.
  }];

  let arguments = (ins
    TFL_FpTensor:$x
  );

	// Avoid round tripping the ClusterConfiguration embedded in the InitConfiguration, since it is
	// only present in the internal version and not in public versions
	obj.ClusterConfiguration = kubeadm.ClusterConfiguration{}

	// Adds the default bootstrap token to get the round trip working
	obj.BootstrapTokens = []bootstraptokenv1.BootstrapToken{
		{

        return Collections.emptyIterator()
    }

    override fun get(index: Int): KaAnnotation = withValidityAssertion {
        throw IndexOutOfBoundsException("Index $index out of bounds")
    }

    override fun contains(classId: ClassId): Boolean = withValidityAssertion {
        return false
    }

    override fun get(classId: ClassId): List<KaAnnotation> = withValidityAssertion {