auto newAttr = DenseElementsAttr::getFromRawBuffer(
        shaped_type, mlir::cast<DenseElementsAttr>(op.getValue()).getRawData());
    rewriter.replaceOpWithNewOp<arith::ConstantOp>(op, newAttr);

    return success();
  }
};

class SanitizeGatherOpOutputToI4 : public OpRewritePattern<TFL::GatherOp> {
 public:
  using OpRewritePattern<TFL::GatherOp>::OpRewritePattern;

    // which should be removed. So the replaced PartitionedCall op should keep
    // its original arguments except for the last element.
    SmallVector<Value> args = call_op.getOperands().drop_back();

    rewriter.replaceOpWithNewOp<TF::PartitionedCallOp>(
        call_op, float_func.getResultTypes(), args, f_attr);
    return success();
  }
};

void ConvertTpuModelToCpuPass::runOnOperation() {
  MLIRContext* ctx = &getContext();

    // this is a forced/hard-coded constraint.
    auto qbarrier = rewriter.create<QuantizeCastOp>(op.getLoc(), quantizedType,
                                                    op.getInputs());
    rewriter.replaceOpWithNewOp<DequantizeCastOp>(op, converter.input_type,
                                                  qbarrier.getResult());

    return false;
  }
};

class ConstFakeQuantRewrite

        mlir::cast<DenseIntOrFPElementsAttr>(input_values)
            .mapValues(FloatType::getF32(rewriter.getContext()),
                       llvm::function_ref<DequantizeFuncType>(dequantize_func));
    rewriter.replaceOpWithNewOp<TFL::ConstOp>(dequant_op, dequant_op.getType(),
                                              dequant_values);

    return success();
  }
};

// If the quant op has no consumer, we will remove them.

                                   op.getInput(), new_reshape_shape);
    TF::ConstOp new_broadcast_shape =
        GetI64ConstantTensor(rewriter, reshape_shape, op.getLoc());
    rewriter.replaceOpWithNewOp<BroadcastToOp>(
        reshape_op, reshape_op.getOutput().getType(), new_reshape,
        new_broadcast_shape);
    return success();
  }
};

#define GEN_PASS_DEF_TENSORFLOWOPTIMIZEPASS