state.stack[-1][1],self.stack = [] # the stack used for function calling, starting with [deffun,0].

时间: 2023-12-04 13:04:04 浏览: 46
这段代码应该是指一个解释器或编译器中的栈(stack)的实现。 stack是一种后进先出(Last In First Out,简称LIFO)的数据结构,它在函数调用时经常被使用。在这个例子中,代码中的self.stack代表一个栈对象,它被用于函数调用。 state.stack[-1][1]表示栈的最后一个元素的第二个值。这意味着在栈的最后一个元素中,它的第二个值是被调用函数的参数数量。例如,当调用一个函数时,第一个元素将是“deffun”,第二个元素将是参数数量。 而self.stack = [] 则是将栈清空,以便开始新的函数调用。
相关问题

lodash.clonedeep Maximum call stack size exceeded

The error message "Maximum call stack size exceeded" typically occurs when there is an infinite recursion or a very deep recursive function call. It means that the function is calling itself too many times, exhausting the call stack and causing the error. In the case of `lodash.clonedeep`, it is a recursive function that deep clones an object. This error can occur if you have a circular reference in your object, meaning an object that references itself at some point. To fix this issue, you can try to identify and resolve any circular references in your object. Alternatively, you can use a different approach to cloning objects, such as using `JSON.parse(JSON.stringify(obj))` or other libraries like `immer` or `rfdc` that handle cloning without the risk of exceeding the call stack size.

Unstable_TrapFocus.js:84 Uncaught RangeError: Maximum call stack size exceeded.

This error occurs when a function calls itself repeatedly until the call stack reaches its maximum limit. The most common cause of this error is a recursive function that doesn't have a proper exit condition, causing it to call itself indefinitely. In the case of the Unstable_TrapFocus.js script, the error is likely caused by a recursive function that's being called repeatedly, causing the call stack to overflow. To fix the issue, you'll need to identify the recursive function and add an exit condition that prevents it from calling itself indefinitely. One way to do this is to use a debugger to step through the code and identify the function that's causing the error. Once you've identified the function, you can add a conditional statement that checks if the exit condition has been met before calling the function again. For example, if the function is supposed to iterate over an array and perform some action on each item, you can add a check that stops the iteration once the end of the array is reached: ``` function myRecursiveFunction(array, index) { if (index >= array.length) { return; // exit condition } // perform action on array[index] myRecursiveFunction(array, index + 1); // call function again with incremented index } ``` By adding an exit condition to your recursive function, you can prevent it from calling itself indefinitely and avoid the "Maximum call stack size exceeded" error.

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Create a model def create_LSTM_model(X_train,n_steps,n_length, n_features): # instantiate the model model = Sequential() model.add(Input(shape=(X_train.shape[1], X_train.shape[2]))) model.add(Reshape((n_steps, 1, n_length, n_features))) model.add(ConvLSTM2D(filters=64, kernel_size=(1,3), activation='relu', input_shape=(n_steps, 1, n_length, n_features))) model.add(Flatten()) # cnn1d Layers # 添加lstm层 model.add(LSTM(64, activation = 'relu', return_sequences=True)) model.add(Dropout(0.5)) #添加注意力层 model.add(LSTM(64, activation = 'relu', return_sequences=False)) # 添加dropout model.add(Dropout(0.5)) model.add(Dense(128)) # 输出层 model.add(Dense(1, name='Output')) # 编译模型 model.compile(optimizer='adam', loss='mse', metrics=['mae']) return model # lstm network model = create_LSTM_model(X_train,n_steps,n_length, n_features) # summary print(model.summary())修改该代码,解决ValueError Traceback (most recent call last) <ipython-input-56-6c1ed99fa3ed> in <module> 53 # lstm network 54 ---> 55 model = create_LSTM_model(X_train,n_steps,n_length, n_features) 56 # summary 57 print(model.summary()) <ipython-input-56-6c1ed99fa3ed> in create_LSTM_model(X_train, n_steps, n_length, n_features) 17 model = Sequential() 18 model.add(Input(shape=(X_train.shape[1], X_train.shape[2]))) ---> 19 model.add(Reshape((n_steps, 1, n_length, n_features))) 20 21 ~\anaconda3\lib\site-packages\tensorflow\python\trackable\base.py in _method_wrapper(self, *args, **kwargs) 203 self._self_setattr_tracking = False # pylint: disable=protected-access 204 try: --> 205 result = method(self, *args, **kwargs) 206 finally: 207 self._self_setattr_tracking = previous_value # pylint: disable=protected-access ~\anaconda3\lib\site-packages\keras\utils\traceback_utils.py in error_handler(*args, **kwargs) 68 # To get the full stack trace, call: 69 # tf.debugging.disable_traceback_filtering() ---> 70 raise e.with_traceback(filtered_tb) from None 71 finally: 72 del filtered_tb ~\anaconda3\lib\site-packages\keras\layers\reshaping\reshape.py in _fix_unknown_dimension(self, input_shape, output_shape) 116 output_shape[unknown] = original // known 117 elif original != known: --> 118 raise ValueError(msg) 119 return output_shape 120 ValueError: Exception encountered when calling layer "reshape_5" (type Reshape). total size of new array must be unchanged, input_shape = [10, 1], output_shape = [10, 1, 1, 5] Call arguments received by layer "reshape_5" (type Reshape): • inputs=tf.Tensor(shape=(None, 10, 1), dtype=float32)问题

帮我用中文注释一下代码:// ThreadTester.java // Multiple threads printing at different intervals. public class ThreadTester { public static void main( String [] args ) { // create and name each thread PrintThread thread1 = new PrintThread( "thread1" ); PrintThread thread2 = new PrintThread( "thread2" ); PrintThread thread3 = new PrintThread( "thread3" ); System.err.println( "主线程将要启动三个线程" ); thread1.start(); // start thread1 and place it in ready state thread2.start(); // start thread2 and place it in ready state thread3.start(); // start thread3 and place it in ready state System.err.println( "三个线程启动完成, 主线程运行结束\n" ); } // end main } // end class ThreadTester // class PrintThread controls thread execution class PrintThread extends Thread { private int sleepTime; // assign name to thread by calling superclass constructor public PrintThread( String name ) { super( name ); // pick random sleep time between 0 and 5 seconds sleepTime = ( int ) ( Math.random() * 5001 ); } // method run is the code to be executed by new thread public void run() { // put thread to sleep for sleepTime amount of time try { System.err.println( getName() + " 进入睡眠状态,睡眠时间是: " + sleepTime ); Thread.sleep( sleepTime ); } // if thread interrupted during sleep, print stack trace catch ( InterruptedException exception ) { } // print thread name System.err.println( getName() + " 睡眠醒来" ); } // end method run } // end class PrintThread

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