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import argparse
import torch
from hivemind.utils.logging import get_logger, use_hivemind_log_handler
from tqdm.auto import trange
from src.bloom.block import BloomBlock
from src.bloom.model import BloomConfig
from src.bloom.ops import build_alibi_tensor
use_hivemind_log_handler("in_root_logger")
logger = get_logger(__file__)
logger.warning("inference_one_block will soon be deprecated in favour of tests!")
def print_device_info(device=None):
"""Prints device stats. Code from https://stackoverflow.com/a/53374933/12891528"""
device = torch.device(device or ("cuda" if torch.cuda.is_available() else "cpu"))
logger.info(f"Using device: {device}")
# Additional Info when using cuda
if device.type == "cuda":
logger.info(torch.cuda.get_device_name(0))
logger.info(f"Memory Usage:")
logger.info(f"Allocated: {round(torch.cuda.memory_allocated(0) / 1024 ** 3, 1)} GB")
logger.info(f"Cached: {round(torch.cuda.memory_cached(0) / 1024 ** 3, 1)} GB")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run a single bloom block locally on dummy data")
parser.add_argument("--config", required=True, type=str, help="Path to a config json file")
parser.add_argument("--state_dict", default=None, type=str, help="Optional path to saved block state dict")
parser.add_argument("--layer_index", default=0, type=int, help="Optional path to saved block state dict")
parser.add_argument("--num_steps", default=500, type=int, help="How many inference steps to run")
parser.add_argument("--device", default=None, type=str, help="Run inference on this device")
args = parser.parse_args()
if args.device is None:
args.device = "cuda" if torch.cuda.is_available() else "cpu"
config = BloomConfig.from_json_file(args.config)
block = BloomBlock(config, args.layer_index).to(args.device)
cache = None
for i in trange(args.num_steps):
dummy_input = torch.randn(1, 1, config.hidden_size, device=args.device)
alibi = build_alibi_tensor(i + 1, config.num_attention_heads).to(args.device)
with torch.no_grad():
outputs, cache = block.forward(dummy_input, alibi=alibi, use_cache=True, layer_past=cache)
print_device_info(args.device)
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