int num_retvals = 1;
  return op_ptr->Execute(absl::MakeSpan(z, 1), &num_retvals);
}

// Op: Log1p()
// Summary: Computes natural logarithm of (1 + x) element-wise.
//
// Description:
//   I.e., \\(y = \log_e (1 + x)\\).
//
//   Example:
//
//   ```python
//   x = tf.constant([0, 0.5, 1, 5])
//   tf.math.log1p(x) ==> [0., 0.4054651, 0.6931472, 1.7917595]
//   ```

	// The probability distribution function is mean*exp(-mean*x), so the CDF is
	// p = 1 - exp(-mean*x), so
	// q = 1 - p == exp(-mean*x)
	// log_e(q) = -mean*x
	// -log_e(q)/mean = x
	// x = -log_e(q) * mean
	// x = log_2(q) * (-log_e(2)) * mean    ; Using log_2 for efficiency
	const randomBitCount = 26
	q := cheaprandn(1<<randomBitCount) + 1
	qlog := fastlog2(float64(q)) - randomBitCount

			expectedEarliestTime:  *deltaTimeAfterTopOfTheHour(1 * time.Minute),
			expectedTooManyMissed: manyMissed,
		},
		{
			name: "rogue cronjob",
			cj: &batchv1.CronJob{
				ObjectMeta: metav1.ObjectMeta{
					CreationTimestamp: metav1.NewTime(*deltaTimeAfterTopOfTheHour(10 * time.Second)),
				},
				Spec: batchv1.CronJobSpec{

---

Dans ce scénario de burgers parallèles, vous êtes un ordinateur / programme 🤖 avec deux processeurs (vous et votre crush 😍) attendant 🕙 à deux et dédiant votre attention 🕙 à "attendre devant le comptoir" pour une longue durée.

Le fast-food a 8 processeurs (serveurs/cuisiniers) 👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳. Alors que le fast-food de burgers concurrents en avait 2 (un serveur et un cuisinier).

	for i := 0; i < len(vf); i++ {
		a := Abs(vf[i])
		if f := Log2(a); !veryclose(log2[i], f) {
			t.Errorf("Log2(%g) = %g, want %g", a, f, log2[i])
		}
	}
	if f := Log2(E); f != Log2E {
		t.Errorf("Log2(%g) = %g, want %g", E, f, Log2E)
	}
	for i := 0; i < len(vflogSC); i++ {
		if f := Log2(vflogSC[i]); !alike(logSC[i], f) {
			t.Errorf("Log2(%g) = %g, want %g", vflogSC[i], f, logSC[i])
		}
	}

// directionality is complicated to manage in a transactionless system, but
// without it we can't ensure sane behavior in the face of different forms of
// trouble. For example, a rogue HA controller instance could end up racing
// and making multiple bindings that are indistinguishable, resulting in
// potential data loss.
//
// This controller is designed to work in active-passive high availability

## 0.88.0

### Upgrades

* ⬆ Bump Starlette to version `0.22.0` to fix bad encoding for query parameters in new `TestClient`. PR [#5659](https://github.com/tiangolo/fastapi/pull/5659) by [@azogue](https://github.com/azogue).

### Docs

* ✏️ Fix typo in docs for `docs/en/docs/advanced/middleware.md`. PR [#5376](https://github.com/tiangolo/fastapi/pull/5376) by [@rifatrakib](https://github.com/rifatrakib).

- Fix pod name of NonIndexed Jobs to not include rogue `-1` substring ([#105676](https://github.com/kubernetes/kubernetes/pull/105676), [@alculquicondor](https://github.com/alculquicondor))

}

def TF_LogOp : TF_Op<"Log", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes natural logarithm of x element-wise.";

  let description = [{
I.e., \\(y = \log_e x\\).

Example:

```python
x = tf.constant([0, 0.5, 1, 5])
tf.math.log(x) ==> [-inf, -0.6931472,  0. ,  1.609438]
```
  }];

  let arguments = (ins
    TF_FpOrComplexTensor:$x

		{"Lgamma", Func, 0},
		{"Ln10", Const, 0},
		{"Ln2", Const, 0},
		{"Log", Func, 0},
		{"Log10", Func, 0},
		{"Log10E", Const, 0},
		{"Log1p", Func, 0},
		{"Log2", Func, 0},
		{"Log2E", Const, 0},
		{"Logb", Func, 0},
		{"Max", Func, 0},
		{"MaxFloat32", Const, 0},
		{"MaxFloat64", Const, 0},
		{"MaxInt", Const, 17},
		{"MaxInt16", Const, 0},
		{"MaxInt32", Const, 0},