let description = [{
    Fixed point shape refinement pass that utilizes the shape functions
    registered on ops using the InferTypeOpInterface as well as by bridging to
    the TensorFlow op registry's shape functions. This is an interprocedural
    pass that propagates information across function calls/control flow
    operations where possible (the GuaranteeAllFuncsOneUsePass is often run

}

void LoadImporterDialects(mlir::MLIRContext& context) {
  // Load dialects involved in the conversion
  mlir::DialectRegistry registry;
  mlir::RegisterAllTensorFlowDialectsImpl(registry, false);
  context.appendDialectRegistry(registry);
  for (llvm::StringRef name : registry.getDialectNames())
    context.getOrLoadDialect(name);
}

absl::StatusOr<std::string> GetDenseTensorNameFromTensorInfo(

    // It is a terrible idea to have local MLIR contexts so we need to
    // register extensions here, again.
    mlir::DialectRegistry registry;
    registry.insert<mlir::func::FuncDialect>();
    mlir::func::registerAllExtensions(registry);
    xla_call_module_context_.appendDialectRegistry(registry);

    auto l = tensorflow::XlaCallModuleLoader::Create(
        &xla_call_module_context_, op.getVersion(), op.getModule().str(),

  }
  func.return
  // expected-remark@above {{ID: 25}}
  // expected-remark@above {{Sinks: {24}}}
}

// -----

// Tests that the pass tracks control dependencies based on TF op registry
// statefulness flag, for ops not yet defined in ODS.

// CHECK-LABEL: func @tf_registry_ops
func.func @tf_registry_ops(
  // expected-remark@above {{ID: 8}}