"message/tracking-status",
				"message/vnd.si.simp",
				"model/example",
				"model/iges",
				"model/mesh",
				"model/vnd.dwf",
				"model/vnd.dwfx+xps",
				"model/vnd.flatland.3dml",
				"model/vnd.gdl",
				"model/vnd.gs-gdl",
				"model/vnd.gs.gdl",
				"model/vnd.gtw",
				"model/vnd.moml+xml",
				"model/vnd.mts",
				"model/vnd.parasolid.transmit.binary",

// RUN: odml_to_stablehlo %s -skip-resize -smuggle-disallowed-ops -o - | FileCheck %s
// RUN: odml-to-stablehlo-opt %s --smuggle-disallowed-ops-pass | FileCheck %s --check-prefix=CHECK-OPT

// CHECK-LABEL: @main
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 975 : i32}, tf_saved_model.semantics}  {

    </magic>
    <glob pattern="*.fcs"/>
  </mime-type>
  <mime-type type="application/vnd.adobe.indesign-idml-package">
    <sub-class-of type="application/zip"/>
    <_comment>IDML</_comment>
    <glob pattern="*.idml"/>
  </mime-type>

  <mime-type type="application/x-adobe-indesign-interchange">
    <acronym>INX</acronym>

    %0 = stablehlo.composite "odml.scaled_dot_product_attention" %arg0, %arg1, %arg2, %arg3, %arg4 {decomposition = @odml.scaled_dot_product_attention.impl} : (tensor<1x100x32x4xf32>, tensor<1x500x4x4xf32>,...

  let dependentDialects = ["TF::TensorFlowDialect"];
  let constructor = "mlir::odml::CreateLegalizeHloToTfPass()";
}

def LegalizeHloToTfLitePass : Pass<"tfl-legalize-hlo", "mlir::ModuleOp"> {
  let summary = "Legalize from MHLO to the TFLite dialect";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let constructor = "mlir::odml::CreateLegalizeHloToTfLitePass()";
}

// RUN: odml-to-stablehlo-opt %s -stablehlo-custom-call-legalize-composite | FileCheck %s

// CHECK-LABEL: module
module {
  // CHECK-LABEL: @main
  func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<2xf32>) {
    // CHECK: stablehlo.custom_call @foo
    stablehlo.custom_call @foo() : () -> ()
    // CHECK-NOT: stablehlo.custom_call

namespace mlir {
namespace odml {

#define GEN_PASS_DEF_LEGALIZECOMPOSITETOCUSTOMOPPASS
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h.inc"

namespace {
bool IsSupportedComposite(::mlir::stablehlo::CompositeOp op) {
  // List of supported composites to represent using CustomOp.
  return llvm::is_contained(
      {"odml.update_kv_cache", "odml.scaled_dot_product_attention"},
      op.getName());

      // The other ops are not accepted.
      return signalPassFailure();
    }
  });
}

}  // namespace odml
}  // namespace mlir

std::unique_ptr<mlir::Pass> mlir::odml::createCheckAcceptedOpsPass(
    const std::vector<std::string> &optional_accepted_dialects) {
  return std::make_unique<mlir::odml::CheckAcceptedOpsPass>(
      optional_accepted_dialects);

// RUN: odml-to-stablehlo-opt %s --tf-stablehlo=skip-quantization-ops=true | FileCheck %s --check-prefix=CHECK-SKIP
// RUN: odml-to-stablehlo-opt %s --tf-stablehlo=skip-quantization-ops=false | FileCheck %s --check-prefix=CHECK-NOSKIP

func.func @fake_quant_with_min_max_vars(%arg0: tensor<1x1x28x48xf32>, %arg1: tensor<f32>, %arg2: tensor<f32>) -> tensor<1x1x28x48xf32> {

#define TENSORFLOW_COMPILER_MLIR_LITE_STABLEHLO_TRANSFORMS_COMPOSITE_LOWERING_PASS_H_

namespace mlir {
namespace odml {

std::unique_ptr<Pass> CreateCompositeLoweringPass();

}  // namespace odml
}  // namespace mlir