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import os
import tempfile
from typing import Callable, Optional
from transformers import AutoConfig, LlamaConfig, LlamaForCausalLM
from mergekit.architecture import get_architecture_info
from mergekit.config import MergeConfiguration
from mergekit.io.lazy_tensor_loader import LazyTensorLoader, ShardedTensorIndex
from mergekit.merge import MergeOptions, run_merge
def run_and_check_merge(
config: MergeConfiguration,
check_nan: bool = True,
check_tensors: bool = True,
validate: Optional[Callable[[str], None]] = None,
index_json_name: Optional[str] = None,
):
if index_json_name is None:
index_json_name = "model.safetensors.index.json"
with tempfile.TemporaryDirectory() as tmpdir:
run_merge(config, out_path=tmpdir, options=MergeOptions())
assert os.path.exists(
os.path.join(tmpdir, index_json_name)
), "No index file for merge"
assert os.path.exists(
os.path.join(tmpdir, "config.json")
), "No config json produced by merge"
if check_nan:
# check for NaN in output
loader = LazyTensorLoader.from_disk(tmpdir, lazy_unpickle=False)
tp = loader.index.tensor_paths
sorted_tensors = sorted(tp.keys(), key=lambda k: tp[k])
for tensor_name in sorted_tensors:
tensor = loader.get_tensor(tensor_name)
has_nan = tensor.view(-1).isnan().any()
assert not has_nan, "Output contains NaN"
if check_tensors:
config = AutoConfig.from_pretrained(tmpdir)
arch_info = get_architecture_info(config)
index = ShardedTensorIndex.from_disk(tmpdir)
for weight_info in arch_info.all_weights(config):
if weight_info.name not in index.tensor_paths:
raise RuntimeError(f"Output missing tensor {tensor_name}")
if validate:
validate(tmpdir)
def make_picollama(path: str, vocab_size: int = 64):
cfg = LlamaConfig(
vocab_size=vocab_size,
hidden_size=32,
intermediate_size=48,
num_attention_heads=16,
num_hidden_layers=2,
)
model = LlamaForCausalLM(cfg)
model.save_pretrained(path, safe_serialization=True)
return str(path)
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