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| import os |
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| from transformers import AutoTokenizer |
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| from llamafactory.data import get_template_and_fix_tokenizer |
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| TINY_LLAMA = os.environ.get("TINY_LLAMA", "llamafactory/tiny-random-Llama-3") |
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| MESSAGES = [ |
| {"role": "user", "content": "How are you"}, |
| {"role": "assistant", "content": "I am fine!"}, |
| {"role": "user", "content": "你好"}, |
| {"role": "assistant", "content": "很高兴认识你！"}, |
| ] |
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| def test_encode_oneturn(): |
| tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA) |
| template = get_template_and_fix_tokenizer(tokenizer, name="llama3") |
| prompt_ids, answer_ids = template.encode_oneturn(tokenizer, MESSAGES) |
| assert tokenizer.decode(prompt_ids) == ( |
| "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\nHow are you<|eot_id|>" |
| "<|start_header_id|>assistant<|end_header_id|>\n\nI am fine!<|eot_id|>" |
| "<|start_header_id|>user<|end_header_id|>\n\n你好<|eot_id|>" |
| "<|start_header_id|>assistant<|end_header_id|>\n\n" |
| ) |
| assert tokenizer.decode(answer_ids) == "很高兴认识你！<|eot_id|>" |
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| def test_encode_multiturn(): |
| tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA) |
| template = get_template_and_fix_tokenizer(tokenizer, name="llama3") |
| encoded_pairs = template.encode_multiturn(tokenizer, MESSAGES) |
| assert tokenizer.decode(encoded_pairs[0][0]) == ( |
| "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\nHow are you<|eot_id|>" |
| "<|start_header_id|>assistant<|end_header_id|>\n\n" |
| ) |
| assert tokenizer.decode(encoded_pairs[0][1]) == "I am fine!<|eot_id|>" |
| assert tokenizer.decode(encoded_pairs[1][0]) == ( |
| "<|start_header_id|>user<|end_header_id|>\n\n你好<|eot_id|>" |
| "<|start_header_id|>assistant<|end_header_id|>\n\n" |
| ) |
| assert tokenizer.decode(encoded_pairs[1][1]) == "很高兴认识你！<|eot_id|>" |
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| def test_jinja_template(): |
| tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA) |
| ref_tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA) |
| get_template_and_fix_tokenizer(tokenizer, name="llama3") |
| assert tokenizer.chat_template != ref_tokenizer.chat_template |
| assert tokenizer.apply_chat_template(MESSAGES) == ref_tokenizer.apply_chat_template(MESSAGES) |
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|
| def test_qwen_template(): |
| tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-7B-Instruct") |
| template = get_template_and_fix_tokenizer(tokenizer, name="qwen") |
| prompt_ids, answer_ids = template.encode_oneturn(tokenizer, MESSAGES) |
| assert tokenizer.decode(prompt_ids) == ( |
| "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n" |
| "<|im_start|>user\nHow are you<|im_end|>\n" |
| "<|im_start|>assistant\nI am fine!<|im_end|>\n" |
| "<|im_start|>user\n你好<|im_end|>\n" |
| "<|im_start|>assistant\n" |
| ) |
| assert tokenizer.decode(answer_ids) == "很高兴认识你！<|im_end|>" |
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