[None][feat] Dev DeepConf (#8362)

Signed-off-by: Dong Cao <[email protected]>

Author: dcaox

examples/scaffolding/contrib/DeepConf/run_generation.py

@@ -0,0 +1,176 @@
+import argparse
+import time
+
+from tensorrt_llm.scaffolding import (NativeGenerationController,
+                                      ScaffoldingLlm, TRTLLMWorker)
+from tensorrt_llm.scaffolding.contrib.DeepConf import (
+    DeepConfOfflineController, DeepConfOfflineMajorityVoteController,
+    DeepConfOnlineController, DeepConfOnlineMajorityVoteController)
+
+_RUN_TYPE_TO_IMPL = {
+    "offline": DeepConfOfflineController,
+    "online": DeepConfOnlineController,
+    "offline_majority_vote": DeepConfOfflineMajorityVoteController,
+    "online_majority_vote": DeepConfOnlineMajorityVoteController,
+}
+
+
+def parse_arguments():
+    parser = argparse.ArgumentParser()
+    # .e.g. DeepSeek-R1/DeepSeek-R1-Distill-Qwen-7B
+    parser.add_argument(
+        '--model_dir',
+        type=str,
+        required=True,
+        help="Path to the directory containing the generation model")
+    parser.add_argument('--run_type',
+                        type=str,
+                        required=True,
+                        choices=list(_RUN_TYPE_TO_IMPL.keys()),
+                        help="Type of the run. Available choices: %(choices)s")
+    parser.add_argument('--sample_num', type=int, default=20)
+    parser.add_argument('--conf_group_size', type=int, default=128)
+    parser.add_argument('--conf_threshold', type=float, default=0.5)
+    parser.add_argument('--vote_policy',
+                        type=str,
+                        default="top10_bottom_window_filtered")
+    parser.add_argument('--warmup_sample_num', type=int, default=5)
+    parser.add_argument('--confidence_percentile', type=int, default=90)
+    parser.add_argument('--logprobs_topk', type=int, default=20)
+    parser.add_argument('--max_tokens', type=int, default=8192)
+    parser.add_argument('--temperature', type=float, default=0.6)
+    parser.add_argument('--top_p', type=float, default=0.95)
+    args = parser.parse_args()
+    return args
+
+
+def run_scaffolding_llm(prompts, proposer_worker, controller):
+    llm = ScaffoldingLlm(
+        controller,
+        {
+            NativeGenerationController.WorkerTag.GENERATION: proposer_worker,
+        },
+    )
+    time_start = time.time()
+    results = llm.generate(prompts)
+    time_end = time.time()
+    print(f"time cost: {time_end - time_start} seconds")
+    for i, result in enumerate(results):
+        print(f"result {i}:\n{result.outputs[0].text}")
+    llm.shutdown(shutdown_workers=True)
+
+
+def test_single_vote_controller(prompts,
+                                proposer_worker,
+                                conf_group_size,
+                                conf_threshold,
+                                temperature,
+                                max_tokens,
+                                logprobs_topk,
+                                top_p,
+                                run_type="offline",
+                                **kwargs):
+    generation_controller = NativeGenerationController(
+        sampling_params={
+            "temperature": temperature,
+            "max_tokens": max_tokens,
+            "num_logprobs": logprobs_topk,
+            "top_p": top_p,
+        })
+    DeepConfControllerImpl = _RUN_TYPE_TO_IMPL[run_type]
+    prototype_controller = DeepConfControllerImpl(
+        generation_controller=generation_controller,
+        conf_group_size=conf_group_size,
+        conf_threshold=conf_threshold,
+    )
+    run_scaffolding_llm(prompts, proposer_worker, prototype_controller)
+
+
+def test_majority_vote_controller(prompts,
+                                  proposer_worker,
+                                  conf_group_size,
+                                  conf_threshold,
+                                  logprobs_topk,
+                                  temperature,
+                                  max_tokens,
+                                  top_p,
+                                  sample_num,
+                                  warmup_sample_num,
+                                  vote_policy,
+                                  confidence_percentile,
+                                  run_type="offline_majority_vote",
+                                  **kwargs):
+    generation_controller = NativeGenerationController(
+        sampling_params={
+            "temperature": temperature,
+            "max_tokens": max_tokens,
+            "num_logprobs": logprobs_topk,
+            "top_p": top_p,
+        })
+    DeepConfControllerKwargs = {
+        "generation_controller": generation_controller,
+        "conf_group_size": conf_group_size,
+        "conf_threshold": conf_threshold,
+    }
+    warmup_generation_controller = DeepConfOfflineController(
+        **DeepConfControllerKwargs)
+    final_generation_controller = DeepConfOnlineController(
+        **DeepConfControllerKwargs)
+    DeepConfMajorityVoteControllerImpl = _RUN_TYPE_TO_IMPL[run_type]
+    majority_vote_controller = DeepConfMajorityVoteControllerImpl(
+        generation_controller=warmup_generation_controller,
+        warmup_generation_controller=warmup_generation_controller,
+        final_generation_controller=final_generation_controller,
+        sample_num=sample_num,
+        vote_policy=vote_policy,
+        warmup_sample_num=warmup_sample_num,
+        confidence_percentile=confidence_percentile)
+    run_scaffolding_llm(prompts, proposer_worker, majority_vote_controller)
+
+
+def main():
+    args = parse_arguments()
+    kwargs = {
+        "sample_num": args.sample_num,
+        "conf_group_size": args.conf_group_size,
+        "conf_threshold": args.conf_threshold,
+        "vote_policy": args.vote_policy,
+        "warmup_sample_num": args.warmup_sample_num,
+        "confidence_percentile": args.confidence_percentile,
+        "logprobs_topk": args.logprobs_topk,
+        "max_tokens": args.max_tokens,
+        "temperature": args.temperature,
+        "top_p": args.top_p,
+    }
+
+    prompts = [
+        "Natalia sold clips to 48 of her friends in April, and then she sold half as many clips in May. How many clips did Natalia sell altogether in April and May?\r\n\r\n",
+        "There exist real numbers $x$ and $y$, both greater than 1, such that $\\log_x\\left(y^x\\right)=\\log_y\\left(x^{4y}\\right)=10$. Find $xy$.",
+        "Find the largest possible real part of \\[(75+117i)z+\\frac{96+144i}{z}\\]where $z$ is a complex number with $|z|=4$.",
+    ]
+
+    llm_worker = TRTLLMWorker.init_with_new_llm(
+        args.model_dir,
+        backend="pytorch",
+        max_batch_size=32,
+        max_num_tokens=kwargs.get("max_tokens"),
+    )
+    print(f"init llm worker done")
+
+    if args.run_type == "offline" or args.run_type == "online":
+        test_single_vote_controller(prompts,
+                                    llm_worker,
+                                    run_type=args.run_type,
+                                    **kwargs)
+    elif args.run_type == "offline_majority_vote" or args.run_type == "online_majority_vote":
+        test_majority_vote_controller(prompts,
+                                      llm_worker,
+                                      run_type=args.run_type,
+                                      **kwargs)
+
+    llm_worker.shutdown()
+    print('llm worker shutdown done')
+
+
+if __name__ == "__main__":
+    main()

tensorrt_llm/scaffolding/contrib/DeepConf/__init__.py

@@ -0,0 +1,11 @@
+from .deep_conf_controller import (DeepConfOfflineController,
+                                   DeepConfOfflineMajorityVoteController,
+                                   DeepConfOnlineController,
+                                   DeepConfOnlineMajorityVoteController)
+
+__all__ = [
+    "DeepConfOfflineController",
+    "DeepConfOnlineController",
+    "DeepConfOfflineMajorityVoteController",
+    "DeepConfOnlineMajorityVoteController",
+]