Hunyuan dit can now accept longer prompts.

comfy/ldm/hydit/models.py

@@ -319,13 +319,15 @@ class HunYuanDiT(nn.Module):
         text_states_mask = text_embedding_mask.bool()           # 2,77
         text_states_t5_mask = text_embedding_mask_t5.bool()     # 2,256
         b_t5, l_t5, c_t5 = text_states_t5.shape
-        text_states_t5 = self.mlp_t5(text_states_t5.view(-1, c_t5))
-        text_states = torch.cat([text_states, text_states_t5.view(b_t5, l_t5, -1)], dim=1)  # 2,205，1024
+        text_states_t5 = self.mlp_t5(text_states_t5.view(-1, c_t5)).view(b_t5, l_t5, -1)
 
-        clip_t5_mask = torch.cat([text_states_mask, text_states_t5_mask], dim=-1)
+        padding = self.text_embedding_padding.to(text_states)
 
-        clip_t5_mask = clip_t5_mask
-        text_states = torch.where(clip_t5_mask.unsqueeze(2), text_states, self.text_embedding_padding.to(text_states))
+        text_states[:,-self.text_len:] = torch.where(text_states_mask[:,-self.text_len:].unsqueeze(2), text_states[:,-self.text_len:], padding[:self.text_len])
+        text_states_t5[:,-self.text_len_t5:] = torch.where(text_states_t5_mask[:,-self.text_len_t5:].unsqueeze(2), text_states_t5[:,-self.text_len_t5:], padding[self.text_len:])
+
+        text_states = torch.cat([text_states, text_states_t5], dim=1)  # 2,205，1024
+        # clip_t5_mask = torch.cat([text_states_mask, text_states_t5_mask], dim=-1)
 
         _, _, oh, ow = x.shape
         th, tw = (oh + (self.patch_size // 2)) // self.patch_size, (ow + (self.patch_size // 2)) // self.patch_size