| """ |
| e2e tests for kd trainer support in Axolotl |
| """ |
|
|
| from pathlib import Path |
|
|
| import pytest |
| from e2e.utils import check_tensorboard, require_torch_2_5_1 |
|
|
| from axolotl.cli.args import TrainerCliArgs |
| from axolotl.common.datasets import load_datasets |
| from axolotl.train import train |
| from axolotl.utils.config import normalize_config, prepare_plugins, validate_config |
| from axolotl.utils.dict import DictDefault |
|
|
|
|
| @pytest.fixture(name="kd_min_cfg") |
| def min_cfg(temp_dir): |
| return { |
| "base_model": "osllmai-community/Llama-3.2-1B", |
| "tokenizer_config": "axolotl-ai-co/Llama-3.3-70B-Instruct-tokenizer", |
| "plugins": [ |
| "axolotl.integrations.kd.KDPlugin", |
| "axolotl.integrations.liger.LigerPlugin", |
| ], |
| "liger_rms_norm": True, |
| "liger_glu_activation": True, |
| "torch_compile": True, |
| "chat_template": "llama3", |
| "kd_trainer": True, |
| "kd_ce_alpha": 0.1, |
| "kd_alpha": 0.9, |
| "kd_temperature": 1.0, |
| "dataloader_prefetch_factor": 8, |
| "dataloader_num_workers": 4, |
| "dataloader_pin_memory": True, |
| "datasets": [ |
| { |
| "path": "axolotl-ai-co/evolkit-logprobs-pipeline-75k-v2-sample", |
| "type": "axolotl.integrations.kd.chat_template", |
| "field_messages": "messages_combined", |
| "split": "train", |
| "logprobs_field": "llm_text_generation_vllm_logprobs", |
| "temperature": 1.0, |
| "preprocess_shards": 2, |
| }, |
| ], |
| "val_set_size": 0.0, |
| "sequence_len": 2048, |
| "sample_packing": True, |
| "pad_to_sequence_len": True, |
| "gradient_accumulation_steps": 2, |
| "micro_batch_size": 1, |
| "num_epochs": 1, |
| "optimizer": "adamw_8bit", |
| "lr_scheduler": "cosine", |
| "learning_rate": 0.00001, |
| "bf16": "auto", |
| "gradient_checkpointing": True, |
| "flash_attention": True, |
| "special_tokens": { |
| "pad_token": "<|end_of_text|>", |
| "eos_token": "<|eot_id|>", |
| }, |
| "max_steps": 5, |
| "output_dir": temp_dir, |
| "save_safetensors": True, |
| "use_tensorboard": True, |
| } |
|
|
|
|
| class TestKnowledgeDistillation: |
| """ |
| Test case for Knowledge Distillation |
| """ |
|
|
| |
| |
| @require_torch_2_5_1 |
| def test_llama_kd(self, temp_dir, kd_min_cfg): |
| cfg = DictDefault(kd_min_cfg) |
| |
| cfg = validate_config(cfg) |
| prepare_plugins(cfg) |
| normalize_config(cfg) |
| cli_args = TrainerCliArgs() |
| dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args) |
|
|
| train(cfg=cfg, dataset_meta=dataset_meta) |
| assert (Path(temp_dir) / "model.safetensors").exists() |
| check_tensorboard( |
| temp_dir + "/runs", "train/loss", 1.0, "Train Loss is too high" |
| ) |
|
|
| @pytest.mark.parametrize( |
| "load_in_8bit", |
| [True, False], |
| ) |
| def test_llama_lora_kd(self, temp_dir, kd_min_cfg, load_in_8bit): |
| cfg = DictDefault( |
| { |
| "load_in_8bit": load_in_8bit, |
| "torch_compile": False, |
| "adapter": "lora", |
| "peft_use_dora": True, |
| "lora_target_linear": True, |
| "lora_r": 16, |
| "lora_alpha": 32, |
| "lora_dropout": 0.0, |
| } |
| | kd_min_cfg |
| ) |
| |
| cfg = validate_config(cfg) |
| prepare_plugins(cfg) |
| normalize_config(cfg) |
| cli_args = TrainerCliArgs() |
| dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args) |
|
|
| train(cfg=cfg, dataset_meta=dataset_meta) |
| assert (Path(temp_dir) / "adapter_model.safetensors").exists() |
| check_tensorboard( |
| temp_dir + "/runs", "train/loss", 1.0, "Train Loss is too high" |
| ) |
|
|
