type: DT_FLOAT
    }
  }
  attr {
    key: "shape"
    value {
      shape {
        dim {
          size: 10
        }
      }
    }
  }
}
node {
  name: "MlirPassthroughOp"
  op: "MlirPassthroughOp"
  input: "x"
  input: "y"
  attr {
    key: "Tinputs"
    value {
      list {
        type: DT_FLOAT
        type: DT_FLOAT
      }
    }
  }
  attr {
    key: "Toutputs"

        "@local_xla//xla/translate/mhlo_to_hlo:type_to_shape",
        "@stablehlo//:stablehlo_ops",
    ],
    alwayslink = 1,
)

cc_library(
    name = "mlir_passthrough_op",
    srcs = ["ops/mlir_passthrough_op.cc"],
    visibility = [
        "//visibility:public",
    ],
    deps = [
        "//tensorflow/core:framework",
    ],
    alwayslink = 1,
)

cc_library(

mlir_module = '''python
func @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> {
   %add = "magic.op"(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32>
   return %ret : tensor<10x10xf32>
}
'''

@tf.function
def foo(x, y):
  return mlir_passthrough_op([x, y], mlir_module, Toutputs=[tf.float32])

// Transforms region bases control flow operations in the TensorFlow dialect to
// their functional counterparts.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFRegionControlFlowToFunctional();

// Materialize the MlirPassthroughOp by replacing it with the MLIR module
// attached as an attribute.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateMaterializePassthroughOpPass();

      return %2 : tensor<?xi32>
    ```
  }];
}

def MaterializePassthroughOp : Pass<"tf-materialize-passthrough-op", "mlir::func::FuncOp"> {
  let summary = "Materialize the MlirPassthroughOp by replacing it with the "
    "MLIR module attached as an attribute";
  let constructor = "TF::CreateMaterializePassthroughOpPass()";
  let description = [{

  return %0 : tensor<i32>
}
```
### `-tf-materialize-passthrough-op`

_Materialize the MlirPassthroughOp by replacing it with the MLIR module attached as an attribute_

A pass that replaces MlirPassthrough ops with the code they have in
their `mlir_module` string attribute.
### `-tf-merge-control-flow`