let summary = "Converts two real numbers to a complex number.";

  let description = [{
Given a tensor `real` representing the real part of a complex number, and a
tensor `imag` representing the imaginary part of a complex number, this
operation returns complex numbers elementwise of the form \\(a + bj\\), where
*a* represents the `real` part and *b* represents the `imag` part.

		{"MakeFromLiteral", Func, 5},
		{"MakeImag", Func, 5},
		{"MakeInt64", Func, 5},
		{"MakeString", Func, 5},
		{"MakeUint64", Func, 5},
		{"MakeUnknown", Func, 5},
		{"Num", Func, 5},
		{"Real", Func, 5},
		{"Shift", Func, 5},
		{"Sign", Func, 5},
		{"String", Const, 5},
		{"StringVal", Func, 5},
		{"ToComplex", Func, 6},
		{"ToFloat", Func, 6},
		{"ToInt", Func, 6},

        "properties": {
          "path": {
            "default": "",
            "description": "path of the directory on the host. If the path is a symlink, it will follow the link to the real path. More info: https://kubernetes.io/docs/concepts/storage/volumes#hostpath",
            "type": "string"
          },
          "type": {

*   Added Java API support for Windows.
*   Added `tf.spectral` module. Moved existing FFT ops to `tf.spectral` while
    keeping an alias in the old location (`tf.*`).
*   Added 1D, 2D and 3D Fourier transform ops for real signals to `tf.spectral`.
*   Added a `tf.bincount` function.
*   Added Keras 2 API to contrib.
*   Added a new lightweight queue-like object - `RecordInput`.
*   Added `tf.contrib.image.compose_transforms` function.

Length of all the Colours, were the Circles of which (as we shewed) that
Spectrum consists contracted and reduced to Physical Points, so in that
Case this corrected distance would be the real distance of the two
observed Colours.

When therefore I farther observed the deepest sensible red, and that
blue whose corrected distance from it was 7/12 Parts of the Length of