}

	cases := map[string]struct {
		mounts      []core.VolumeMount
		expectError bool
	}{
		"subpath expr not specified": {
			[]core.VolumeMount{{
				Name:      "abc-123",
				MountPath: "/bab",
			}},
			false,
		},
		"subpath expr specified": {
			[]core.VolumeMount{{
				Name:        "abc-123",
				MountPath:   "/bab",
				SubPathExpr: "$(POD_NAME)",
			}},

By default, this op performs an inclusive cumulative log-sum-exp,
which means that the first
element of the input is identical to the first element of the output:
```python
tf.math.cumulative_logsumexp([a, b, c])  # => [a, log(exp(a) + exp(b)), log(exp(a) + exp(b) + exp(c))]
```

By setting the `exclusive` kwarg to `True`, an exclusive cumulative log-sum-exp is
performed instead:
```python

		{"Cos", Func, 0},
		{"Cosh", Func, 0},
		{"Dim", Func, 0},
		{"E", Const, 0},
		{"Erf", Func, 0},
		{"Erfc", Func, 0},
		{"Erfcinv", Func, 10},
		{"Erfinv", Func, 10},
		{"Exp", Func, 0},
		{"Exp2", Func, 0},
		{"Expm1", Func, 0},
		{"FMA", Func, 14},
		{"Float32bits", Func, 0},
		{"Float32frombits", Func, 0},
		{"Float64bits", Func, 0},
		{"Float64frombits", Func, 0},

        tf.math.invert_permutation.
    *   Add `tf.math.sobol_sample` op.
    *   Add `tf.math.xlog1py`.
    *   Add `tf.math.special.{dawsn,expi,fresnel_cos,fresnel_sin,spence}`.
    *   Add a Modified Discrete Cosine Transform (MDCT) and its inverse to
        `tf.signal`.
*   TPU Enhancements: