From 5098d67d9fa9fbb5b92fc8cafed615845c3ae0ad Mon Sep 17 00:00:00 2001 From: jingyaogong Date: Sat, 4 Apr 2026 12:13:28 +0800 Subject: [PATCH] [fix] issue#114 --- model/model_vlm.py | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/model/model_vlm.py b/model/model_vlm.py index 81cd2dd..696ccd8 100644 --- a/model/model_vlm.py +++ b/model/model_vlm.py @@ -115,18 +115,11 @@ class MiniMindVLM(MiniMindForCausalLM): if hasattr(pixel_values, 'keys'): img_emb = MiniMindVLM.get_image_embeddings(pixel_values, self.vision_encoder) vision_tensors = self.vision_proj(img_emb) - else: if len(pixel_values.shape) == 6: pixel_values = pixel_values.squeeze(2) bs, num, c, im_h, im_w = pixel_values.shape - - # 每次取整个 batch 的第 i 张图，经过 vision encoder + projector 后得到 [B, target_tokens, hidden_size] - # 再统一在图片维（dim=1）上堆叠，使 vision_tensors 始终为 [B, N, target_tokens, hidden_size] - # 这样可与后续 count_vision_proj 中的 vf[b][k]、vf.size(1) 保持一致 - vision_tensors = torch.stack( - [self.vision_proj(MiniMindVLM.get_image_embeddings(pixel_values[:, i, :, :, :], self.vision_encoder)) - for i in range(num)],dim=1) + vision_tensors = torch.stack([self.vision_proj(MiniMindVLM.get_image_embeddings(pixel_values[:, i, :, :, :], self.vision_encoder)) for i in range(num)], dim=1) hidden_states = self.count_vision_proj(tokens=input_ids, h=hidden_states, vision_tensors=vision_tensors, seqlen=input_ids.shape[1]) position_embeddings = (