mirror of
https://github.com/hiyouga/LLaMA-Factory.git
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72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
# Copyright 2025 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import pathlib
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import sys
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from unittest.mock import patch
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from llamafactory.v1.config.arg_parser import get_args
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def test_get_args_from_yaml(tmp_path: pathlib.Path):
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config_yaml = """
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### model
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model: "llamafactory/tiny-random-qwen2.5"
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trust_remote_code: true
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use_fast_processor: true
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model_class: "llm"
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kernel_config:
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name: "auto"
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include_kernels: "auto" # choice: null/true/false/auto/kernel_id1,kernel_id2,kernel_id3, default is null
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peft_config:
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name: "lora"
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lora_rank: 0.8
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quant_config: null
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### data
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dataset: "llamafactory/tiny-supervised-dataset"
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cutoff_len: 2048
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### training
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output_dir: "outputs/test_run"
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micro_batch_size: 1
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global_batch_size: 1
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learning_rate: 1.0e-4
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bf16: false
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dist_config: null
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### sample
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sample_backend: "hf"
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max_new_tokens: 128
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"""
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config_file = tmp_path / "config.yaml"
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config_file.write_text(config_yaml, encoding="utf-8")
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test_argv = ["test_args_parser.py", str(config_file)]
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with patch.object(sys, "argv", test_argv):
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data_args, model_args, training_args, sample_args = get_args()
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assert training_args.output_dir == "outputs/test_run"
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assert training_args.micro_batch_size == 1
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assert training_args.global_batch_size == 1
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assert training_args.learning_rate == 1.0e-4
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assert training_args.bf16 is False
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assert training_args.dist_config is None
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assert model_args.model == "llamafactory/tiny-random-qwen2.5"
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assert model_args.kernel_config.name == "auto"
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assert model_args.kernel_config.get("include_kernels") == "auto"
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assert model_args.peft_config.name == "lora"
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assert model_args.peft_config.get("lora_rank") == 0.8
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