trainX Y shape is: (4755, 48, 23) (4755, 60, 23) (4755, 5, 1) Hx= 1 Traceback (most recent call last): File ~\anaconda4\envs\tensorflow\lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec exec(code, globals, locals) File d:\lstnet_keras-master\train_batch_a391.py:172 model,normalize = startTrainMult_1H(df,name,config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a391.py:400 in startTrainMult_1H model = trainModel(trainX1, trainX2 , trainY, config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a391.py:323 in trainModel model = LSTNetAttention(trainX1,trainX2,trainY,config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a391.py:297 in LSTNetAttention res = add([concat,z]) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\layers\merge.py:555 in add return Add(**kwargs)(inputs) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py:75 in symbolic_fn_wrapper return func(*args, **kwargs) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\engine\base_layer.py:463 in __call__ self.build(unpack_singleton(input_shapes)) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\layers\merge.py:90 in build output_shape = self._compute_elemwise_op_output_shape(output_shape, File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\layers\merge.py:59 in _compute_elemwise_op_output_shape raise ValueError('Operands could not be broadcast ' ValueError: Operands could not be broadcast together with shapes (23, 32) (5,)
时间: 2023-09-06 08:11:49 浏览: 41
这个错误是由于在使用 Keras 进行模型训练时,两个张量的形状无法进行广播运算所导致的。具体来说,在您的代码中,您使用了 Keras 的 Merge 层中的 Add 层,将两个张量进行相加。但是,这两个张量的形状不匹配,无法进行广播运算,所以会导致这个错误。
您需要检查一下您的代码,确定这两个张量的形状是否正确,并且可以进行相加操作。如果您没有修改过这个代码,可能是数据集的问题,您需要检查一下数据集的形状是否正确。
相关问题
trainX Y shape is: (4755, 48, 23) (4755, 60, 23) (4755, 5, 1) Hx= 1 Traceback (most recent call last): File ~\anaconda4\envs\tensorflow\lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec exec(code, globals, locals) File d:\lstnet_keras-master\train_batch_a391.py:172 model,normalize = startTrainMult_1H(df,name,config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a391.py:417 in startTrainMult_1H model = trainModel(trainX1, trainX2 , trainY, config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a391.py:340 in trainModel model = LSTNetAttention(trainX1,trainX2,trainY,config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a391.py:282 in LSTNetAttention bidirectional = Bidirectional(LSTM(units=32, return_sequences=True))(embedding) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\layers\wrappers.py:437 in __call__ return super(Bidirectional, self).__call__(inputs, **kwargs) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py:75 in symbolic_fn_wrapper return func(*args, **kwargs) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\engine\base_layer.py:446 in __call__ self.assert_input_compatibility(inputs) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\engine\base_layer.py:338 in assert_input_compatibility raise ValueError('Input ' + str(input_index) + ValueError: Input 0 is incompatible with layer bidirectional_1: expected ndim=3, found ndim=4
根据你提供的信息,这个错误是在使用 Keras 框架中进行训练时出现的。错误提示中指出了问题的源头是在 Bidirectional 层的第一个输入,它期望一个三维张量作为输入,但实际上输入的是一个四维张量。这可能是因为你的输入数据的维度不正确导致的。
你可以检查一下你的输入数据的维度是否正确。确保你的输入数据的维度是 (batch_size, time_steps, features),其中 batch_size 表示每个 batch 中的样本数,time_steps 表示序列的时间步数,features 表示每个时间步中的特征数。如果你的输入数据维度正确,你可以尝试将它们转换为正确的维度,例如使用 reshape() 函数,以便它们可以被正确地输入到模型中进行训练。
Exception in thread Thread-1: Traceback (most recent call last):
引用: Exception in thread Thread-1: Traceback most recent call last.
引用: Exception in thread Thread-1: Traceback (most recent call last): File “D:\Python37\lib\threading.py”, line 917, in _bootstrap_inner self.run() File “D:\Python37\lib\threading.py”, line 1158, in run self.function(*self.args, **self.kwargs) TypeError: ‘NoneType’ object is not callable.
引用: t=Timer(timer_interval,clearTwoBlock())#定时函数
当你得到异常 "Exception in thread Thread-1: Traceback (most recent call last)" 时,这表示在线程 Thread-1 中发生了一个异常,最近的调用发生了错误。
在引用中,异常的具体信息是:"File “D:\Python37\lib\threading.py”, line 917, in _bootstrap_inner self.run() File “D:\Python37\lib\threading.py”, line 1158, in run self.function(*self.args, **self.kwargs) TypeError: ‘NoneType’ object is not callable"。这个错误的意思是在线程运行的过程中,执行的函数为 NoneType 对象,而 NoneType 对象是不可调用的,因此会引发 TypeError。
在引用中,你可能在创建 Timer 对象时遇到了问题。根据提供的代码,你使用了 clearTwoBlock() 作为定时函数,但是你应该只传递函数名,而不是通过函数调用。正确的写法应该是:t=Timer(timer_interval, clearTwoBlock)。