rm some

src/llmtuner/train/sftmm/collator.py

@@ -1,42 +0,0 @@
-from dataclasses import dataclass
-from transformers import AutoProcessor
-
-
-@dataclass
-class DataCollatorForVis2Seq:
-    processor: AutoProcessor
-
-    def __call__(self, examples):
-        texts = []
-        images = []
-        for example in examples:
-            if len(example["images"]) > 1:
-                raise ValueError("This collator only supports one image per example")
-            messages = example["messages"]
-            text = self.processor.tokenizer.apply_chat_template(
-                messages, tokenize=False, add_generation_prompt=False
-            )
-            texts.append(text)
-            images.append(example["images"][0])
-
-        batch = self.processor(
-            text=texts, images=images, return_tensors="pt", padding=True
-        )
-
-        labels = batch["input_ids"].clone()
-        if self.processor.tokenizer.pad_token_id is not None:
-            labels[labels == self.processor.tokenizer.pad_token_id] = -100
-        batch["labels"] = labels
-
-        return batch
-
-
-@dataclass
-class DataCollatorForMLLM:
-    processor: AutoProcessor
-
-    def __call__(self, examples):
-        print(examples[0].keys())
-        print(examples[0]["input_ids"])
-        batch = {}
-        return batch