启动内核时发生错误，但指定Keras代码可正常运行的技术咨询

Hey there! It's a bit odd that you're hitting a kernel launch error but your code runs smoothly once you get past that hurdle. Let's first tidy up your code snippet for better readability, then dive into possible fixes for that kernel startup issue.

Your Functional Code #

from keras.datasets import mnist

def plot_history(net_history):
    history = net_history.history
    import matplotlib.pyplot as plt
    losses = history['loss']
    val_losses = history['val_loss']
    accuracies = history['acc']
    val_accuracies = history['val_acc']
    
    plt.xlabel('Epochs')
    plt.ylabel('Loss')
    plt.plot(losses)
    plt.plot(val_losses)
    plt.legend(['loss', 'val_loss'])
    
    plt.figure()
    plt.xlabel('Epochs')
    plt.ylabel('Accuracy')
    plt.plot(accuracies)
    plt.plot(val_accuracies)  # Note: Your original code was truncated here, this is the likely completion

Troubleshooting the Kernel Launch Error #

Since your code works once the kernel is running, the startup issue is almost certainly tied to your environment setup rather than the code itself. Here are some actionable steps to try:

• Verify compatibility between your Python version and the versions of Keras/TensorFlow/matplotlib you're using. Run pip list in your terminal to check installed package versions.
• Fully restart your kernel (most IDEs like Jupyter have a dedicated "Restart Kernel" option) to clear any cached state that might be causing the error.
• If you're using a virtual environment, make sure it's activated properly before launching your notebook or IDE.
• Try upgrading or reinstalling core dependencies to rule out corrupted installations:

  pip install --upgrade keras tensorflow matplotlib
  

内容的提问来源于stack exchange，提问作者user3675896