ComfyUI Node: REF] Ref Attn Map Adv

REF] Ref Attn Map Adv:

The ConfigRefMapAdv node is designed to help you configure and manage attention maps for different stages of a neural network model, specifically for input, middle, and output layers. This node allows you to specify which attention layers to include in the attention map by providing a list of indices for each stage. By customizing these attention maps, you can fine-tune the model's focus on different parts of the input data, potentially improving the model's performance and output quality. This node is particularly useful for advanced users who want to have granular control over the attention mechanisms in their models.

REF] Ref Attn Map Adv Input Parameters:

input_attns

This parameter allows you to specify the indices of the input attention layers that you want to include in the attention map. You can provide a comma-separated list of indices, such as "0,1,2,3,4,5". Each index corresponds to a specific input attention layer. The default value is "0,1,2,3,4,5". This parameter helps in focusing the model's attention on specific input layers, which can be crucial for tasks requiring detailed input analysis.

middle_attns

This parameter allows you to specify the indices of the middle attention layers that you want to include in the attention map. Similar to the input_attns parameter, you can provide a comma-separated list of indices. The default value is "0". This parameter is useful for controlling the attention in the middle layers of the model, which can be important for capturing intermediate features and representations.

output_attns

This parameter allows you to specify the indices of the output attention layers that you want to include in the attention map. You can provide a comma-separated list of indices, such as "0,1,2,3,4,5,6,7,8". Each index corresponds to a specific output attention layer. The default value is "0,1,2,3,4,5,6,7,8". This parameter helps in focusing the model's attention on specific output layers, which can be crucial for tasks requiring detailed output analysis.

REF] Ref Attn Map Adv Output Parameters:

ATTN_MAP

The output of this node is an attention map, represented as a set of tuples. Each tuple consists of a stage (input, middle, or output) and an index, indicating which attention layers are included in the map. This attention map can be used to guide the model's focus during processing, potentially improving the quality and relevance of the output.

REF] Ref Attn Map Adv Usage Tips:

• Ensure that the indices provided in the input_attns, middle_attns, and output_attns parameters are valid and correspond to the actual layers in your model.
• Experiment with different combinations of attention layers to find the optimal configuration for your specific task.
• Use this node in conjunction with other nodes that manage or utilize attention mechanisms to achieve more refined control over your model's behavior.

REF] Ref Attn Map Adv Common Errors and Solutions:

Invalid index in input_attns, middle_attns, or output_attns

• Explanation: One or more of the indices provided do not correspond to valid attention layers in the model.
• Solution: Verify the indices and ensure they match the actual layers in your model. Adjust the indices as needed.

Empty attention map

• Explanation: No valid indices were provided, resulting in an empty attention map.
• Solution: Ensure that you provide at least one valid index in the input_attns, middle_attns, or output_attns parameters.

TypeError: 'NoneType' object is not iterable

• Explanation: One of the parameters was set to None instead of a string.
• Solution: Ensure that all parameters are provided as strings, even if they are empty. For example, use an empty string "" instead of None.