Add benchmark_forward.py

src/petals/cli/benchmark_forward.py

@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+
+import argparse
+import multiprocessing as mp
+from time import perf_counter
+
+import torch
+from hivemind.utils.logging import get_logger
+from petals import DistributedBloomForCausalLM
+from transformers import BloomTokenizerFast
+
+logger = get_logger()
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model", type=str, default="bigscience/bloom-petals")
+    parser.add_argument("--initial_peers", type=str, nargs='+', default=["/ip4/185.244.175.92/tcp/31337/p2p/QmehSoMKScoMF3HczLwaLVnw2Lgsap4bhAMrULEzGc1fSV"])
+    parser.add_argument("-p", "--n_processes", type=int, required=True)
+    parser.add_argument("-l", "--seq_len", type=int, default=128)
+    parser.add_argument("-s", "--n_steps", type=int, default=100)
+    parser.add_argument("-b", "--batch_size", type=int, required=True)
+    args = parser.parse_args()
+
+    processes = [mp.Process(target=benchmark_forward, args=(i, args,)) for i in range(args.n_processes)]
+    for proc in processes:
+        proc.start()
+    for proc in processes:
+        proc.join()
+
+
+@torch.inference_mode()
+def benchmark_forward(process_idx, args):
+    tokenizer = BloomTokenizerFast.from_pretrained(args.model)
+    model = DistributedBloomForCausalLM.from_pretrained(args.model)#, initial_peers=args.initial_peers)
+    logger.info(f"Created model: {process_idx=} {model.device=}")
+
+    torch.manual_seed(42)
+    for step in range(args.n_steps):
+        input_ids = torch.randint(100, 10000, size=(args.batch_size, args.seq_len))
+        logger.info(f"Fwd begin {input_ids.shape=}")
+        outputs = model.forward(input_ids)
+        logger.info("Fwd end")
+
+        if step == 0:
+            start_time = perf_counter()
+        else:
+            speed = step / (perf_counter() - start_time) * input_ids.numel()
+            logger.info(f"{process_idx=} {step=} {speed=:.3f}")
+
+    logger.info(f"Final result: {process_idx=} {speed=:.3f}")
+
+
+if __name__ == "__main__":
+    main()