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[deps] update to transformers 4.52 (#8125)

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hoshi-hiyouga
2025-05-21 05:16:18 +08:00
committed by GitHub
parent 56926d76f9
commit 9ae17cd173
28 changed files with 365 additions and 109 deletions
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32
tests/data/test_template.py
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@@ -127,20 +127,21 @@ def test_encode_multiturn(use_fast: bool):
@pytest.mark.parametrize("use_fast", [True, False])
@pytest.mark.parametrize("cot_messages", [True, False])
@pytest.mark.parametrize("enable_thinking", [True, False])
@pytest.mark.parametrize("enable_thinking", [True, False, None])
def test_reasoning_encode_oneturn(use_fast: bool, cot_messages: bool, enable_thinking: bool):
messages = MESSAGES_WITH_THOUGHT if cot_messages else MESSAGES
input_messages = MESSAGES_WITH_THOUGHT if cot_messages else MESSAGES
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B", use_fast=use_fast)
data_args = DataArguments(template="qwen3", enable_thinking=enable_thinking)
template = get_template_and_fix_tokenizer(tokenizer, data_args)
prompt_ids, answer_ids = template.encode_oneturn(tokenizer, messages)
prompt_ids, answer_ids = template.encode_oneturn(tokenizer, input_messages)
output_messages = MESSAGES if enable_thinking is False else input_messages
prompt_str = (
f"<|im_start|>user\n{messages[0]['content']}<|im_end|>\n<|im_start|>assistant\n"
f"<|im_start|>user\n{output_messages[0]['content']}<|im_end|>\n<|im_start|>assistant\n"
f"{MESSAGES[1]['content']}<|im_end|>\n"
f"<|im_start|>user\n{messages[2]['content']}<|im_end|>\n<|im_start|>assistant\n"
f"<|im_start|>user\n{output_messages[2]['content']}<|im_end|>\n<|im_start|>assistant\n"
)
answer_str = f"{messages[3]['content']}<|im_end|>\n"
if not cot_messages:
answer_str = f"{output_messages[3]['content']}<|im_end|>\n"
if not cot_messages or enable_thinking is False:
if enable_thinking:
answer_str = "<think>\n\n</think>\n\n" + answer_str
else:
@@ -151,18 +152,19 @@ def test_reasoning_encode_oneturn(use_fast: bool, cot_messages: bool, enable_thi
@pytest.mark.parametrize("use_fast", [True, False])
@pytest.mark.parametrize("cot_messages", [True, False])
@pytest.mark.parametrize("enable_thinking", [True, False])
@pytest.mark.parametrize("enable_thinking", [True, False, None])
def test_reasoning_encode_multiturn(use_fast: bool, cot_messages: bool, enable_thinking: bool):
messages = MESSAGES_WITH_THOUGHT if cot_messages else MESSAGES
input_messages = MESSAGES_WITH_THOUGHT if cot_messages else MESSAGES
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B", use_fast=use_fast)
data_args = DataArguments(template="qwen3", enable_thinking=enable_thinking)
template = get_template_and_fix_tokenizer(tokenizer, data_args)
encoded_pairs = template.encode_multiturn(tokenizer, messages)
prompt_str_1 = f"<|im_start|>user\n{messages[0]['content']}<|im_end|>\n<|im_start|>assistant\n"
answer_str_1 = f"{messages[1]['content']}<|im_end|>\n"
prompt_str_2 = f"<|im_start|>user\n{messages[2]['content']}<|im_end|>\n<|im_start|>assistant\n"
answer_str_2 = f"{messages[3]['content']}<|im_end|>\n"
if not cot_messages:
encoded_pairs = template.encode_multiturn(tokenizer, input_messages)
output_messages = MESSAGES if enable_thinking is False else input_messages
prompt_str_1 = f"<|im_start|>user\n{output_messages[0]['content']}<|im_end|>\n<|im_start|>assistant\n"
answer_str_1 = f"{output_messages[1]['content']}<|im_end|>\n"
prompt_str_2 = f"<|im_start|>user\n{output_messages[2]['content']}<|im_end|>\n<|im_start|>assistant\n"
answer_str_2 = f"{output_messages[3]['content']}<|im_end|>\n"
if not cot_messages or enable_thinking is False:
if enable_thinking:
answer_str_1 = "<think>\n\n</think>\n\n" + answer_str_1
answer_str_2 = "<think>\n\n</think>\n\n" + answer_str_2