File size: 1,590 Bytes
91ac3cc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | from __future__ import annotations
import argparse
import json
from transformers import LlamaForCausalLM
from kawk50m.cli import configure_utf8_stdio
from kawk50m.config import build_llama_config, count_unique_parameters, load_yaml
def main() -> None:
configure_utf8_stdio()
parser = argparse.ArgumentParser(description="Inspect the configured model size.")
parser.add_argument("--config", default="configs/model_50m.yaml")
args = parser.parse_args()
config, expected = build_llama_config(load_yaml(args.config))
model = LlamaForCausalLM(config)
unique_parameters = count_unique_parameters(model)
embedding_parameters = config.vocab_size * config.hidden_size
result = {
"parameters": unique_parameters,
"parameters_millions": round(unique_parameters / 1_000_000, 6),
"embedding_parameters": embedding_parameters,
"transformer_and_norm_parameters": unique_parameters - embedding_parameters,
"layers": config.num_hidden_layers,
"hidden_size": config.hidden_size,
"vocab_size": config.vocab_size,
"attention_heads": config.num_attention_heads,
"kv_heads": config.num_key_value_heads,
"context_length": config.max_position_embeddings,
"expected_parameters": expected,
}
print(json.dumps(result, ensure_ascii=False, indent=2))
if expected is not None and unique_parameters != expected:
raise RuntimeError(
f"Parameter count mismatch: expected={expected}, actual={unique_parameters}"
)
if __name__ == "__main__":
main()
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