vllm - 💡(How to fix) Fix [Feature]: FA4 Attention Sinks [1 participants]

Fix Plan

To add attention sink support in FA4 for running GPT-OSS-120b efficiently on the blackwell architecture, we need to implement the following steps:

• Modify the FA4 configuration to include attention sink support
• Update the model architecture to utilize the attention sink

Code Changes

Here's an example code snippet in Python to demonstrate the changes:

# Import necessary libraries
import torch
import torch.nn as nn

# Define the attention sink module
class AttentionSink(nn.Module):
    def __init__(self):
        super(AttentionSink, self).__init__()
        self.attention = nn.MultiHeadAttention()

    def forward(self, x):
        return self.attention(x, x)

# Update the FA4 model to include attention sink support
class FA4Model(nn.Module):
    def __init__(self):
        super(FA4Model, self).__init__()
        self.attention_sink = AttentionSink()

    def forward(self, x):
        x = self.attention_sink(x)
        # Rest of the model architecture remains the same
        return x

Configuration Changes

Update the FA4 configuration file to include the attention sink support:

model:
  architecture: FA4
  attention_sink: true

Verification

To verify that the fix worked, run the GPT-OSS-120b model on the blackwell architecture and check for improved performance.

Extra Tips

• Ensure that the attention sink module is properly integrated with the rest of the model architecture.
• Monitor the model's performance and adjust the attention sink configuration as needed.