<table border="1" cellspacing="0" cellpadding="8">
    <tr>
        <th>Issue</th>
        <td>
            <a href=https://github.com/llvm/llvm-project/issues/97680>97680</a>
        </td>
    </tr>

    <tr>
        <th>Summary</th>
        <td>
            `lambda function` return type deducing seems to be broken in the newest versions of `clang`
        </td>
    </tr>

    <tr>
      <th>Labels</th>
      <td>
            clang
      </td>
    </tr>

    <tr>
      <th>Assignees</th>
      <td>
      </td>
    </tr>

    <tr>
      <th>Reporter</th>
      <td>
          Life4gal
      </td>
    </tr>
</table>

<pre>
    I wrote a piece of code for testing purposes:
```cpp
#include <algorithm>
#include <functional>
#include <ranges>
#include <vector>

template <typename F>
struct y {
    F f;

 template <typename... Args>
    constexpr auto operator()(Args&&... args) const -> decltype(auto)  //
    {
        #if USE_INVOKE
 return std::invoke(f, *this, std::forward<Args>(args)...);
 #else
        return f(*this, std::forward<Args>(args)...);
 #endif
    }
};

struct list {
    std::vector<list> children;

    int data;
};

struct list_wrapper
{
 list l;
};

int main() {
    struct test {
        int a;
 int b;

        auto operator+(const test& o) const noexcept -> test {
            return {a + o.a, b + o.b};
        }
 };

    auto f1 = y{[](auto self, const list& l) -> test {
 return std::ranges::fold_left(
            l.children, test{.a = l.data % 2, .b = l.data % 4},
            [self](const test& total, const list& nl) -> test {
                return total + self(nl);
            });
 }};

    list_wrapper lw{.l{.data = 42}};
 lw.l.children.emplace_back(std::vector<list>{}, 1337);

#if CALL_F1
 const auto r1 = f1(lw.l);
#endif

    const auto f2 = [f1](const list_wrapper& l) -> test
    {
        return f1(l.l);
 };

    const auto r = f2(lw);

    return 0;
}
```
The result of the compilation is shown below (you can also check out the [godbolt link](https://godbolt.org/#z:OYLghAFBqd5QCxAYwPYBMCmBRdBLAF1QCcAaPECAMzwBtMA7AQwFtMQByARg9KtQYEAysib0QXACx8BBAKoBnTAAUAHpwAMvAFYTStJg1DIApACYAQuYukl9ZATwDKjdAGFUtAK4sGIAMykrgAyeAyYAHI%2BAEaYxCBmAKykAA6oCoRODB7evgGp6ZkCoeFRLLHxSbaY9o4CQgRMxAQ5Pn6BdpgOWQ1NBCWRMXEJyQqNza15HeP9YYPlw0kAlLaoXsTI7Bzm/mHI3lgA1Cb%2BbmLAJIQILCfYJhoAgjt7B5jHp1ReDN0CYrf3TzMu2%2Br3ebmIhmAmAU/0ezxBXiOJzcADcukRiLCno8CJgWCkDLiwQQAJ4pRisN4AMSxY2IXgchxJxwA7FZHodOYcqYcqCd2diHlzDrj8YS3sjSeTmGwAHTyw4PYjAGH%2BO4crloBhjTCqFLEQ5MLxEQ6ockQjEQJYQJUq8wANgd8tlhuVCiWhy1Y0OAFpbocsPspZgIEaiB7DgB6SMA4UmNmx4Vc55UQ5yITYAD6AEkIgA1ADyAGl1UKk5ziJgCOsGIcxugQCAwijUABrENUUiHABUBAQeAUXfrjf4xAA7k10MjbarsKG3UtnUt%2BYnyzsakpV0nK9XiLWqBBe/3B3WCA2QKOJ8Qp6cZ7d5yrF/Ll/4BeXOeuGPg%2BRqPyyACIAvGgGvkBjx0gyBCHLQA5QfGb5csOIBog4JDIjBYz%2Bsg/a0OglYMCucK/ocYRQegTCNIRTwAVRAIQYyGEEJmY4Qik5pAQmxGMdBtE0aBREPKRhwsEwYRWqyCGcvRUG4t68FbsKQlMFR74kYIhzRLRxHCmGqCmuaFFoZYEBejJ0IEA6poeqZhwMKguqbCkUF%2BmqIrmRJCnvjuNYSUwxyWKaspMF20T%2BRYgWaXxklJsBW6xfxgo6caelUFw7z/ky8mJFYiT/qGyV1jUnaegI3qMZZtAei52BuXJnFluW3l7qe54QkY0Ijp46CZvQVAEBAnnlrQsrYXQeGMF2skWWyQXpdBsrkY0/mJIcZhdrKoUnBlw2LX55grZIwGkINMXZXYfK5SZpVmZhZj2iKqCNLQXY2eVd22ZVvr%2BlNHnaapXJNbWRBPWFhW0AeDCVSp/1/v%2BL7RbFUVgQ10GwcxrHmtBY7wbKtA47tc2SGYiMgdFtBjrjI04eNDCyniBJMJsmbRIzrYQEhKEYuhsH/AmAFdlw/j%2BCy8PIymhxuA8wTBJmVJcFuNm6YcxBpVtvJcBA5O46LcJAq4eA/olmrXYaBVUGYc0mNlqVW3lr1oyxTBsXEFVVd95lxfVqmA%2Brmva9DsNaSjisFQaavm5rY460bFZVj5Gi8f%2BHArLQnCJLwfjcLwqCcG41jWHWawbBKQI8KQBCaMnKytgEiSyv4ACciQNw39qJFwAAcLJcFwDdVKnHCSLwLASBoGikJnWikDnHC8AoIDjxXHBaCscCwDAUAbxASBoPidBxOQlC7yk%2B/xPskKZgQ9IMK2fB0LixDzxA0SV6Q0RhE0JKcGX7/MMQJIFmiNodE39eC7zYIIAskMv7L14FgaIXhgBnFoLQeeWdSBYBEkYcQsCMF4ErN0NEaCp66i6MaLYZdSI1FAfoPA0QIT/w8FgV%2BV88Aj3QWiYg0R0iYH/HiSEMEjCVxWFQAwKo8x4EwGOAs0oaH8EECIMQ7ApAyEEIoFQ6hcG6C4PoSEKB86WFodEeekAVhmjqNqTgPp6xbVMJYawQJs6cOIHgLAJirTVFqFkFwX5Jh%2BB0SEOYZQKh6DSBkCxfjQmFAsQMYJwwdGdB%2BAwXoExPBtD0IkixKTZilCGPEBJMxIkFL6LEvJEgVgKCLpscp%2Bg04Z1fjPQ4qgO72h9PaSQnoDBGEOBAK%2BXxWweggLgQgJB/L%2BC4EsXgS8V4rAQJgJgWB4geJrkLWUZgkiJBZJIbud1JD%2BHtB3Wpg9h4JH8LKLgLIWT%2BA7v4ZuGhW43MSIcye2dOBzwXuXYRpA16IBQKgPe9AyAUCugC4Y58jCX2vrfGgtAH5Pxfrg3%2Bn8aFIv/oA4BDgaHgMYAQKBtAYFT3gYg5BqCaGYIEVsQl%2BD0R4CIa/UhyByE0KoQPMuMF6GfyYZSqZLj2Fl04dwpQfCsHAEEaAWBIixEKAkVImRjA5GyEUeIFR8j5BKDUK/XQ9pdFCLsVYQx7L3FmKclkNB1izy2IMRYIEvp/zpizLmQsJYtpl1QM41xHVTGeJpc4CArgilBC/KUhY%2BSCjhKyAGsJRQGDBpCQkmoPrkmFLSXkeNXj6gzFjfE2wybcj%2BJzSUoJZSJmrHWNUktA904TwaZwJpLS2kdPBcAHpfSb6DOGRiMZEypnCNmfMxZlAU6cCHqQEeZgWSyiuWYDQzchYN38Ns7VLzp5vNsB86Zydvlbx3v8k%2BgLD4gr3WCrpwBIX9LvrCuI8LX6opgT/D%2BaKgEgPQdiyB0DX5EqQWIUl6DyXYO5Xgghjg6W4IZUy9BLKaHsoYSSLlLDeU0IFTw4VAiwjipXnwKVMrpGyPQaqpVyjpCqvURqrRCQdXGCtUYo108TWlSsTY/w/49UOP8LayW0tZbyyY6691bj4AVITUknx7gU35sCbkkNUTw0CEjdErIWbQ2ZJ6Lm9JabE3ZMUxk1TqaC3NC0yWypZblFDo4FW5djTmmtPaZ0yELaoXtvwJ2nY3bPkSr7Qs4YHiB4jrHZIWUHcnn2jMJILu6ym5AmeTW2ea7F5fJ%2BdvP5oKgVH13afFAJ6z03wvXCygCKp63pRQ%2BgBT7MUvv%2BRA3F77cGfpJWgsuf7RUAfwEB2lHVQOqDIbiZlghqHoOg5yjAAHWF8t4EhoV/DsFoa%2BaIpg4jJE4flXhxVohlVEdkCRzRU9dDJBPfo%2BxBq6E0fMaahjFqmMscsDan0/4OMyzli6219qcz5mLHcHjTi4guP4165Tvr/Vib0BJ%2BYcaw3RrkzJmNRapPqaSdkgNf2k2Fsk6DsYfQEeZuh3GipVSTNHPM9Fut1nG0nvs/0xzIyw6l0mW5mZRzfMJH86XedZhe5XI7hznRFnV3zzi%2B50gNd7RnKuSyMwHcG4zskPOxI9oG5HP8PU3BM8e0Sq3fABLO7ksHuPulptncuDjxhbl5%2BN7itFb/iVjFS8y6vqq/ij9mAEFfpQfVuBk2msfupYQ9rJDOuMu6xB3rrLeADcYUN%2BDbDENxEFbw93YqZtYYW3KzOZd8OrcI6otVGjNUgGkHty7NhDUCdoxYs1jHmNWscdPPjnqPGI5E5EswcvgdxMqIcqNETAdN7BzErHixDmI/h13uXg/Mco/73plow/J9abFzj4zNTK2K6npZ%2BtNmm2HE7uc2UGgekdtGS5mnG6lgeYHcsgI9o1nBe7vcyQiQNDtPGfTk59/q1K55%2Bu%2BL26ktHpS4e3XJ6FyGgOiRuV6eWpuFu5un86Kz6NuFWOKeKBKbuTudWZKcezWXuwGPuvAYGAelCQeUGdCMGcGuCI2UeXCyGce02qus282squGqeK2SiEg62ai6qW2Og%2BQ%2BeVGReXqJ29GHA5qN4FeB21qCu1eX2HqNG9efqvigOASQafeoaHeEa8hPeCmShGSQmWSOm%2Bao%2ByOIO2aaOqSea2mBhreNSRmxci%2BdSb%2BK%2BtaVmDatm3SFyO%2B5ye%2BTmB%2B1OKudOcynmSypmDOr%2B3OMWvOtOVcAuF%2BV%2B46BuDcd%2BD%2BeyOiA84hIRPhERNcd%2BAWXA7cGg1ybcTe3ccuA8ZgJyBu48qR4Rq8W83%2BOu%2B6wKtRwwwAUgIB98YBJuiKZu6Ct6MBZWcBLAlWiBDuKB36ruGC6BnurWIGvuXWFCvAkG/WRBg2zCpBCGHC0elBIq8eNBie9BS2jBCi6eLBmem2OeLIFG%2B2%2BqheR2xe/Bligh5eBeVebqkhP2de2h3ishomphCh6ABm6hsmahKhxQmhsOOh6Oah%2Bh%2BmIJk%2BGO5hxa8%2B1hFathIRROThwAyAyAm%2B/maUQynhVO4yR%2BvapAfhZ%2B1cpyk6Hc467cVJeyGg2yz%2Bo6IAwR0W7yfOGGGuP%2Bp82uaWgKIATRT%2BoBj84BHRkBXRxWPR1uYC8Bb69uNWjuxKIxaBmxGBkx2BQQfu4G%2BBuIweRixB4eKxkeaxFBE2mx1BGGtB0qSeDBvAaezBKqG27BOehy3Boh1GNxdGdxQhlqohTxNe0h7x/2ch3xgavx0JQJ2QgJ8mwJ4%2BSmAZSOJham3qcOY%2BhhSmuhZhUJMZlhuONhZmy%2BryHAqJNm6JmJgs7huJlOXahJ/OJJXmgRL%2B5RLJsWlRZJW%2BLIHO4urc2RLcGgHOa0yR%2BZK6MWx%2BpmJRdhBZaRJ%2BpAnCGQzgkgQAA%3D))
![image](https://github.com/llvm/llvm-project/assets/52756109/6dae022a-2747-4fc8-b5b5-8ec95e55c6fd)

I found this error with Clang-CL 17.0.3 on VisualStudio, but testing on godbolt I found that Clang 17.0.1 and Clang 18.1.0 don't have these errors.

Confusingly, in `y::operator()`, I can't use std::invoke unless I call `f1`(even though this call theoretically doesn't make any sense for our code).
</pre>
<img width="1px" height="1px" alt="" src="http://email.email.llvm.org/o/eJykeceOo8rb99UwG3RauAjGi1lUYcAEG4MDxpsjDEUwORnw1X8Cpiefv_TpbbXopsITf08oym2aOMwx_kqwiGC3X9yujYr6qx4HmAnd9Muj8MevCtnXRYtJlyxj7GGyCEiv8DEZFDXZ4qaN85Asu7osGtwQNCSoLUFBgqOWX68sv40AOs69tPMxSdCCm4ZFHbdRRtDi3-aDLvfauMjd9D8W1G4eTvz-OvnCXlvUPybnZ4uzMnXbeUE7ljh3M0xK3xc1bd15LTmSxBotIyRJkhIZEDT6mQz5NzofHx8krMMf8kx7vSJvWjyUNel2bUEWJa7dSSzAE2BDAH7eADgCcNN2d37bLLvIfwhaJH3spRMHAvAThWmWJIA0_X5n8ou08wCg44C8nMR_lcPV0D7lqXHb1TnZtP7kIxrG-atIJsoBAQSSALCN4mb69_uKoKh7t_YJWvjUDPDfhPz4-JhU-DTMxBOnDf5VkG8cg1nf_zP53I-Dn7XefvPJevubf775MY2b9lfjfOf8iQ5hWjPZ2Yvi1K9x_runSZKM85b03db9MfW_GP7b125Z4vpz6Sf3WZj0f9CY2GRunC_Y-F3umf4Uan96e9r4Q7j59fEXNaaf30CICMAvWJsoE4Ajix_wyws8eLj8hsO_s_7Jx8QauSQBEFl8uJOTH99eHj9r-h2gn74j_7TDdzmDFUnQW3KcuM656VsMkA1OZ8Qucs4eBByZTqL_TdbfYf-ZNhYEpv6_KQ7ayep_qJZ-fIcFEBYbrdGHO4uVfkyYIAnAkmCa_Xj8PsxMugHhT7IEi2YVZo1-tX9btG76p275fyr32883XWcyswMWW_EzgT_c8OmKXwJtvf27T34GN5n2kyXS6bHoS29JBvy2l0z7jx8m_Jhzpof_fbheQgD-P2NxUm62HLmi6fXPwv3I8wEpQF3_V1p947SYa0ZHvcAmWBGAnwT4hcAvWeS3NP0NdWDeTrAoWP3soV9i-w-4_Y9k_JkDZ3l-Fec_0P-zMosuYNblT1P8RJ_6JbX8WoCX13OEyRo3XdpO9buNMOkVWRmn7lRkybghm6joc_KB06InCcCPRUd6bk66aVOQXoS9hCy6dt5IsCgs_EeRTnbJk8VOUduWc1jN5enb_EdRh_MA_SZoaDh6GEEJVT5rCgN0-qOD9kKGLB_pUFqZggfdoyjA_btH7R6uodlL7d5EI7TCjdaajgjHJn5Q5g0KA48Q1AqUnyG8wF3Zw_0LSs751KrhaqvAEgoONDunS9LNHZ77rfb0oSxdWqgxjazA_ZjUIRwxHB24UwjAAgRF1xkElEFtTCDkCqGwjC1a41col9w9EQosWbq-G04P19kUjGCG1n6AJnvMOeSXoWGbqwMSbGt_E9XRrA5vd8Xu8HHjOMe0pxKY6m5xa87KGr0zAkjZTqHTEK6Ex8z9kelQVUxFFwJHjQoYPts1Yp-7cmXh7YESnDqgz-99B-bVNY0fmRJlMIMXAkgUfg_oFhvq24Nbr0usWBfyghfU0BaSrR73pglVprTi5sDA_WlwgHILvWhQhx6upfuu8A3HqxyvEnzgx7v0va2fvHOim-cJnzO5h7vz2DNH5wnl3czfYLw6LVD0PAuVpIsmu9cH0eQKLzGfoqk6pnqp-B4eQp9v06i7CrEdjSuHMqBUPgqvOTblPVREN0brbYi40x4yl-yQDczVY9mLyY7K2YFbDoqJEsIV3I5QTlcXLWHfsRoKRiMr3tCFpgD7-HmBqBYPl0u8g-iCoInh5RbUz4AZIFwnK2r_fLh1o8n0pc0v7Sy-k4_vxk3KK5Vrm1us2xVCmAASjWhbgMDUDJU3S867r312rCdA6ykBJAbhm4E7-RjOVKzqOI5QUOBLDuVXgp4DFY5I2OkmZM1AfrBeYyioCBl1qzyR8543NVNAuJQRps5e6DyNAFLhOZaJw7NwUKxzD68WVExnlEVRzRzGjBO2hGY2yHsftSLlIks8albUN2LvWHY1CrL3si4y03K89Gg0M91L1ppJHCV6W7o17IRMroSscyWpuDsiwk-VUkTIlQWu7lG_18KuegjJRZqlyyqlzixVyF_P7uCcLv0w2prblHsJUOdFaSe03duQpGqDbG4IhrDgPBenF6lfvwkgJSOfqZITnwkgVfJ4XT0vuYtDha7293sLccwC1N3UXEo7m07XFWYZM3Eo5VkynHB_mVcoIpjnaW02tXMzsbyXQJPY9mjeSh81deJQU_CoineP_ForLjlKe6DfWDas70ovJ8phf7vfnEBjT_fymt2j-xPEWiUcdPPmAHz1AbhfX_WsTHrY5a5b3tTDw7bQ0ZYim4J4K1xPJQGkFQGk17xOX1sP6XINzRUl995Q77IWOev-obWQWbceOMlOvA99qUXP-qlQDD5shTGPkbpXm-xhKe_aMcVIE50uanYEkGAGJX9K6dJzpi-M_FEZs2joIN-fkZpdVU_qDhnneAMqr-1L9RBkDYbTPRVWDJ6ybJFm9c1x0fUiOx6VHdLqatNpvSrG4Yyamyhdr_6GTYfgWmVwSRrZy91sm4N7esaNZLruK2Nrh-Goh3S_Plk5no4CLEA7WOtmLqh6Hzw9va8ET2ZWT3tnu_0DaabCayYS3H2ujW0oxqfxxUDBi81DT28qVeoh9HTVk_qtf9XynXDSex2eUCHHiZrbcbLNdwIPC2X7HG475AqNJ_RbeIGPYVp1jH00GGYqrMdkFoYA0nBsEu0emhtlr4EAUXo8bN8DpE5XzqSsSKRUzZNvawJI-72pKlIWHwpfpDdYWL8dRYFNsn-t9RUjha5yi0KUS4VuYmz7J-QgMXE8sxH2EiPWB-ogukLJcTG3d3Xn7p-UlQSD4ggpU5kA3fNSeJ3FuvI8fNKmHTshZVGxM3l1F5_EvfgUroMtmbDXCn5gxF42YEMV7o4XRUHZm2tYwlEUlUIyuciTOYE5FidRQzxnS4UvYpzAa5Q9q0N1Do8lNzyue9Vxe1NtOM9QdqEO1bg-X6VKSqT-xqrRLA6iTqLh3E0t4rYnlAhD8DQzCTbm3lH73pd9tJS4_laIwxG1W0pJ4kE73-NUkI8iUveDkkg6p4svVQyvoSboZeOV86aQYu6r4Hk0mSo01iDaHN2TmRdbJIsGgtq85jbYPQ5DPTRDdXKZvsCaEZtbeOKvTA1NNVRDGzEhVutEty_3MIlVdFeVR-ev1O0CvBbRdhluIkbd8bqmh7piL1kHrl_MvZMjm6H3J8UbMfAN9O5v3c2xSrjiFGRq4RFv4AgvQhcKjMPyT-EGXnUghy3cscchqEN6ppXzrqS8pgiCDNqG7i7cO9DUUAsd6UyHTsiiSnBlRxGvjZnOW7aUxQiKSwDpEo1oFCmtMI_7bi9xcjA691N1159ASinG70szEJodFEUX2kiJB1GDyVXJrCdk5VG8YEWy-CeLtO1lSv03c1P6kqA3V8cc1jotZZqXJge0it8jUPaWo4ivKRW9y_itZ2ajOm2Zrsw9sxp217OM1dJjpuNznCKBAJJ2iZxZ4JPwjLQRyo1qmfIWlYKZZMWxTjJJP90SfLg9ufAtPQMR9OPDW5KQ-j5dCvV-UrN6Zx8uSQs3FHPu3XuvlvoJJP4ReXBXBqcHtzVkK97fxbHMhUMW7Id7Ci-cJ-wqU8T30D6NcWc7W_PtRc6B5g_N-qq_S_Z1aBDP3Uf_lT4G-sUvER7qWyasaVuoyx4pt43-qoVO4fUbV5ThFHULOFwtFMOj6ccjorY3VqxMW7mk3Ha8OQZ7C8PoGXI2o9wv4wbpmrtrCud00lN9iy-UIp175grj_hmXt7zXrvu6lMej6VbldXyWQvW6WFVtCaZ_k4X24hQrij_b6ak5O1PUT6V_czGOvO6ONtXeH-PocNxm9Xgy8KqcL0k-rMMLzTbCI0kOl3NPCeLTF2vFfpjgrnJ6tlHdh0jf95chWZ0rV6APAjXaY3l_pNK2YCSb9Z_nLGuP7p0axalRbF-9CnKHfhyTU702G8bZxYh51ru7Yl92Xp6D515V9I4bMxZm-GwD7K4lNlBnY_mvI1to4XW3ot1Agir3puj-dRPGUNBKji4tczE9Oq_3l9dS5CxIS-u1JwelaodNF6ytCwx6EYF0dzWNaqs84nsaRtWuMEJ2fEK4syW-ZcSouE5OaqTCXRyllCHzVEUmSG_RcC2i9Cr6iWC9rcvG36roGBTzugFVnEgFe9eNnlKV7Ruv2br5VN0ZYz--05gDq03lvdlM33m75zlmwu7IrDj2PFVv6Ro_KLRo63huT1t18lazg-WWx8o9-Ul4CEACpCbhto0TTLjsIlqOy-vpfNgd9xupa1e5TOWvZmqgh7cy9lxKZTab3a13sFd3PHfD_j3C7E1ZR-_ckvIr_X7HM0eWCg_-2sq17jTu-50nM-8mORqDsilkdnfkjxca7XlMnSo6gEg31kmz645dWra5122fQ_RI2ZnQYR230oMAUnx9Sid-5F5VNb09NxkUpaA0g2uHEpA1QVc65qZWt0a377gB0XWtY7j1nMthSVGPrXgYROnRb2inureOY9Pa27j7vFF7Cle0V_l5uIRysmvH9SHaXgS_GJxm9dxlB7vx_OPxmVdHWWFFVmx67xX6w75SvOognqF_WKO3WO_iYZspBJCiFd3dpj527xUEkNZ0mRZTkKgb9yG9n8z7cNaAxuXlfRatPWQZ2InrzgMXOcSJ38onNstlLg2xs_OaUNkUqxzh9csbzdg8bNujHJwTdjO1kCuNXSzVLZ0Y4JJ2V54YTN9UThrl0Iit7sphu-ykju1yntPe3KGTbEPDGtIe3bnz7bvm4bd963r52L2gI0OcCia-yL6wlz25ExRwwTdhlD1MgaprAA-aqpMrrIFTLIYccGOusoGxtP1L6OCrbOFbpYKNvINsdWAkjMCqEroVvoFddZA3OKhecWjAk-kGuHB3WHT56IiF7BTJJzOzT0a2xMsSDqOhGMB1jeqEXZChqMaHk5UN3gI4_7QcE5dy27rXbOu2GX2SRmMB5Ijnv-dsqfQrQ-t8wxvz7DSW2dZY-l3a2NsvozWuHuyWhn_pZhgOdVvPX4C0qDcaMeSZSLGOkWgdvs1B-wbXnhyuxod3xrTndZC_h-qIOoavLMaqeJtfiqyxuIvrtdbq-x5eQgVteAepXazdO05ouT262x7SYWrHaNtpiObqThY4lHe1rciv7mZLwgsmMgEk20IheAslEuSdQOEUKRWPDyjGG3QCTyTEHNZRhjNgYF2R5Jnzck6uImyBYTraoTQOIxYjfMWPKomOwMcgouMmKrIyEiIOooyLmsyNtGgws6gxjIgz3KW7Wp6Zoi4FSzbYaHD5xc6R5LaRYlnGOerhCEeYfbatmXsxxzy6GsxozWMvt4RBtMTEyivHhNt5DLf2rioe5RCMywGx4BTYW5S9HgNDluXuOI-WPOhcO9QUeLaWlqhAT55BOytBN2uwj9aqcwQePbhNd7Cf3aApg4uyQUbJAJBpBh2z2AV1So-teEAM1oYEu4OERJANKyTLLaKqE96iF3TxG2mVDNbIwNFIoyJayYfBl_3BjNKqiM7DAVPReiCABLyIHkL3NVCqqQIzVPmsV5mlCcng_WSokZvRlWcsjUkUnbIuukcXdX9Po844RPdsXE4n4w5W6iHj1EwNm3XUqalxcyOVAJKhqrcstJamkrV0tbFT667aS0ZQdgbT1R6wdE8Od4ZLfTP3XeP29rBYL1MtP0J311oKRglzQTbfYRKacDob0fNXULD5_E64IlgUZ26I__ptK26j7vHhFRkBpDR9ff75p6yLJ_ba6XzfNLid6goL1iy3oqZMxvkupgBw_wFrZv0PE3j8Pw_2wf7DY2_DYpb1uMD_IcL8VMig6HKfbKO4IXFdFzXZx21ECqmbh_8IOrlaf1AfNFnk5DVuOjc9tZ0fF_MH-K79fjdX5OTn97ofFN12IbPQWJFu7n8O8B-rD4r0i5wA65aM3Bcm2wg3eBGh-fhZRKHIg66J8zAdJ7ZxThIcNS6fdn-77-KoaYVCeu5CuGvw77dRZJenuGnmRWk6kQpW8z4ev3BOtlHRhdFijnlBG-Gixm08vYykX-BmIZ25CSbdfCQbnDfLRWXR1fOtJQE2H1_8r7S_oTfuF_x1tQYUtQYrmvkSfd3gzeZBcS5gMcvxPOdR1PrBsRhQq8cK-96X-CugAEOtKYZiGZ5lPoINzWOf4hjsMxt6tSEYCmdunH5MiPgo6vBL3DQd_rpZczz1JXUfOG3my1YAvMnaBAAEu_1Sf50R9OjChmCoNG7a5geFNm5T_JXgqNTNHr5Lfl6NEhz1_ZP_WGLSx37nTQ5vMM4asi3IByYfdZHgfHJMG2Eyxz1uWvKF6yYu8oYsgsnIiyQc9aWr06__32CfFZzAvuj4-gr-XwAAAP__IlFY-g">