231a67e70b
* working * fixes * deprecate --iterable; cleanup * pretrain_multipack_buffer_size -> streaming_multipack_buffer_size * improvements * tests * remove unused * docs, examples * nit * nit * add val_set_size validation * val * nit * min * coderabbito * cleanup * nit * add depr warning, cleanup * nit * fix test, fix quarto * fix * review comments * review comments * fix
74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
"""E2E tests for streaming dataset functionality"""
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# pylint: disable=duplicate-code
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import pytest
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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, validate_config
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from axolotl.utils.dict import DictDefault
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from .utils import check_model_output_exists, check_tensorboard
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class TestStreamingDatasets:
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"""Test case for streaming datasets"""
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@pytest.mark.parametrize(
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"sample_packing",
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[True, False],
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)
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def test_streaming_dataset(self, temp_dir, sample_packing):
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"""Test streaming datasets"""
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cfg = DictDefault(
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{
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"base_model": "HuggingFaceTB/SmolLM2-135M",
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"flash_attention": True,
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"sequence_len": 1024,
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"sample_packing": sample_packing,
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"pretrain_multipack_attn": sample_packing,
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"streaming_multipack_buffer_size": 10000,
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"dataset_processes": 1,
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"special_tokens": {
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"pad_token": "<|endoftext|>",
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},
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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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# Streaming config
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"streaming": True,
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"max_steps": 3,
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"micro_batch_size": 1,
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"gradient_accumulation_steps": 1,
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"val_set_size": 0.0,
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"output_dir": temp_dir,
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"learning_rate": 0.00001,
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"optimizer": "adamw_torch_fused",
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"lr_scheduler": "cosine",
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"save_safetensors": True,
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"bf16": "auto",
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"use_tensorboard": True,
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"save_first_step": False,
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}
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)
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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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train(cfg=cfg, dataset_meta=dataset_meta)
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check_model_output_exists(temp_dir, cfg)
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# Verify training actually happened by checking loss decrease
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check_tensorboard(
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temp_dir + "/runs",
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"train/train_loss",
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3.0,
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"Train Loss (%s) is too high",
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)
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