// OneHot op legalizations.
//===----------------------------------------------------------------------===//

// -----

// CHECK-LABEL:one_hot
func.func @one_hot(%indices: tensor<3xi32>, %on_value: tensor<f32>, %off_value: tensor<f32>) -> tensor<3x5xf32> {
  // CHECK: %[[IOTA:.*]] = "mhlo.iota"() <{iota_dimension = 1 : i64}> : () -> tensor<3x5xi32>

    "SUM",
    "SQRT",
    "RSQRT",
    "SHAPE",
    "POW",
    "ARG_MIN",
    "FAKE_QUANT",
    "REDUCE_PROD",
    "REDUCE_MAX",
    "PACK",
    "LOGICAL_OR",
    "ONE_HOT",
    "LOGICAL_AND",
    "LOGICAL_NOT",
    "UNPACK",
    "REDUCE_MIN",
    "FLOOR_DIV",
    "REDUCE_ANY",
    "SQUARE",
    "ZEROS_LIKE",
    "FILL",
    "FLOOR_MOD",

            uprank rank 1 inputs, so these layers can now multi-hot encode
            unbatched multi-dimensional samples.
        *   Added a new output mode `"one_hot"` for `CategoryEncoding`,
            `StringLookup`, `IntegerLookup`, which will encode each element in
            an input batch individually, and automatically append a new output