// limitations under the License.

// Revision History
// Version 0: Initial version.
// Version 1: Add subgraphs to schema.
// Version 2: Rename operators to conform to NN API.
// Version 3: Move buffer data from Model.Subgraph.Tensors to Model.Buffers.
// Version 3a: Add new builtin op code field. Has backward compatibility with
//             version 3.

// CHECK:           %[[VAL_3:.*]] = tfl.mul(%[[VAL_1]], %[[VAL_2]]) <{fused_activation_function = "NONE"}> : (tensor<3xf32>, tensor<f32>) -> tensor<3xf32>
// CHECK:           %[[VAL_4:.*]] = tfl.add(%[[VAL_0]], %[[VAL_3]]) <{fused_activation_function = "NONE"}> : (tensor<1x384x384x3xf32>, tensor<3xf32>) -> tensor<1x384x384x3xf32>
// CHECK:           return %[[VAL_4]] : tensor<1x384x384x3xf32>
// CHECK:         }

// -----

def CreateTensorScatterNdOp : NativeCodeCall<
    "$_builder.create<TF::ScatterNdOp>($0.getLoc(), $0.getType(), $1, $2, $3)">;

//===----------------------------------------------------------------------===//
// Add op patterns.
//===----------------------------------------------------------------------===//

// We can lower AddOp to AddV2Op, except for string type. AddOp is defined for

        "tf_device.cluster"() ({
          %group = "tf.Const"() <{value = dense<[[0, 1]]> : tensor<1x2xi32>}> : () -> tensor<1x2xi32>
          %arg1_reduced = "tf.XlaAllReduce"(%arg1_id, %group) <{mode = "CrossReplica", reduce_op = "Add"}> : (tensor<f32>, tensor<1x2xi32>) -> tensor<f32>
          "tf.OpA"(%arg1_reduced) : (tensor<f32>) -> ()
          tf_device.return
        }) : () -> ()
        tf_device.return
      }
      return
    }