limit of GoogLeNet

The limit of GoogLeNet, also known as Inception-v1, is its depth and complexity. GoogLeNet is a deep neural network architecture with 22 layers, including 9 inception modules. The complexity of the network makes it difficult to train and requires a significant amount of computational resources. Additionally, the large number of parameters in the network can lead to overfitting, which can limit the network's generalization ability. However, GoogLeNet has been highly successful in image classification tasks and has inspired the development of other deep neural network architectures.

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Out of memory. GC overhead limit exceeded

This error message typically indicates that the Java virtual machine (JVM) has run out of memory and is unable to allocate any more memory to the application. The "GC overhead limit exceeded" part of the message means that the garbage collector (GC) is taking up too much time trying to free up memory, but is unable to do so because there is not enough memory available.

To fix this issue, you can try increasing the amount of memory allocated to the JVM by setting the "Xmx" parameter in the command line or configuration file. For example, you can set -Xmx1024m to allocate 1GB of memory.

You can also try optimizing your code to use less memory, such as avoiding creating unnecessary objects or using more efficient data structures.

If the issue persists, it may be a sign of a memory leak or other underlying issue in the application that needs to be addressed.

outofmemory error GC overhead limit exceeded

The "OutOfMemory" error occurs when the Java Virtual Machine (JVM) runs out of memory and cannot allocate more memory to the application. The "GC overhead limit exceeded" error occurs when the garbage collector (GC) spends too much time trying to reclaim memory and fails to free up enough memory. This error is usually caused by the application generating too much garbage, which results in the GC running frequently and taking up too much CPU time.

To resolve this error, you can increase the memory available to the JVM by setting the -Xmx option to a larger value. You can also optimize your application to generate less garbage and reduce the frequency of garbage collection. This can be done by using efficient algorithms, avoiding unnecessary object creation, and using cache mechanisms to reuse objects. Additionally, you can tune the GC settings to make it more efficient by adjusting the GC threshold and other parameters.