#include "mlir/Interfaces/CallInterfaces.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "mlir/Transforms/InliningUtils.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"

#include "mlir/Rewrite/FrozenRewritePatternSet.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project
#include "re2/re2.h"
#include "tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.h"

#include "mlir/IR/Value.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Pass/PassRegistry.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/quantization/tensorflow/passes/passes.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

// Required to use LLVM_DEBUG macro.

  // Test that full type information can be accessed.
  auto outs = unwrap(add_outputs);
  auto h = outs->outputs[0];
  ASSERT_NE(h, nullptr);
  ASSERT_EQ(h->FullType().type_id(), TFT_UNSET);
  ASSERT_EQ(unwrap(inputs[0])->FullType().type_id(), TFT_UNSET);

  // Clean up operation and inputs.
  TF_DeleteAbstractOp(add_op);

  TF_AbstractFunction* func =
      TF_FinalizeFunction(graph_ctx, add_outputs, status.get());

						}
						t.Fatalf("test %s failed", test.name)
					}
				}
			}
		})
	}
}

// This program is intended to be just big/complicated enough that
// we wind up with decent-sized .data.rel.ro.{typelink,itablink,gopclntab}
// sections.
const ifacecallsProg = `
package main

import "reflect"

type A string
type B int
type C float64

type describer interface{ What() string }

#include "mlir/IR/ValueRange.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project  // IWYU pragma: keep
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "stablehlo/dialect/StablehloOps.h"  // from @stablehlo
#include "tensorflow/compiler/mlir/quantization/common/func.h"
#include "tensorflow/compiler/mlir/quantization/common/lift_as_function_call.h"

	mode := fmtGo
	switch verb {
	case 'v', 'S', 'L':
		if verb == 'v' && s.Flag('+') { // %+v is debug format
			mode = fmtDebug
		}
		if verb == 'S' && s.Flag('-') { // %-S is special case for receiver - short typeid format
			mode = fmtTypeID
		}
		fmt.Fprint(s, tconv(t, verb, mode))
	default:
		fmt.Fprintf(s, "%%!%c(*Type=%p)", verb, t)
	}
}

// String returns the Go syntax for the type t.

//===----------------------------------------------------------------------===//

TensorFlowSavedModelDialect::TensorFlowSavedModelDialect(MLIRContext *context)
    : Dialect(/*name=*/"tf_saved_model", context,
              TypeID::get<TensorFlowSavedModelDialect>()) {
  // The TensorFlow Dialect is needed in the verifier and other routines
  // associated to this dialect. It makes little sense anyway to use the

	data []byte
}

var dataSects []wasmDataSect

func asmb(ctxt *ld.Link, ldr *loader.Loader) {
	sections := []*sym.Section{
		ldr.SymSect(ldr.Lookup("runtime.rodata", 0)),
		ldr.SymSect(ldr.Lookup("runtime.typelink", 0)),
		ldr.SymSect(ldr.Lookup("runtime.itablink", 0)),
		ldr.SymSect(ldr.Lookup("runtime.symtab", 0)),
		ldr.SymSect(ldr.Lookup("runtime.pclntab", 0)),
		ldr.SymSect(ldr.Lookup("runtime.noptrdata", 0)),

#include "mlir/Pass/PassRegistry.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Support/TypeID.h"  // from @llvm-project
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.h"
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"