[data] fix MiniCPMV plugin (#6998)

* fix template

* fix bug in messages processing

Former-commit-id: cde479e47a51beb60ab555cdee083c1cdba0ead6

src/llamafactory/data/mm_plugin.py

@@ -516,7 +516,6 @@ class MiniCPMVPlugin(BasePlugin):
         image_processor: "BaseImageProcessor" = getattr(processor, "image_processor")
         mm_inputs = {}
         audio_inputs = {}
-        audio_parts = []
         if len(images) != 0 and len(videos) != 0:
             raise ValueError("MiniCPM-V model does not support input images and videos at the same time.")
 
@@ -540,7 +539,6 @@ class MiniCPMVPlugin(BasePlugin):
                 num_video_tokens += 1
 
             while AUDIO_PLACEHOLDER in content:
-                audio_parts.append(i)
                 content = content.replace(AUDIO_PLACEHOLDER, "{{audio}}", 1)
                 num_audio_tokens += 1
 
@@ -552,12 +550,12 @@ class MiniCPMVPlugin(BasePlugin):
             mm_inputs = self._get_mm_inputs(images, [], [], processor)
 
         if num_audio_tokens > 0:
-            audio_parts_ls = [audio_parts]
-            audio_inputs = self._get_mm_inputs([], [], audios, processor, audio_parts_ls=audio_parts_ls, ret_phs=True)
+            audio_inputs = self._get_mm_inputs([], [], audios, processor, ret_phs=True)
 
         if mm_inputs:
             pattern = "(<image>./</image>)"
             image_sizes = mm_inputs["image_sizes"]
+            idx = 0
             for index, message in enumerate(messages):
                 text = message["content"]
                 image_tags = re.findall(pattern, text)
@@ -568,23 +566,26 @@ class MiniCPMVPlugin(BasePlugin):
                         final_text
                         + text_chunks[i]
                         + image_processor.get_slice_image_placeholder(
-                            image_sizes[0][i], i, max_slice_nums, use_image_id
+                            image_sizes[0][idx], idx, max_slice_nums, use_image_id
                         )
                     )
+                    idx += 1
 
                 final_text += text_chunks[-1]
                 messages[index]["content"] = final_text
 
         if audio_inputs:
             pattern = "(<audio>./</audio>)"
+            idx = 0
             for index, message in enumerate(messages):
                 text = message["content"]
                 audio_tags = re.findall(pattern, text)
                 text_chunks = text.split(pattern)
                 final_text = ""
                 for i in range(len(audio_tags)):
-                    audio_placeholder = audio_inputs["audio_phs"][0][i]
+                    audio_placeholder = audio_inputs["audio_phs"][0][idx]
                     final_text = final_text + text_chunks[i] + audio_placeholder
+                    idx += 1
 
                 final_text += text_chunks[-1]
                 messages[index]["content"] = final_text
@@ -644,22 +645,24 @@ class MiniCPMVPlugin(BasePlugin):
             mm_inputs.update(video_inputs)
 
         if len(audios) != 0:
-            audio_parts_ls = kwargs.get("audio_parts_ls", None)
             new_audios = []
             for audio in audios:
                 if not isinstance(audio, np.ndarray):
                     audio = librosa.load(audio, sr=processor.feature_extractor.sampling_rate)[0]
                 new_audios.append(audio)
 
-            audios_ls = []
-            idx = 0
-            for audio_parts in audio_parts_ls:
-                audios_ls.append(new_audios[idx : idx + len(audio_parts)])
-                idx += len(audio_parts)
+            if "valid_audio_nums_ls" in kwargs:
+                valid_audio_nums_ls = kwargs["valid_audio_nums_ls"]
+                audios_ls = []
+                idx = 0
+                for valid_audio_nums in valid_audio_nums_ls:
+                    audios_ls.append(new_audios[idx : idx + valid_audio_nums])
+                    idx += valid_audio_nums
+            else:
+                audios_ls = [new_audios]
 
             audio_features, audio_feature_lens, audio_phs = processor.audio_feature_extract(
                 audios_ls,
-                audio_parts_ls,
                 chunk_input=True,
                 sampling_rate=16000,
             )
@@ -715,7 +718,7 @@ class MiniCPMVPlugin(BasePlugin):
             # audio bound
             audio_bounds_ls = []
             spk_bounds_ls = []
-            audio_parts_ls = []
+            valid_audio_nums_ls = []
 
             for input_ids, audiolen in zip(batch_ids, audlens):
                 input_ids_ = torch.tensor(input_ids)
@@ -724,7 +727,7 @@ class MiniCPMVPlugin(BasePlugin):
                 assert len(audio_start_idx) == len(audio_end_idx)
                 audio_bounds = torch.hstack([(audio_start_idx + 1).unsqueeze(-1), audio_end_idx.unsqueeze(-1)])
                 audio_bounds_ls.append(audio_bounds)
-                audio_parts_ls.append(list(range(audiolen)))
+                valid_audio_nums_ls.append(audiolen)
 
                 spk_start_idx = torch.where(input_ids_ == processor.tokenizer.spk_start_id)[0]
                 spk_end_idx = torch.where(input_ids_ == processor.tokenizer.spk_end_id)[0]
@@ -732,7 +735,7 @@ class MiniCPMVPlugin(BasePlugin):
                 spk_bounds = torch.hstack([(spk_start_idx + 1).unsqueeze(-1), spk_end_idx.unsqueeze(-1)])
                 spk_bounds_ls.append(spk_bounds)
 
-            audio_inputs = self._get_mm_inputs([], [], audios, processor, audio_parts_ls=audio_parts_ls)
+            audio_inputs = self._get_mm_inputs([], [], audios, processor, valid_audio_nums_ls=valid_audio_nums_ls)
             mm_inputs.update(audio_inputs)
             mm_inputs.update({"audio_bounds": audio_bounds_ls, "spk_bounds": spk_bounds_ls})