How can I avoid exploding gradients in large-scale generative models

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With the help of code and explanation, can you tell me how I can avoid exploding gradients in large-scale generative models?
Jan 8 in Generative AI by Ashutosh
• 15,240 points
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1 answer to this question.

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In order to avoid exploding gradients in large-scale generative models, especially for large models. You can refer to the code snippet below.

Here is the code showing how:

In the above code, we are using the following key steps:

  • Gradient Clipping: clip_grad_norm_ prevents gradients from exploding.
  • Spectral Normalization: Regularizes the discriminator’s weights.
  • Learning Rate Scheduling: Dynamically adjusts learning rates.
  • Proper Optimizers: Adam optimizer with tuned betas.
  • Stable Initialization: Default PyTorch initialization is robust for GANs.

Hence, these strategies collectively ensure stable training for large-scale generative models.

answered Jan 9 by techboy support

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