77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
"""
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E2E smoke test for Aux-Loss-Free MoE routing on Qwen3-MoE tiny
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"""
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import unittest
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from axolotl.common.datasets import load_datasets
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from axolotl.train import train
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from axolotl.utils.config import normalize_config, prepare_plugins, validate_config
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from axolotl.utils.dict import DictDefault
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from .utils import check_model_output_exists, with_temp_dir
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class TestQwen3MoeAuxFree(unittest.TestCase):
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@with_temp_dir
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def test_qwen3_moe_aux_free_smoke(self, temp_dir):
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cfg = DictDefault(
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{
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"base_model": "trl-internal-testing/tiny-Qwen3MoeForCausalLM",
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"tokenizer_config": "trl-internal-testing/tiny-Qwen3MoeForCausalLM",
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"flash_attention": False,
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"sequence_len": 512,
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"bf16": False,
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"fp16": False,
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"val_set_size": 0.02,
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"special_tokens": {},
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"datasets": [
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{
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"path": "mhenrichsen/alpaca_2k_test",
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"type": "alpaca",
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},
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],
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"num_epochs": 1,
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"micro_batch_size": 2,
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"gradient_accumulation_steps": 1,
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"output_dir": temp_dir,
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"learning_rate": 1e-5,
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"optimizer": "adamw_torch",
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"lr_scheduler": "cosine",
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"max_steps": 5,
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"save_steps": 0,
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"eval_steps": 0,
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"save_first_step": False,
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# Aux-free plugin and toggles
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"plugins": [
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"axolotl.integrations.aux_free_router.plugin.AuxFreeMoEPlugin",
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],
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"moe_balance_type": "noaux_tc",
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"moe_update_rate": 0.01,
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"moe_update_momentum": 0.9,
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"moe_bias_cap": 2.0,
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}
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)
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prepare_plugins(cfg)
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cfg = validate_config(cfg)
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normalize_config(cfg)
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dataset_meta = load_datasets(cfg=cfg)
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model, _, _ = train(cfg=cfg, dataset_meta=dataset_meta)
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# check that at least one sparse MoE block has been patched
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found = False
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for m in model.modules():
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if m.__class__.__name__.endswith("SparseMoeBlock") and hasattr(
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m, "_afb_patched"
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):
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assert m._afb_patched is True
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assert hasattr(m, "_afb_bias") and m._afb_bias.ndim == 1
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assert hasattr(m, "_afb_counts") and m._afb_counts.ndim == 1
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found = True
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break
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assert found, "No Qwen3-MoE sparse block patched by aux-free plugin"
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check_model_output_exists(temp_dir, cfg)
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