IPAdapter Embeds Batch¶

Documentation¶

Class name: IPAdapterEmbedsBatch
Category: ipadapter/embeds
Output node: False

The IPAdapterEmbedsBatch node is designed to handle batch processing of image embeddings within the IPAdapter framework. It extends the capabilities of IPAdapterEmbeds by enabling the processing of multiple embeddings simultaneously, optimizing for efficiency and scalability in embedding operations.

Input types¶

Required¶

model
- unknown
- Comfy dtype: MODEL
- Python dtype: unknown
ipadapter
- unknown
- Comfy dtype: IPADAPTER
- Python dtype: unknown
pos_embed
- unknown
- Comfy dtype: EMBEDS
- Python dtype: unknown
weight
- unknown
- Comfy dtype: FLOAT
- Python dtype: unknown
weight_type
- unknown
- Comfy dtype: COMBO[STRING]
- Python dtype: unknown
start_at
- unknown
- Comfy dtype: FLOAT
- Python dtype: unknown
end_at
- unknown
- Comfy dtype: FLOAT
- Python dtype: unknown
embeds_scaling
- unknown
- Comfy dtype: COMBO[STRING]
- Python dtype: unknown

Optional¶

neg_embed
- unknown
- Comfy dtype: EMBEDS
- Python dtype: unknown
attn_mask
- unknown
- Comfy dtype: MASK
- Python dtype: unknown
clip_vision
- unknown
- Comfy dtype: CLIP_VISION
- Python dtype: unknown

Output types¶

model
- Comfy dtype: MODEL
- Represents the output model after processing the batch of image embeddings, encapsulating the enhanced or modified embeddings.
- Python dtype: torch.nn.Module

Usage tips¶

Infra type: CPU
Common nodes: unknown

Source code¶

class IPAdapterEmbedsBatch(IPAdapterEmbeds):
    def __init__(self):
        self.unfold_batch = True