#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project
#include "stablehlo/dialect/StablehloOps.h"  // from @stablehlo
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.h"
#include "tensorflow/compiler/mlir/quantization/common/uniform_quantized_types.h"

#define DEBUG_TYPE "uniform-quantized-stablehlo-to-tfl"

namespace mlir {
namespace odml {

#include "tensorflow/compiler/jit/encapsulate_subgraphs_pass.h"

#include <memory>
#include <utility>

#include "absl/strings/match.h"
#include "absl/strings/str_cat.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/compiler/jit/encapsulate_util.h"
#include "tensorflow/compiler/jit/extract_outside_compilation_pass.h"

            return "hi";
          }
        };

    // We'd like for all the following to compile.
    ListenableFuture<String> unused;

    // Compiles:
    unused = whenAllComplete(futureA, futureB).call(combiner, directExecutor());

    // Does not compile:
    // unused = whenAllComplete(futures).call(combiner);

    // Workaround for the above:

            return "hi";
          }
        };

    // We'd like for all the following to compile.
    ListenableFuture<String> unused;

    // Compiles:
    unused = whenAllComplete(futureA, futureB).call(combiner, directExecutor());

    // Does not compile:
    // unused = whenAllComplete(futures).call(combiner);

    // Workaround for the above:

from tensorflow.compiler.mlir.quantization.common.python import testing
from tensorflow.compiler.mlir.quantization.stablehlo import quantization_config_pb2 as stablehlo_quant_config_pb2
from tensorflow.compiler.mlir.quantization.tensorflow import quantization_options_pb2 as quant_opts_pb2
from tensorflow.compiler.mlir.quantization.tensorflow.python import quantize_model

include "mlir/Interfaces/LoopLikeInterface.td"
include "mlir/Interfaces/SideEffectInterfaces.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_op_interfaces.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_op_enums.td"
include "tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td"

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

// easier to write, but generates horrible messages when there is a
// compiler error, as gcc insists on printing out each template
// argument, even if it has the default value (this means Types<int>
// will appear as Types<int, None, None, ..., None> in the compiler
// errors).
//
// Our solution is to combine the best part of the two approaches: a

// easier to write, but generates horrible messages when there is a
// compiler error, as gcc insists on printing out each template
// argument, even if it has the default value (this means Types<int>
// will appear as Types<int, None, None, ..., None> in the compiler
// errors).
//
// Our solution is to combine the best part of the two approaches: a

}

func TestGCBits(t *testing.T) {
	verifyGCBits(t, TypeOf((*byte)(nil)), []byte{1})

	// Building blocks for types seen by the compiler (like [2]Xscalar).
	// The compiler will create the type structures for the derived types,
	// including their GC metadata.
	type Xscalar struct{ x uintptr }
	type Xptr struct{ x *byte }
	type Xptrscalar struct {
		*byte

)

// Reference imports to suppress errors if they are not otherwise used.
var _ = proto.Marshal
var _ = fmt.Errorf
var _ = math.Inf

// This is a compile-time assertion to ensure that this generated file
// is compatible with the proto package it is being compiled against.
// A compilation error at this line likely means your copy of the
// proto package needs to be updated.