<jsp:param name="menuType" value="webAuthentication"/>
    </jsp:include>
    <main class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.webauth_title_details"/>

        <jsp:param name="menuCategoryType" value="system"/>
        <jsp:param name="menuType" value="dict"/>
    </jsp:include>
    <main class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.dict_stopwords_title"/>
                        </h1>

        <jsp:param name="menuCategoryType" value="system"/>
        <jsp:param name="menuType" value="dict"/>
    </jsp:include>
    <main class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.dict_stopwords_title"/>
                        </h1>

        // of A, B, C, and D, so when scanning B and D, E will be added again 'filtered'.
        //
        // Without de-duplication, the final list would contain E three times, once for E being in the projects and
        // whitelisted, and twice more for E being a downstream dependency of B and D.
        return filtered.stream().distinct().toList();
    }

    @Override

   *
   * <p>This implementation is highly efficient when {@code elements} is itself a {@link Multiset}.
   *
   * @param elements the elements that the multiset should contain
   * @throws IllegalArgumentException if {@code elements} is empty
   */
  public static <E extends Enum<E>> EnumMultiset<E> create(Iterable<E> elements) {
    Iterator<E> iterator = elements.iterator();

     */
    @Nonnull
    Optional<Boolean> ignoreTransitiveRepositories();

    /**
     * Specifies "@file"-like file, to load up command line from. It may contain goals as well. Format is one parameter
     * per line (similar to {@code maven.conf}) and {@code '#'} (hash) marked comment lines are allowed. Goals, if
     * present, are appended, to those specified on CLI input, if any.

/// tip

Keep in mind that JSON only supports `str` as keys.

But Pydantic has automatic data conversion.

This means that, even though your API clients can only send strings as keys, as long as those strings contain pure integers, Pydantic will convert them and validate them.

And the `dict` you receive as `weights` will actually have `int` keys and `float` values.

///

## Recap { #recap }

        <jsp:param name="menuType" value="scheduler"/>
    </jsp:include>
    <main class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.scheduledjob_title_details"/>

        <jsp:param name="menuCategoryType" value="system"/>
        <jsp:param name="menuType" value="dict"/>
    </jsp:include>
    <main class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.dict_mapping_title"/>
                        </h1>

// graph_def.library().gradient()
std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def);

// Returns a sorted vector of names contained in `grad_def`
std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def);

class CSession {
 public:
  CSession(TF_Graph* graph, TF_Status* s, bool use_XLA = false);