안녕하세요! 항상 잘 듣고 있습니다. RNN 관련 영화평 분류 강의에서 코드 에러가 발생해 질문하게 되었습니다. 문제가 된 코드는 아래와 같습니다. 분명 강의에서 알려 주신 대로 입력했는데 RUN해보니 두 번째 코드와 같은 에러가 뜨네요... 구글링해봐도 해결 방법을 찾을 수가 없어 글을 올립니다. 감사합니다! history = model.fit(train_dataset, epochs = 10, validation_data = test_dataset, validation_steps=30) Epoch 1/10 WARNING:tensorflow:Model was constructed with shape (None, None) for input KerasTensor(type_spec=TensorSpec(shape=(None, None), dtype=tf.float32, name='embedding_1_input'), name='embedding_1_input', description="created by layer 'embedding_1_input'"), but it was called on an input with incompatible shape (None, None, None, None, None). WARNING:tensorflow:Model was constructed with shape (None, None) for input KerasTensor(type_spec=TensorSpec(shape=(None, None), dtype=tf.float32, name='embedding_1_input'), name='embedding_1_input', description="created by layer 'embedding_1_input'"), but it was called on an input with incompatible shape (None, None, None, None, None). --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-40-79f235ece0ed> in <module> ----> 1 history = model.fit(train_dataset, epochs = 10, 2 validation_data = test_dataset, 3 validation_steps=30) ~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing) 1098 _r=1): 1099 callbacks.on_train_batch_begin(step) -> 1100 tmp_logs = self.train_function(iterator) 1101 if data_handler.should_sync: 1102 context.async_wait() ~\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py in __call__(self, *args, **kwds) 826 tracing_count = self.experimental_get_tracing_count() 827 with trace.Trace(self._name) as tm: --> 828 result = self._call(*args, **kwds) 829 compiler = "xla" if self._experimental_compile else "nonXla" 830 new_tracing_count = self.experimental_get_tracing_count() ~\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py in _call(self, *args, **kwds) 869 # This is the first call of __call__, so we have to initialize. 870 initializers = [] --> 871 self._initialize(args, kwds, add_initializers_to=initializers) 872 finally: 873 # At this point we know that the initialization is complete (or less ~\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py in _initialize(self, args, kwds, add_initializers_to) 723 self._graph_deleter = FunctionDeleter(self._lifted_initializer_graph) 724 self._concrete_stateful_fn = ( --> 725 self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access 726 *args, **kwds)) 727 ~\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs) 2967 args, kwargs = None, None 2968 with self._lock: -> 2969 graph_function, _ = self._maybe_define_function(args, kwargs) 2970 return graph_function 2971 ~\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _maybe_define_function(self, args, kwargs) 3359 3360 self._function_cache.missed.add(call_context_key) -> 3361 graph_function = self._create_graph_function(args, kwargs) 3362 self._function_cache.primary[cache_key] = graph_function 3363 ~\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes) 3194 arg_names = base_arg_names + missing_arg_names 3195 graph_function = ConcreteFunction( -> 3196 func_graph_module.func_graph_from_py_func( 3197 self._name, 3198 self._python_function, ~\anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes) 988 _, original_func = tf_decorator.unwrap(python_func) 989 --> 990 func_outputs = python_func(*func_args, **func_kwargs) 991 992 # invariant: `func_outputs` contains only Tensors, CompositeTensors, ~\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py in wrapped_fn(*args, **kwds) 632 xla_context.Exit() 633 else: --> 634 out = weak_wrapped_fn().__wrapped__(*args, **kwds) 635 return out 636 ~\anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py in wrapper(*args, **kwargs) 975 except Exception as e: # pylint:disable=broad-except 976 if hasattr(e, "ag_error_metadata"): --> 977 raise e.ag_error_metadata.to_exception(e) 978 else: 979 raise ValueError: in user code: C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:805 train_function * return step_function(self, iterator) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:795 step_function ** outputs = model.distribute_strategy.run(run_step, args=(data,)) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1259 run return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2730 call_for_each_replica return self._call_for_each_replica(fn, args, kwargs) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:3417 _call_for_each_replica return fn(*args, **kwargs) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:788 run_step ** outputs = model.train_step(data) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:754 train_step y_pred = self(x, training=True) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:1012 __call__ outputs = call_fn(inputs, *args, **kwargs) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\sequential.py:375 call return super(Sequential, self).call(inputs, training=training, mask=mask) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\functional.py:424 call return self._run_internal_graph( C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\functional.py:560 _run_internal_graph outputs = node.layer(*args, **kwargs) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\layers\wrappers.py:539 __call__ return super(Bidirectional, self).__call__(inputs, **kwargs) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:998 __call__ input_spec.assert_input_compatibility(self.input_spec, inputs, self.name) C:\Users\User\anaconda3\lib\site-packages\tensorflow\python\keras\engine\input_spec.py:219 assert_input_compatibility raise ValueError('Input ' + str(input_index) + ' of layer ' + ValueError: Input 0 of layer bidirectional_1 is incompatible with the layer: expected ndim=3, found ndim=6. Full shape received: (None, None, None, None, None, 64)

hhtml과 css 첨부해서 적습니다 <!DOCTYPE html>     <head>         <meta charset="UTP-8">         <meta name="viewport" content="width=device-width, initial-scale=1.0">         <title>StarUp Mate : App Offical Landing</title>         <link rel="icon" href="images/logo-favicon.png">         <!-- jQuery CDN-->         <script src="https://code.jquery.com/jquery-3.5.1.min.js"></script>         <!--Slick Slider-->         <link rel="stylesheet" href="../js/slick/slick-theme.css">         <link rel="stylesheet" href="../js/slick/slick.css">         <script src="../js/slick/slick.min.js"></script>         <!--Custom CSS & JS-->         <link rel="stylesheet" href="css/style.css">         <link rel="stylesheet" href="css/responsive.css">         <script src="script/custom.js"></script>     </head>     <body>         <!--Header-->        <header>         <div class="header-inner">             <div class="logo">                 <a href="#"><img src="images/logo.png" alt=""></a>                 <div class="gnb">                     <a href="#none">CEO 인사말</a>                     <a href="#none">서비스 특징</a>                     <a href="#none"> 자주 묻는 질문들</a>                     <a href="#none">경영비전</a>                     <a href="#none"> 사용자 리뷰</a>                     <a href="#none"> 앱 사용자 가이드</a>                     <a href="#none">최신소식</a>                 </div>             </div>         </div>        </header>        <!--welcome-->        <section class="welcome">         <div class="slideshow">             <img src="images/slide-welcome-01.png">             <img src="images/slide-welcome-02.png">             <img src="images/slide-welcome-03.png">         </div>         <div class="welcome-heading">           <span>창의적인 아이디어를 만드는 가장 빠른 방법</span>           <h1>             An idea solution of startup for your           </h1>             <em>                  Business strategy                 Organization Management                 Business Innovation             </em>             <p>                 스타트업 메이트 앱이 여러분의 최상의 스타트업 구축을                 위해 창의적인 아이디어를 제공하는 데 최선을 다하겠습니다.             </p>         </div>        </section>        <!--ceo-access-->        <section class="ceo-access">         <div class="ceo-inner">             <div class="ceo-inner">                 <div class="ceo-content">                     <div class="ceo-left">                         <img src="images/quotation-mark.svg" alt="">                         <h3>3 Pre-made Solutions for your Startup Business</h3>                         <p>창의적인 아이디어를 가장 빠르게 창출할 수 있는 최고의 앱 솔루션을 제공합니다.                              여러분의 스타트업을 더욱 성장시키기 위해 온 힘을 다할 것이며                             STARTUP MATE 라는 이름답게 항상 동반자가 되겠습니다. 감사합니다.</p>                         <span>앤드류 - 스타트업 메이트 대표이사</span>                     </div>                     <div class="ceo-right">                         <div class="ceo-msg">                             <h3>Application Downloads<big>30,000+</big></h3>                             <p>스타트업메이트는 앱 다운로드 30,000명 이상의 앱 사용자의 충분한 피드백을 통해 검증된 서비스를 제공합니다.</p>                         </div>                         <div class="ceo-photo">                             <img src="images/icon-face-ceo.jpg" alt="">                         </div>                     </div>                 </div>             </div>          </div>          <div class="access-inner">             <div class="access-content">                 <div class="access-left">                     <h2>언제나 어디서나 즐겁고 편리한 액세스 스타트업 CEO들의 커뮤니티</h2>                         <p>언제나 어디서나. 즐겁고 편리한 액세스가 가능합니다.                            회원 가입은 쉽고 간단합니다.                            무료 회원 가입 후 로그인하시면 업데이트 된 스타트업 메이트의 서비스를 받으실 수 있습니다.</p>                         <div class="btn-download">                             <a href=""><img src="images/btn-appstore.png" alt=""></a>                             <a href=""><img src="images/btn-playstore.png" alt=""></a>                         </div>                                     </div>             </div>             <div class="access-right">                 <img src="images/access-mockup.png" alt="">             </div>          </div>                 </section> css /* Fontawesome 4.7 */ @import url('https://stackpath.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css'); /* XEION CDN */ @import url('http://cdn.jsdelivr.net/npm/xeicon@2.3.3/xeicon.min.css'); /* Web Fonts - Source Sans Pro */ @import url('https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@200;300;400;600;700;900&display=swap'); /* font-family: 'Source Sans Pro', sans-serif; */ /* Web Fonts - NoonNoo */ @font-face {   font-family: 'NEXON Lv2 Gothic';   src: url('https://cdn.jsdelivr.net/gh/projectnoonnu/noonfonts_20-04@2.1/NEXON Lv2 Gothic.woff') format('woff');   font-weight: normal;   font-style: normal; } /* Reset CSS */ * {   box-sizing: border-box; } a {   text-decoration: none;   color: #222; } button, input {   outline: none; } h1,h2,h3,h4,h5,h6 {   margin-top: 0;   font-weight: normal;   line-height: 1.5em; } /* Default CSS */ body {   font-family: 'NEXON Lv2 Gothic', sans-serif;   font-size: 18px;   line-height: 1.7em;   margin: 0;   background-color: #fff;   color: #222; } /* header */    .header {}    .header-inner{     border: 1px solid #000;     width: 1300px;     margin: auto;     overflow: hidden;     padding-top: 30px;     padding-bottom: 15px;    }    .logo {     float: left;    }    .logo img{      margin-top:-7px;     }    .gnb {     float: right;     }     .gnb a{       margin: 10px;       font-size: 16px;       }   

3D 돌출 및 베벨 효과를 사용하려고하는데 RAM이 충분하지 않다는 메시지가 계속 표시됩니다 사용할 수있는 메모리 (RAM)가 부족하여 작업을 완료할 수없습니다라고 떠요ㅠㅠ

scanf_s 가 제 환경에서는 계속 오류가 나는데 구글에 쳐서 해결하려 해봐도 안되더라고요 어떻게 다른 방법이 있나요?

build.gradle에 org.javassist를 추가해봤는데 서버 실행이 되지 않습니다. 꼭 알려주세요.