import re import pytest import shutil from pathlib import Path from typing import Optional, Iterator from tempfile import TemporaryDirectory from subprocess import PIPE, Popen # === # = Arguments # === @pytest.fixture(scope="session", params=[1, 2]) def llama_version(request) -> int: return request.param @pytest.fixture(scope="session") def llama_meta(pytestconfig, llama_version: int ) -> Path: if llama_version == 1: return pytestconfig.getoption("llama_path") return pytestconfig.getoption("llama2_path") @pytest.fixture(scope="session") def cache_dir(pytestconfig) -> Optional[Path]: return pytestconfig.getoption("cache_path") @pytest.fixture(scope="session") def data(pytestconfig) -> Path: return pytestconfig.getoption("data_path") @pytest.fixture(scope="session") def vocab(pytestconfig) -> Path: return pytestconfig.getoption("vocab_path") @pytest.fixture(scope="session") def root_dir(pytestconfig) -> TemporaryDirectory: prefix = pytestconfig.getoption("tmp_dir") prefix = None if prefix is None else str(prefix/"tmp") return TemporaryDirectory(prefix=prefix) # === # = Paths # === @pytest.fixture(scope="session") def root(root_dir, llama_version: int) -> Path: return Path(f"{root_dir.name}-{llama_version}") @pytest.fixture(scope="session") def llama_meta2mega(root: Path) -> Path: return root/"llama-meta2mega" @pytest.fixture(scope="session") def llama_hf2mega(root: Path) -> Path: return root/"llama-hf2mega" @pytest.fixture(scope="session") def vocab_hf2mega(llama_hf2mega: Path) -> Path: return llama_hf2mega/"tokenizer.model" @pytest.fixture(scope="session") def llama_sharded(root: Path) -> Path: return root/"llama-sharded" @pytest.fixture(scope="session") def llama_unsharded(root: Path) -> Path: return root/"llama-unsharded" @pytest.fixture(scope="session") def llama_mega2hf(root: Path) -> Path: return root/"llama-mega2hf" @pytest.fixture(scope="session") def llama_unsharded2hf(root: Path) -> Path: return root/"llama-unsharded2hf" # === # = Utils # === def execute(cmd: list[str]) -> Iterator[str]: with Popen(cmd, stdout=PIPE, text=True) as proc: yield from map(lambda line: line.strip(), iter(proc.stdout.readline, "")) assert proc.wait() == 0 def verify_correctness(our_path: Path, cache_dir: Optional[Path], data: Path, vocab: Path, llama_v: int = 2) -> list[float]: llama_version = llama_v model_name = "llama" if llama_version == 1 else "llama2" distributed_args = ["--nproc_per_node=1", "--nnodes=1", "--node_rank=0", "--master_addr=localhost", "--master_port=8001"] main_args = [f"--model_name={model_name}", f"--load={our_path}", f"--data_path={data}", "--no_new_tokens", "--tokenizer_type=SentencePieceTokenizer", "--model_size=7", f"--vocab_file={vocab}"] extra_args = ["--hidden_dropout=0.0", "--attention_dropout=0.0", "--no_bias_dropout_fusion", "--no_bias_gelu_fusion"] cmd = ["torchrun"] + distributed_args + ["verify_correctness.py"] \ + main_args + extra_args if cache_dir is not None: cmd.append(f"--huggingface_cache={cache_dir}") if llama_version == 1: cmd.append("--layernorm_epsilon=1e-6") max_errors = [] for line in execute(cmd): if any(key in line for key in ["Iteration", "Max abs", "Abs loss"]): print(line) if rmatch := re.match(fr"^.*max=([0-9]+\.[0-9]+).*$", line): max_errors.append(float(rmatch.group(1))) assert sum(max_errors)/len(max_errors) <= 0.001, "Avg max error exceeds tolerance (0.001)" return max_errors def shard(load_dir: Path, save_dir: Path, llama_v: int = 2, tp: int = 1, pp: int = 1): llama_version = llama_v model_type = "llama" if llama_version == 1 else "llama2" cmd = ["python", "tools/checkpoint_util.py", f"--load_dir={load_dir}", f"--save_dir={save_dir}", f"--model_type={model_type}", "--true_vocab_size=32000", f"--target_tensor_parallel_size={tp}", f"--target_pipeline_parallel_size={pp}"] ignores = {"---", "...", "Setting"} for line in execute(cmd): if all(avoid not in line for avoid in ignores): print(line) def mega2hf(load_dir: Path, out_dir: Path, llama_v: int): model_type = "llama" if llama_v == 1 else "llama2" with Popen(["python", "weights_conversion/megatron_to_hf.py", f"--model={model_type}", f"--input_dir={load_dir}", f"--output_dir={out_dir}"]) as proc: assert proc.wait() == 0 # === # = Tests # === @pytest.mark.incremental class TestLlamaWeights: def test_path_exists(self, llama_meta: Path): assert llama_meta.exists() and llama_meta.is_dir() def test_meta2mega(self, llama_meta2mega: Path, llama_meta: Path, llama_version: int, cache_dir: Optional[Path], data: Path, vocab: Path): assert not llama_meta2mega.exists() model_name = "llama" if llama_version == 1 else "llama2" with Popen(["python", Path("weights_conversion")/"hf_to_megatron.py", model_name, "--size=7", f"--out={llama_meta2mega}", f"--cache-dir={llama_meta}"]) as proc: assert proc.wait() == 0 assert llama_meta2mega.exists() if llama_version == 1: llama_meta = cache_dir verify_correctness(llama_meta2mega, llama_meta, data, vocab, llama_v=llama_version) shutil.rmtree(llama_meta2mega) # all future tests will only use llama_hf2mega def test_hf2mega(self, llama_hf2mega: Path, cache_dir: Optional[Path], data: Path, vocab_hf2mega: Path, llama_version: int): assert not llama_hf2mega.exists() model_name = "llama" if llama_version == 1 else "llama2" cmd = ["python", Path("weights_conversion")/"hf_to_megatron.py", model_name, "--size=7", f"--out={llama_hf2mega}"] if cache_dir is not None: cmd.append(f"--cache-dir={cache_dir}") with Popen(cmd) as proc: assert proc.wait() == 0 assert llama_hf2mega.exists() verify_correctness(llama_hf2mega, cache_dir, data, vocab_hf2mega, llama_v=llama_version) def test_metallama_verification(self, llama_hf2mega: Path, llama_meta: Path, llama_version: int, data: Path, vocab: Path): verify_correctness(llama_hf2mega, llama_meta, data, vocab, llama_v=llama_version) def test_shard_unshard(self, llama_hf2mega: Path, llama_sharded: Path, llama_unsharded: Path, cache_dir: Optional[Path], llama_version: int, data: Path, vocab_hf2mega: Path): print("sharding to tp=2, pp=2") shard(llama_hf2mega, llama_sharded, llama_v=llama_version, tp=2, pp=2) assert llama_sharded.exists() print("merging back to tp=1, pp=1") shard(llama_sharded, llama_unsharded, llama_v=llama_version, tp=1, pp=1) assert llama_unsharded.exists() verify_correctness(llama_unsharded, cache_dir, data, vocab_hf2mega, llama_v=llama_version) def test_mega2hf(self, llama_hf2mega: Path, llama_mega2hf: Path, cache_dir: Optional[Path], data: Path, vocab_hf2mega: Path, llama_version: int ): mega2hf(llama_hf2mega, llama_mega2hf, llama_version) verify_correctness(llama_mega2hf, cache_dir, data, vocab_hf2mega, llama_v=llama_version) def test_unsharded2hf(self, llama_unsharded: Path, llama_unsharded2hf: Path, cache_dir: Optional[Path], data: Path, vocab_hf2mega: Path, llama_version: int): mega2hf(llama_unsharded, llama_unsharded2hf, llama_version) verify_correctness(llama_unsharded2hf, cache_dir, data, vocab_hf2mega, llama_v=llama_version)