// MainOnly is true if the caller only wants to load main packages.
	// For a literal argument matching a non-main package, a stub may be returned
	// with an error. For a non-literal argument (with "..."), non-main packages
	// are not be matched, and their dependencies may not be loaded. A warning
	// may be printed for non-literal arguments that match no main packages.
	MainOnly bool

									ContainerName: ptr.To("main-container"),
									Operator:      batch.PodFailurePolicyOnExitCodesOpIn,
									Values:        []int32{1, 2, 3},
								},
							},
							{
								Action: batch.PodFailurePolicyActionFailJob,
								OnExitCodes: &batch.PodFailurePolicyOnExitCodesRequirement{
									ContainerName: ptr.To("main-container"),

  // Entry functions for signature defs.
  std::vector<FuncOp> entry_functions;
  std::vector<FuncOp> non_entry_functions;
  FuncOp main_fn = module_.lookupSymbol<FuncOp>("main");
  if (main_fn != nullptr) {
    // Treat the main function as a signature def when the given main function
    // contains on the tf.entry_function attribute.
    auto attrs =
        main_fn->getAttrOfType<mlir::DictionaryAttr>("tf.entry_function");

                         ops_to_skip);
  auto main = module.lookupSymbol<mlir::func::FuncOp>("main");
  // Error if no main to refine with input shapes
  if (!main && !input_shapes.empty()) {
    return module->emitError(
        "Input shapes provided but no `main` function found.");
  }

  // Add main function to head of queue, refine input shapes if provided
  if (main) {
    if (!input_shapes.empty()) {

			}

			// Remove duplicate main symbol with runtime/cgo on AIX.
			// With runtime/cgo, two main are available:
			// One is generated by cgo tool with {return 0;}.
			// The other one is the main calling runtime.rt0_go
			// in runtime/cgo.
			// The second can't be used by cgo programs because
			// runtime.rt0_go is unknown to them.
			// Therefore, we let ld remove this main version

    // CHECK-NEXT: "tf._TPUCompileMlir"(%[[A_SHAPE_OUTPUT]])
    // CHECK-SAME: metadata
    // CHECK-SAME: mlir_module
    // CHECK-SAME: func @main
    // CHECK-SAME: tf.B
    // CHECK-NOT: func = @tpu0_func
    // CHECK: "tf_device.launch"() <{device = "/job:worker/replica:0/task:0/device:CPU:0"}>
    // CHECK-NEXT: "tf.TPUCompileSucceededAssert"(%[[COMPILE_OUTPUT]]#0)

	CMPQ inl, $256
	JBE  sealAVX2Tail256
	CMPQ inl, $384
	JBE  sealAVX2Tail384
	CMPQ inl, $512
	JBE  sealAVX2Tail512

	// We have 448 bytes to hash, but main loop hashes 512 bytes at a time - perform some rounds, before the main loop
	VMOVDQA ·chacha20Constants<>(SB), AA0; VMOVDQA AA0, AA1; VMOVDQA AA0, AA2; VMOVDQA AA0, AA3
	VMOVDQA state1StoreAVX2, BB0; VMOVDQA BB0, BB1; VMOVDQA BB0, BB2; VMOVDQA BB0, BB3

      return {0, 0, 0, 0};
    }

    auto padding_values = padding_attr.getValues<int64_t>();
    // Padding has [[h_low, h_high], [w_low, w_high]] format.
    // https://github.com/openxla/stablehlo/blob/main/docs/spec.md#convolution.
    return {padding_values[0], padding_values[1], padding_values[2],
            padding_values[3]};
  }

  // Returns the input and output dimensions, respectively.

    // side.
    //
    // We also use this as the name for the NameLoc for ops in function, since
    // otherwise our names could collide across functions.
    // For ops in the main graph, we omit the "@function_name" (which, would be
    // just "@" since function_name would be empty) because some code seems to
    // depend on the name being this way for correctness.

		}

		if rs != 0 && (rst == sym.Sxxx || rst == sym.SXREF) {
			// When putting the runtime but not main into a shared library
			// these symbols are undefined and that's OK.
			if target.IsShared() || target.IsPlugin() {
				if ldr.SymName(rs) == "main.main" || (!target.IsPlugin() && ldr.SymName(rs) == "main..inittask") {
					sb := ldr.MakeSymbolUpdater(rs)
					sb.SetType(sym.SDYNIMPORT)