smoke test
This commit is contained in:
Dan Saunders
261
tests/e2e/test_streaming.py
Normal file
261
tests/e2e/test_streaming.py
Normal file
@@ -0,0 +1,261 @@
|
||||
"""E2E tests for streaming dataset functionality"""
|
||||
|
||||
import pytest
|
||||
|
||||
from axolotl.common.datasets import load_datasets
|
||||
from axolotl.train import train
|
||||
from axolotl.utils.config import normalize_config, validate_config
|
||||
from axolotl.utils.dict import DictDefault
|
||||
|
||||
from .utils import check_model_output_exists, check_tensorboard
|
||||
|
||||
|
||||
class TestStreamingDatasets:
|
||||
"""Test case for streaming datasets with different mixing strategies"""
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("dataset_mixing_strategy", "mixing_weights"),
|
||||
[
|
||||
("round_robin", None),
|
||||
("weighted", [0.7, 0.3]),
|
||||
("random", None),
|
||||
],
|
||||
)
|
||||
def test_streaming_dataset_mixing_strategies(
|
||||
self, temp_dir, dataset_mixing_strategy, mixing_weights
|
||||
):
|
||||
"""Test different mixing strategies with streaming datasets"""
|
||||
|
||||
cfg = DictDefault(
|
||||
{
|
||||
"base_model": "HuggingFaceTB/SmolLM2-135M",
|
||||
"flash_attention": True,
|
||||
"sequence_len": 1024,
|
||||
"sample_packing": False,
|
||||
"dataset_processes": 1,
|
||||
"special_tokens": {
|
||||
"pad_token": "<|endoftext|>",
|
||||
},
|
||||
"datasets": [
|
||||
{
|
||||
"path": "mhenrichsen/alpaca_2k_test",
|
||||
"type": "alpaca",
|
||||
},
|
||||
{
|
||||
"path": "tatsu-lab/alpaca",
|
||||
"type": "alpaca",
|
||||
},
|
||||
],
|
||||
# Streaming config
|
||||
"streaming": True,
|
||||
"max_steps": 3, # Very small for smoke test
|
||||
"dataset_mixing_strategy": dataset_mixing_strategy,
|
||||
"micro_batch_size": 1,
|
||||
"gradient_accumulation_steps": 1,
|
||||
"val_set_size": 0.0,
|
||||
"output_dir": temp_dir,
|
||||
"learning_rate": 0.00001,
|
||||
"optimizer": "adamw_torch_fused",
|
||||
"lr_scheduler": "cosine",
|
||||
"save_safetensors": True,
|
||||
"bf16": "auto",
|
||||
"use_tensorboard": True,
|
||||
"save_first_step": False,
|
||||
}
|
||||
)
|
||||
|
||||
# Add mixing weights if specified
|
||||
if mixing_weights:
|
||||
cfg["mixing_weights"] = mixing_weights
|
||||
|
||||
cfg = validate_config(cfg)
|
||||
normalize_config(cfg)
|
||||
dataset_meta = load_datasets(cfg=cfg)
|
||||
|
||||
train(cfg=cfg, dataset_meta=dataset_meta)
|
||||
check_model_output_exists(temp_dir, cfg)
|
||||
|
||||
# Verify training actually happened by checking loss decrease
|
||||
check_tensorboard(
|
||||
temp_dir + "/runs",
|
||||
"train/train_loss",
|
||||
25.0, # Loss should be reasonable for a smoke test (higher threshold for streaming)
|
||||
"Train Loss (%s) is too high",
|
||||
)
|
||||
|
||||
def test_streaming_eval_specific_mixing(self, temp_dir):
|
||||
"""Test eval-specific mixing strategy override"""
|
||||
|
||||
cfg = DictDefault(
|
||||
{
|
||||
"base_model": "HuggingFaceTB/SmolLM2-135M",
|
||||
"flash_attention": True,
|
||||
"sequence_len": 512,
|
||||
"sample_packing": False,
|
||||
"dataset_processes": 1,
|
||||
"special_tokens": {
|
||||
"pad_token": "<|endoftext|>",
|
||||
},
|
||||
"datasets": [
|
||||
{
|
||||
"path": "mhenrichsen/alpaca_2k_test",
|
||||
"type": "alpaca",
|
||||
},
|
||||
{
|
||||
"path": "tatsu-lab/alpaca",
|
||||
"type": "alpaca",
|
||||
},
|
||||
],
|
||||
"test_datasets": [
|
||||
{
|
||||
"path": "mhenrichsen/alpaca_2k_test",
|
||||
"type": "alpaca",
|
||||
"split": "train", # Specify train split for eval dataset
|
||||
},
|
||||
{
|
||||
"path": "tatsu-lab/alpaca",
|
||||
"type": "alpaca",
|
||||
"split": "train", # Specify train split for eval dataset
|
||||
},
|
||||
],
|
||||
# Streaming config
|
||||
"streaming": True,
|
||||
"eval_streaming": True,
|
||||
"max_steps": 3,
|
||||
# Different mixing for train vs eval
|
||||
"dataset_mixing_strategy": "round_robin",
|
||||
"eval_dataset_mixing_strategy": "weighted",
|
||||
"eval_mixing_weights": [0.6, 0.4],
|
||||
"micro_batch_size": 1,
|
||||
"gradient_accumulation_steps": 1,
|
||||
"output_dir": temp_dir,
|
||||
"learning_rate": 0.00001,
|
||||
"optimizer": "adamw_torch_fused",
|
||||
"lr_scheduler": "cosine",
|
||||
"save_safetensors": True,
|
||||
"bf16": "auto",
|
||||
"use_tensorboard": True,
|
||||
"save_first_step": False,
|
||||
"eval_steps": 3, # Eval at the end
|
||||
}
|
||||
)
|
||||
|
||||
cfg = validate_config(cfg)
|
||||
normalize_config(cfg)
|
||||
dataset_meta = load_datasets(cfg=cfg)
|
||||
|
||||
train(cfg=cfg, dataset_meta=dataset_meta)
|
||||
check_model_output_exists(temp_dir, cfg)
|
||||
|
||||
# Check both train and eval losses
|
||||
check_tensorboard(
|
||||
temp_dir + "/runs",
|
||||
"train/train_loss",
|
||||
25.0,
|
||||
"Train Loss (%s) is too high",
|
||||
)
|
||||
check_tensorboard(
|
||||
temp_dir + "/runs",
|
||||
"eval/eval_loss",
|
||||
25.0,
|
||||
"Eval Loss (%s) is too high",
|
||||
)
|
||||
|
||||
def test_streaming_validation_error(self, temp_dir):
|
||||
"""Test that pydantic validation catches invalid streaming configs"""
|
||||
|
||||
cfg = DictDefault(
|
||||
{
|
||||
"base_model": "HuggingFaceTB/SmolLM2-135M",
|
||||
"datasets": [
|
||||
{
|
||||
"path": "mhenrichsen/alpaca_2k_test",
|
||||
"type": "alpaca",
|
||||
},
|
||||
{
|
||||
"path": "tatsu-lab/alpaca",
|
||||
"type": "alpaca",
|
||||
},
|
||||
],
|
||||
"streaming": True,
|
||||
"max_steps": 3,
|
||||
# Invalid: wrong number of weights for datasets
|
||||
"dataset_mixing_strategy": "weighted",
|
||||
"mixing_weights": [1.0], # Should be [0.x, 0.y] for 2 datasets
|
||||
"micro_batch_size": 1,
|
||||
"gradient_accumulation_steps": 1,
|
||||
"output_dir": temp_dir,
|
||||
"learning_rate": 0.00001,
|
||||
"special_tokens": {
|
||||
"pad_token": "<|endoftext|>",
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
# This should raise a validation error
|
||||
with pytest.raises(Exception) as exc_info:
|
||||
validate_config(cfg)
|
||||
|
||||
# Verify it's the right validation error
|
||||
assert "mixing_weights length" in str(exc_info.value)
|
||||
assert "must match number of datasets" in str(exc_info.value)
|
||||
|
||||
def test_streaming_three_datasets_weighted(self, temp_dir):
|
||||
"""Test weighted mixing with three datasets"""
|
||||
|
||||
cfg = DictDefault(
|
||||
{
|
||||
"base_model": "HuggingFaceTB/SmolLM2-135M",
|
||||
"flash_attention": True,
|
||||
"sequence_len": 512,
|
||||
"sample_packing": False,
|
||||
"dataset_processes": 1,
|
||||
"special_tokens": {
|
||||
"pad_token": "<|endoftext|>",
|
||||
},
|
||||
"datasets": [
|
||||
{
|
||||
"path": "mhenrichsen/alpaca_2k_test",
|
||||
"type": "alpaca",
|
||||
},
|
||||
{
|
||||
"path": "tatsu-lab/alpaca",
|
||||
"type": "alpaca",
|
||||
},
|
||||
{
|
||||
"path": "yahma/alpaca-cleaned",
|
||||
"type": "alpaca",
|
||||
},
|
||||
],
|
||||
# Streaming config
|
||||
"streaming": True,
|
||||
"max_steps": 3,
|
||||
"dataset_mixing_strategy": "weighted",
|
||||
"mixing_weights": [0.5, 0.3, 0.2],
|
||||
"micro_batch_size": 1,
|
||||
"gradient_accumulation_steps": 1,
|
||||
"val_set_size": 0.0,
|
||||
"output_dir": temp_dir,
|
||||
"learning_rate": 0.00001,
|
||||
"optimizer": "adamw_torch_fused",
|
||||
"lr_scheduler": "cosine",
|
||||
"save_safetensors": True,
|
||||
"bf16": "auto",
|
||||
"use_tensorboard": True,
|
||||
"save_first_step": False,
|
||||
}
|
||||
)
|
||||
|
||||
cfg = validate_config(cfg)
|
||||
normalize_config(cfg)
|
||||
dataset_meta = load_datasets(cfg=cfg)
|
||||
|
||||
train(cfg=cfg, dataset_meta=dataset_meta)
|
||||
check_model_output_exists(temp_dir, cfg)
|
||||
|
||||
check_tensorboard(
|
||||
temp_dir + "/runs",
|
||||
"train/train_loss",
|
||||
25.0,
|
||||
"Train Loss (%s) is too high",
|
||||
)
|
||||
Reference in New Issue
Block a user