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""" |
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Test classes for checking functionality of the cfg normalization |
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""" |
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import unittest |
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from unittest.mock import patch |
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from axolotl.utils.config import normalize_cfg_datasets, normalize_config |
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from axolotl.utils.dict import DictDefault |
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class NormalizeConfigTestCase(unittest.TestCase): |
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""" |
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test class for normalize_config checks |
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""" |
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def _get_base_cfg(self): |
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return DictDefault( |
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{ |
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"base_model": "JackFram/llama-68m", |
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"base_model_config": "JackFram/llama-68m", |
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"tokenizer_type": "LlamaTokenizer", |
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"num_epochs": 1, |
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"micro_batch_size": 1, |
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"gradient_accumulation_steps": 1, |
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} |
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) |
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def test_lr_as_float(self): |
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cfg = ( |
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self._get_base_cfg() |
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| DictDefault( |
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{ |
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"learning_rate": "5e-5", |
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} |
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) |
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) |
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normalize_config(cfg) |
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assert cfg.learning_rate == 0.00005 |
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def test_base_model_config_set_when_empty(self): |
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cfg = self._get_base_cfg() |
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del cfg.base_model_config |
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normalize_config(cfg) |
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assert cfg.base_model_config == cfg.base_model |
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def test_chat_template_chatml(self): |
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cfg = DictDefault( |
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{ |
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"chat_template": "chatml", |
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"datasets": [ |
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{ |
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"path": "lorem/ipsum", |
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"type": "sharegpt", |
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"conversation": "vicuna_v1.1", |
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}, |
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{ |
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"path": "sit/amet", |
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"type": "sharegpt", |
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}, |
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], |
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} |
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) |
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normalize_cfg_datasets(cfg) |
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assert cfg.datasets[0].conversation == "vicuna_v1.1" |
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assert cfg.datasets[1].conversation == "chatml" |
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@patch("axolotl.utils.config.is_torch_bf16_gpu_available") |
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def test_bf16_auto_setter_available(self, mock_bf16_avail): |
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cfg = self._get_base_cfg() |
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cfg.bf16 = "auto" |
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mock_bf16_avail.return_value = True |
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normalize_config(cfg) |
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self.assertTrue(cfg.bf16) |
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@patch("axolotl.utils.config.is_torch_bf16_gpu_available") |
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def test_bf16_auto_setter_not_available(self, mock_bf16_avail): |
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cfg = self._get_base_cfg() |
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cfg.bf16 = "auto" |
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mock_bf16_avail.return_value = False |
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normalize_config(cfg) |
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self.assertFalse(cfg.bf16) |
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