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Update train from QwenVL (#50)

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* update from vlm

* update

* update

* update
This commit is contained in:
Lufang Chen
2025-10-16 10:53:51 +08:00
committed by GitHub
parent 17335bcc3d
commit 35399d187a
8 changed files with 344 additions and 44 deletions
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wall_x/data/load_lerobot_dataset.py
+22 -17
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@@ -255,14 +255,6 @@ class DataCollator:
processor_path = self.config["pretrained_wallx_path"]
action_tokenizer_path = self.config["action_tokenizer_path"]
# Use cached processors if available
if processor_path not in self._processor_cache:
self._processor_cache[processor_path] = AutoProcessor.from_pretrained(
processor_path, use_fast=True
)
if self.config.get("padding_side", "left") == "left":
self._processor_cache[processor_path].tokenizer.padding_side = "left"
if (
self.use_fast_tokenizer
and action_tokenizer_path not in self._action_tokenizer_cache
@@ -273,6 +265,28 @@ class DataCollator:
)
)
# Use cached processors if available
if processor_path not in self._processor_cache:
processor = AutoProcessor.from_pretrained(processor_path, use_fast=True)
if self.config.get("padding_side", "left") == "left":
processor.tokenizer.padding_side = "left"
if self.use_fast_tokenizer and self.config.get("model_type") == "qwen2_5":
action_tokenizer = self._action_tokenizer_cache[action_tokenizer_path]
new_tokens = ["<|propri|>", "<|action|>"]
new_tokens += [
f"<|action_token_{i}|>" for i in range(action_tokenizer.vocab_size)
]
processor.tokenizer.add_tokens(new_tokens)
begin_idx_token = "<|action_token_0|>"
token_id = processor.tokenizer.convert_tokens_to_ids(begin_idx_token)
processor.tokenizer.init_kwargs["action_token_start_index"] = token_id
processor.tokenizer.init_kwargs["action_token_vocab_size"] = (
action_tokenizer.vocab_size
)
self._processor_cache[processor_path] = processor
self.processor = self._processor_cache[processor_path]
if not self.use_fast_tokenizer:
@@ -282,15 +296,6 @@ class DataCollator:
action_tokenizer_path
]
if self.use_fast_tokenizer:
self.action_mapper = {}
for i in range(self.train_action_tokenizer.vocab_size):
token = f"<|action_token_{i}|>"
token_id = self.processor.tokenizer.convert_tokens_to_ids(token)
self.action_mapper[token_id] = i
else:
self.action_mapper = None
@classmethod
def _normalize(cls, action, min_stat, delta):
"""