pass for now, but should be integrated with some notion of "target" in the
MLIR pipeline in the future.
### `-tf-group-by-dialect`

_Groups ops into functions that only contain one dialect._

Factors operations into subroutines such that all functions only
contain a single dialect. Which of the dialects are allowed in the
"top" function is configurable.

For example, the code
  x.a()
  x.b()
  %c = y.c()

// This transformation pass prepares for legalization to the TFLite dialect by
// converting operations in TensorFlow dialect into operations that can be
// legalized to TensorFlow Lite dialect with simple replacements.  The newly
// created operations are in the TensorFlow dialect if the operation can be
// represented using a TensorFlow op.  Otherwise, TensorFlow Lite dialect op is

		t.Fatalf("Found deleted column")
	}
}

func TestMigrateColumns(t *testing.T) {
	tidbSkip(t, "use another test case")

	sqlite := DB.Dialector.Name() == "sqlite"
	sqlserver := DB.Dialector.Name() == "sqlserver"

	type ColumnStruct struct {
		gorm.Model
		Name  string
		Age   int    `gorm:"default:18;comment:my age"`
		Code  string `gorm:"unique;comment:my code;"`

// This transformation pass prepares for legalization to the TFLite dialect by
// converting Tensorlist operations in TensorFlow dialect into operations that
// can be legalized to TensorFlow Lite dialect with simple replacements.  The
// newly created operations are in the TensorFlow dialect if the operation can
// be represented using a TensorFlow op. Otherwise, TensorFlow Lite dialect op
// is used.

#include <climits>
#include <cstdint>

#include "llvm/Support/Casting.h"
#include "llvm/Support/FormatVariadic.h"
#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/Extensions/AllExtensions.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/IR/Attributes.h"  // from @llvm-project

            "ir/tfl_ops.h.inc",
        ),
        (
            ["-gen-op-defs"],
            "ir/tfl_ops.cc.inc",
        ),
        (
            [
                "-gen-dialect-doc",
                "-dialect=tfl",
            ],
            "g3doc/tfl_ops.md",
        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",
    td_file = "ir/tfl_ops.td",
    deps = [

#include <utility>

#include "absl/algorithm/container.h"
#include "llvm/ADT/Sequence.h"
#include "llvm/Support/Debug.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project  // NOLINT: Required to register quantization dialect.
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/IR/Builders.h"  // from @llvm-project

#include "llvm/ADT/Twine.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/raw_ostream.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/IR/BuiltinAttributes.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

// This is the optimization pattern definition file for TensorFlow Lite.

include "mlir/IR/OpBase.td"
include "mlir/IR/PatternBase.td"
include "mlir/Dialect/Arith/IR/ArithOps.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td"
include "tensorflow/compiler/mlir/lite/utils/utils.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"

						if !strings.Contains(resultType, "int") {
							t.Errorf("invalid data type for %v, got %v %#v", dbName, resultType, first[dbName])
						}
					case "Birthday":
						if !strings.Contains(resultType, "Time") && !(DB.Dialector.Name() == "sqlite" && strings.Contains(resultType, "string")) {
							t.Errorf("invalid data type for %v, got %v %#v", dbName, resultType, first[dbName])
						}
					}