From 1b6cd282f019fa8b49a8a34b4ae1b87f0ab4f0c2 Mon Sep 17 00:00:00 2001
From: Tai An <antai12232931@outlook.com>
Date: Mon, 14 Sep 2026 06:48:51 -0700
Subject: [PATCH] fix(qwen-image): drop the shadowed dead
 _get_qwen_prompt_embeds duplicate (#7461)

Signed-off-by: Anai-Guo <antai12232931@outlook.com>
---
 .../qwen_image/pipeline_qwen_image_edit.py    | 45 -------------------
 1 file changed, 45 deletions(-)

diff --git a/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image_edit.py b/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image_edit.py
index 34e5733fd..a9b7ef95a 100644
--- a/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image_edit.py
+++ b/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image_edit.py
@@ -374,51 +374,6 @@ class QwenImageEditPipeline(
 
         return split_result
 
-    def _get_qwen_prompt_embeds(
-        self,
-        prompt: str | list[str] = None,
-        image: torch.Tensor | None = None,
-        dtype: torch.dtype | None = None,
-    ):
-        dtype = dtype or self.text_encoder.dtype
-
-        prompt = [prompt] if isinstance(prompt, str) else prompt
-
-        template = self.prompt_template_encode
-        drop_idx = self.prompt_template_encode_start_idx
-        txt = [template.format(e) for e in prompt]
-
-        model_inputs = self.processor(
-            text=txt,
-            images=image,
-            padding=True,
-            return_tensors="pt",
-        ).to(self.device)
-
-        outputs = self.text_encoder(
-            input_ids=model_inputs.input_ids,
-            attention_mask=model_inputs.attention_mask,
-            pixel_values=model_inputs.pixel_values,
-            image_grid_thw=model_inputs.image_grid_thw,
-            output_hidden_states=True,
-        )
-
-        hidden_states = outputs.hidden_states[-1]
-        split_hidden_states = self._extract_masked_hidden(hidden_states, model_inputs.attention_mask)
-        split_hidden_states = [e[drop_idx:] for e in split_hidden_states]
-        attn_mask_list = [torch.ones(e.size(0), dtype=torch.long, device=e.device) for e in split_hidden_states]
-        max_seq_len = max([e.size(0) for e in split_hidden_states])
-        prompt_embeds = torch.stack(
-            [torch.cat([u, u.new_zeros(max_seq_len - u.size(0), u.size(1))]) for u in split_hidden_states]
-        )
-        encoder_attention_mask = torch.stack(
-            [torch.cat([u, u.new_zeros(max_seq_len - u.size(0))]) for u in attn_mask_list]
-        )
-
-        prompt_embeds = prompt_embeds.to(dtype=dtype, device=self.device)
-
-        return prompt_embeds, encoder_attention_mask
-
     def _get_qwen_prompt_embeds(
         self,
         prompt: str | list[str] = None,