symbolic.c:58:3: warning:implicitlydeclaring libraryfunction 'memset' with type'void *(void *, int, unsigned ong)' [-Wimplicit-function-declaration]memset(arr,o,n); symbolic.c:58:3: note: include the header <string.h> or explicitly provide a declaration for 'memset'symbolic.c:106:5: warning: implicitly declaring libraryfunction 'memcpy' with type 'void *(void *, const void *unsigned Tong)' [-Wimplicit-function-declarationlmemcpy(arr, arr.5): symbolic.c:106:5: note: include the header <string.h> or explicitly provide a declaration for 'memcpy

这些warning的意思是在symbolic.c文件中，函数memset和memcpy被隐式声明并使用了，但没有在代码中显式声明。编译器建议你在代码中显式地包含<string.h>头文件，或者提供这些函数的声明。

你可以在代码中添加以下声明：

#include <string.h>

或者在代码中显式声明这些函数，例如：

void *memset(void *s, int c, size_t n);
void *memcpy(void *dest, const void *src, size_t n);

这样应该就可以解决这些warning了。

相关问题

(64849, 21) (64849, 1) trainX Y shape is: (64599, 48, 21) (64599, 60, 21) (64599, 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_a1.py:148 model,normalize = startTrainMult_1H(data,name,config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a38.py:570 in startTrainMult_1H model = trainModel(trainX1, trainX2 , trainY, config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a38.py:500 in trainModel model = LSTNetAttention(trainX1,trainX2,trainY,config) File D:\lstnet_keras-master\lstm\LSTNet_Interface_a38.py:443 in LSTNetAttention lstm1 = LSTM(64, return_sequences=True)(input1) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\layers\recurrent.py:541 in __call__ return super(RNN, 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:475 in __call__ previous_mask = _collect_previous_mask(inputs) File ~\anaconda4\envs\tensorflow\lib\site-packages\keras\engine\base_layer.py:1441 in _collect_previous_mask mask = node.output_masks[tensor_index] AttributeError: 'Node' object has no attribute 'output_masks'

这个错误是由于 Keras 版本的问题导致的。在旧版本的 Keras 中，LSTM 层的参数是 return_sequences 和 return_state，而在新版本的 Keras 中，LSTM 层的参数是 return_sequences、return_state 和 return_attention。你可以检查一下你使用的 Keras 版本是否与代码中使用的版本相同。如果不同，你需要修改代码以适应你的 Keras 版本。另外，你可以尝试在 LSTM 层中添加 `return_sequences=True` 参数来解决这个问题。

mysqld: error while loading shared libraries: libprotobuf-lite.so.3.19.4: cannot open shared object file: No such file or directory

This error message indicates that the MySQL server is unable to find the required shared library "libprotobuf-lite.so.3.19.4" on the system. The library may be missing or not installed in the correct location.

To resolve this issue, try the following steps:

1. Check if the library is installed on the system by running the command:

`ldconfig -p | grep libprotobuf-lite.so.3.19.4`

If the library is not found, you may need to install it using your system's package manager or download it from the internet and install it manually.

2. If the library is installed but not in the correct location, you can create a symbolic link to the correct location using the command:

`sudo ln -s /path/to/libprotobuf-lite.so.3.19.4 /usr/lib/libprotobuf-lite.so.3.19.4`

Replace "/path/to" with the actual path to the library on your system.

3. Once the library is installed or linked correctly, restart the MySQL server and check if the error has been resolved.

`sudo systemctl restart mysql`

If the issue persists or you are unsure about how to proceed, it may be best to consult a system administrator or technical support for further assistance.