*   `tf.data`

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.

def TF_FlatMapDatasetOp : TF_Op<"FlatMapDataset", [Pure]> {
  let summary = [{
Creates a dataset that applies `f` to the outputs of `input_dataset`.
  }];

  let description = [{
Unlike MapDataset, the `f` in FlatMapDataset is expected to return a
Dataset variant, and FlatMapDataset will flatten successive results
into a single Dataset.
  }];

  let arguments = (ins
    TF_VariantTensor:$input_dataset,

          "datasetName": {
            "description": "datasetName is Name of the dataset stored as metadata -> name on the dataset for Flocker should be considered as deprecated",
            "type": "string"
          },
          "datasetUUID": {
            "description": "datasetUUID is the UUID of the dataset. This is unique identifier of a Flocker dataset",
            "type": "string"
          }
        },

		{"BRKINT", Const, 0},
		{"Bind", Func, 0},
		{"BindToDevice", Func, 0},
		{"BpfBuflen", Func, 0},
		{"BpfDatalink", Func, 0},
		{"BpfHdr", Type, 0},
		{"BpfHdr.Caplen", Field, 0},
		{"BpfHdr.Datalen", Field, 0},
		{"BpfHdr.Hdrlen", Field, 0},
		{"BpfHdr.Pad_cgo_0", Field, 0},
		{"BpfHdr.Tstamp", Field, 0},
		{"BpfHeadercmpl", Func, 0},
		{"BpfInsn", Type, 0},
		{"BpfInsn.Code", Field, 0},