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cd63278 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | # Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import random
import pytest
from datasets import load_dataset
from transformers import AutoTokenizer
from llamafactory.extras.constants import IGNORE_INDEX
from llamafactory.train.test_utils import load_dataset_module
DEMO_DATA = os.getenv("DEMO_DATA", "llamafactory/demo_data")
TINY_LLAMA3 = os.getenv("TINY_LLAMA3", "llamafactory/tiny-random-Llama-3")
TRAIN_ARGS = {
"model_name_or_path": TINY_LLAMA3,
"stage": "kto",
"do_train": True,
"finetuning_type": "full",
"dataset": "kto_en_demo",
"dataset_dir": "REMOTE:" + DEMO_DATA,
"template": "llama3",
"cutoff_len": 8192,
"output_dir": "dummy_dir",
"overwrite_output_dir": True,
"fp16": True,
}
@pytest.mark.parametrize("num_samples", [16])
def test_feedback_data(num_samples: int):
train_dataset = load_dataset_module(**TRAIN_ARGS)["train_dataset"]
ref_tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA3)
original_data = load_dataset(DEMO_DATA, name="kto_en_demo", split="train")
indexes = random.choices(range(len(original_data)), k=num_samples)
for index in indexes:
messages = original_data["messages"][index]
ref_input_ids = ref_tokenizer.apply_chat_template(messages)
prompt_len = len(ref_tokenizer.apply_chat_template(messages[:-1], add_generation_prompt=True))
ref_labels = [IGNORE_INDEX] * prompt_len + ref_input_ids[prompt_len:]
assert train_dataset["input_ids"][index] == ref_input_ids
assert train_dataset["labels"][index] == ref_labels
assert train_dataset["kto_tags"][index] == original_data["label"][index]
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