Output x = ops::Placeholder(root.WithOpName("x"), DT_FLOAT);
  NameAttrList f_name_attr;
  f_name_attr.set_name("XTimesTwoFloat");
  ops::TPUPartitionedCall f(root.WithOpName("f"), {x}, /*device_ordinal=*/0,
                            {DT_FLOAT}, f_name_attr);

  TF_ASSERT_OK(root.ToGraph(&graph));
  EXPECT_TRUE(IsInferenceGraph(graph, /*function_library=*/nullptr));
}

    ConfinedAttr<TypeArrayAttr, [ArrayMinCount<1>]>:$dtypes,
    TF_ShapeAttrArray:$shapes,
    DefaultValuedOptionalAttr<I64ArrayAttr, "{}">:$layouts,
    DefaultValuedOptionalAttr<I64Attr, "-1">:$device_ordinal
  );

  let results = (outs);
}

// This op is manually defined because the attribute name `template` (which is
// a keyword) is changed to `strtemplate`.

    // CHECK: %0 = "tf._XlaCompileMlirPlaceholderProgramKey"() : () -> tensor<3x!tf_type.string>
    // CHECK: %1:4 = "tf._XlaRecvAtHost"(%0) <{device_ordinal = 0 : i64, device_type = "TPU", key = "host_compute_channel_0_args"}> : (tensor<3x!tf_type.string>) -> (tensor<3360x8xi32>, tensor<3xi32>, tensor<i32>, tensor<2xi32>)

                           "_XlaRecvAtHost", opts.op_registry());
  node_builder.Input(std::move(key_input));
  return opts.WithAttr("Toutputs", dtypes)
      .WithAttr("key", key)
      .WithAttr("device_ordinal", 0)
      .WithAttr("_encapsulate", cluster)
      .WithAttr("_outside", oc_cluster)
      .FinalizeBuilder(&node_builder);
}

Node* SendFromHost(ops::NodeOut key_input, const string& cluster,

// Helper function to get an absolute device string, combining device and
// ordinal attribute values.
std::string GetAbsDeviceStr(Operation* op, uint64_t device_ordinal) {
  std::string device_ordinal_str = std::to_string(device_ordinal);
  auto device_attr = op->getAttrOfType<StringAttr>("device");
  if (!device_attr || device_attr.getValue().empty()) return device_ordinal_str;

which to execute computations, such as `TPUPartitionedCall`.

device_ordinal: An integer in [0, NumTPUCoresVisiblePerHost].
  }];

  let arguments = (ins);

  let results = (outs
    TF_Int32Tensor:$device_ordinal
  );
}

def TF_TakeDatasetOp : TF_Op<"TakeDataset", [Pure]> {
  let summary = [{

      %1 = "tf_device.launch"() ({
        %2 = "tf._XlaCompileMlirPlaceholderProgramKey"() : () -> tensor<3x!tf_type.string>
        %3 = "tf._XlaRecvAtHost"(%2) {_xla_has_host_transfer = true, device_ordinal = 0 : i64, key = "host_compute_channel_0_args"} : (tensor<3x!tf_type.string>) -> tensor<?xi32>
        %4 = "tf.B"(%3) : (tensor<?xi32>) -> tensor<?x!tf_type.string>
        tf_device.return %4 : tensor<?x!tf_type.string>