[Feature]: Support speculative decoding

benchmark/benchmark_serving.py

@@ -13,14 +13,15 @@ def get_launching_server_cmd(model_path, backend, server_config):
     elif backend == 'sglang':
         cmd = ['python3', '-m', 'sglang.launch_server', '--model-path', model_path]
     elif backend == 'vllm':
-        cmd = ['vllm', 'serve', '--model', model_path]
+        cmd = ['vllm', 'serve', model_path]
     else:
         raise ValueError(f'unknown backend: {backend}')
     for key, value in server_config.items():
         # Convert snake_case to kebab-case for command line args
         key = key.replace('_', '-')
         cmd.append(f'--{key}')
-        cmd.append(str(value))
+        if str(value):
+            cmd.append(str(value))
     # Special handling for proxy server case
     if server_config.get('proxy_url') and server_config.get('dp'):
         cmd.append('--allow-terminate-by-client')
@@ -66,9 +67,9 @@ def get_server_ip_port(backend: str, server_config: Dict) -> Tuple[str, int]:
             server_ip = server_config.get('server_ip', '0.0.0.0')
             server_port = server_config.get('server_port', 23333)
     elif backend == 'sglang':
-        return (server_config.get('server_ip', '0.0.0.0'), server_config.get('server_port', 30000))
+        return (server_config.get('server_ip', '0.0.0.0'), server_config.get('port', 30000))
     elif backend == 'vllm':
-        return (server_config.get('server_ip', '0.0.0.0'), server_config.get('server_port', 8000))
+        return (server_config.get('server_ip', '0.0.0.0'), server_config.get('port', 8000))
     else:
         raise ValueError(f'unknown backend: {backend}')
     return server_ip, server_port
@@ -131,7 +132,7 @@ def benchmark(model_path: str, backend: str, server_config: Dict, data_config: D
 
     try:
 
-        print(f"Starting api_server: {' '.join(server_cmd)}")
+        print(f"Starting api_server: {' '.join(server_cmd)}", flush=True)
         proc = subprocess.Popen(server_cmd)
         # Wait for the server to be ready
         wait_server_ready(server_ip, server_port)

docs/en/advance/spec_decoding.md

@@ -0,0 +1,104 @@
+# Speculative Decoding
+
+Speculative decoding is an optimization technique that introcude a lightweight draft model to propose multiple next tokens and then, the main model verify and choose the longest matched tokens in a forward pass. Compared with standard auto-regressive decoding, this methold lets the system generate multiple tokens at once.
+
+> \[!NOTE\]
+> This is an experimental feature in lmdeploy.
+
+## Examples
+
+Here are some examples.
+
+### Eagle 3
+
+#### Prepare
+
+Install [flash-atten3 ](https://github.com/Dao-AILab/flash-attention?tab=readme-ov-file#flashattention-3-beta-release)
+
+```shell
+git clone --depth=1 https://github.com/Dao-AILab/flash-attention.git
+cd flash-attention/hopper
+python setup.py install
+```
+
+#### pipeline
+
+```python
+from lmdeploy import pipeline, PytorchEngineConfig
+from lmdeploy.messages import SpeculativeConfig
+
+
+if __name__ == '__main__':
+
+    model_path = 'meta-llama/Llama-3.1-8B-Instruct'
+    spec_cfg = SpeculativeConfig(method='eagle3',
+                                    num_speculative_tokens=3,
+                                    model='yuhuili/EAGLE3-LLaMA3.1-Instruct-8B',
+                                    )
+    pipe = pipeline(model_path,
+                    backend_config=PytorchEngineConfig(max_batch_size=128),
+                    speculative_config=spec_cfg)
+    response = pipe(['Hi, pls intro yourself', 'Shanghai is'])
+    print(response)
+```
+
+### serving
+
+```shell
+lmdeploy serve api_server \
+meta-llama/Llama-3.1-8B-Instruct \
+--backend pytorch \
+--server-port 24545 \
+--speculative-draft-model yuhuili/EAGLE3-LLaMA3.1-Instruct-8B \
+--speculative-algorithm eagle3 \
+--speculative-num-draft-tokens 3 \
+--max-batch-size 128 \
+--enable-metrics
+```
+
+### Deepseek MTP
+
+#### Prepare
+
+Install [FlashMLA](https://github.com/deepseek-ai/FlashMLA?tab=readme-ov-file#installation)
+
+```shell
+git clone https://github.com/deepseek-ai/FlashMLA.git flash-mla
+cd flash-mla
+git submodule update --init --recursive
+pip install -v .
+```
+
+#### pipeline
+
+```python
+from lmdeploy import pipeline, PytorchEngineConfig
+from lmdeploy.messages import SpeculativeConfig
+
+
+if __name__ == '__main__':
+
+    model_path = 'deepseek-ai/DeepSeek-V3'
+    spec_cfg = SpeculativeConfig(method='deepseek_mtp',
+                                    num_speculative_tokens=3,
+                                    )
+    pipe = pipeline(model_path,
+                    backend_config=PytorchEngineConfig(tp=16, max_batch_size=128),
+                    speculative_config=spec_cfg)
+    response = pipe(['Hi, pls intro yourself', 'Shanghai is'])
+    print(response)
+```
+
+### serving
+
+```shell
+lmdeploy serve api_server \
+deepseek-ai/DeepSeek-V3 \
+--backend pytorch \
+--server-port 24545 \
+--tp 16 \
+--speculative-algorithm deepseek_mtp \
+--speculative-num-draft-tokens 3 \
+--max-batch-size 128 \
+--enable-metrics
+```

docs/en/index.rst

@@ -103,6 +103,7 @@ Documentation
    advance/pytorch_multinodes.md
    advance/pytorch_profiling.md
    advance/metrics.md
+   advance/spec_decoding.md
 
 .. toctree::
    :maxdepth: 1

docs/zh_cn/advance/spec_decoding.md

@@ -0,0 +1,104 @@
+# Speculative Decoding
+
+推测解码是一种优化技术，它通过引入轻量级草稿模型来预测多个后续token，再由主模型在前向推理过程中验证并选择匹配度最高的长token序列。与标准的自回归解码相比，这种方法可使系统一次性生成多个token。
+
+> \[!NOTE\]
+> 请注意，这是lmdeploy中的实验性功能。
+
+## 示例
+
+请参考如下使用示例。
+
+### Eagle 3
+
+#### 安装依赖
+
+安装 [flash-atten3 ](https://github.com/Dao-AILab/flash-attention?tab=readme-ov-file#flashattention-3-beta-release)
+
+```shell
+git clone --depth=1 https://github.com/Dao-AILab/flash-attention.git
+cd flash-attention/hopper
+python setup.py install
+```
+
+#### pipeline
+
+```python
+from lmdeploy import pipeline, PytorchEngineConfig
+from lmdeploy.messages import SpeculativeConfig
+
+
+if __name__ == '__main__':
+
+    model_path = 'meta-llama/Llama-3.1-8B-Instruct'
+    spec_cfg = SpeculativeConfig(method='eagle3',
+                                    num_speculative_tokens=3,
+                                    model='yuhuili/EAGLE3-LLaMA3.1-Instruct-8B',
+                                    )
+    pipe = pipeline(model_path,
+                    backend_config=PytorchEngineConfig(max_batch_size=128),
+                    speculative_config=spec_cfg)
+    response = pipe(['Hi, pls intro yourself', 'Shanghai is'])
+    print(response)
+```
+
+### serving
+
+```shell
+lmdeploy serve api_server \
+meta-llama/Llama-3.1-8B-Instruct \
+--backend pytorch \
+--server-port 24545 \
+--speculative-draft-model yuhuili/EAGLE3-LLaMA3.1-Instruct-8B \
+--speculative-algorithm eagle3 \
+--speculative-num-draft-tokens 3 \
+--max-batch-size 128 \
+--enable-metrics
+```
+
+### Deepseek MTP
+
+#### 安装依赖
+
+Install [FlashMLA](https://github.com/deepseek-ai/FlashMLA?tab=readme-ov-file#installation)
+
+```shell
+git clone https://github.com/deepseek-ai/FlashMLA.git flash-mla
+cd flash-mla
+git submodule update --init --recursive
+pip install -v .
+```
+
+#### pipeline
+
+```python
+from lmdeploy import pipeline, PytorchEngineConfig
+from lmdeploy.messages import SpeculativeConfig
+
+
+if __name__ == '__main__':
+
+    model_path = 'deepseek-ai/DeepSeek-V3'
+    spec_cfg = SpeculativeConfig(method='deepseek_mtp',
+                                    num_speculative_tokens=3,
+                                    )
+    pipe = pipeline(model_path,
+                    backend_config=PytorchEngineConfig(tp=16, max_batch_size=128),
+                    speculative_config=spec_cfg)
+    response = pipe(['Hi, pls intro yourself', 'Shanghai is'])
+    print(response)
+```
+
+### serving
+
+```shell
+lmdeploy serve api_server \
+deepseek-ai/DeepSeek-V3 \
+--backend pytorch \
+--server-port 24545 \
+--tp 16 \
+--speculative-algorithm deepseek_mtp \
+--speculative-num-draft-tokens 3 \
+--max-batch-size 128 \
+--enable-metrics
+```

docs/zh_cn/index.rst

@@ -104,6 +104,7 @@ LMDeploy 工具箱提供以下核心功能：
    advance/pytorch_multinodes.md
    advance/pytorch_profiling.md
    advance/metrics.md
+   advance/spec_decoding.md
 
 .. toctree::
    :maxdepth: 1

lmdeploy/api.py

@@ -3,7 +3,7 @@
 from typing import List, Literal, Optional, Union
 
 from .archs import autoget_backend_config, get_task
-from .messages import PytorchEngineConfig, TurbomindEngineConfig
+from .messages import PytorchEngineConfig, SpeculativeConfig, TurbomindEngineConfig
 from .model import ChatTemplateConfig
 
 
@@ -12,6 +12,7 @@ def pipeline(model_path: str,
              chat_template_config: Optional[ChatTemplateConfig] = None,
              log_level: str = 'WARNING',
              max_log_len: int = None,
+             speculative_config: SpeculativeConfig = None,
              **kwargs):
     """
     Args:
@@ -68,6 +69,12 @@ def pipeline(model_path: str,
             if backend_config is not None else None
         model_path = get_model(model_path, download_dir, revision)
 
+    # spec model
+    if speculative_config is not None and speculative_config.model and not os.path.exists(speculative_config.model):
+        download_dir = backend_config.download_dir \
+            if backend_config is not None else None
+        speculative_config.model = get_model(speculative_config.model, download_dir)
+
     _, pipeline_class = get_task(model_path)
     if not isinstance(backend_config, PytorchEngineConfig):
         # set auto backend mode
@@ -80,6 +87,7 @@ def pipeline(model_path: str,
                           backend_config=backend_config,
                           chat_template_config=chat_template_config,
                           max_log_len=max_log_len,
+                          speculative_config=speculative_config,
                           **kwargs)
 
 

lmdeploy/cli/cli.py

@@ -3,7 +3,8 @@
 import os
 
 from ..version import __version__
-from .utils import ArgumentHelper, DefaultsAndTypesHelpFormatter, FlexibleArgumentParser, convert_args
+from .utils import (ArgumentHelper, DefaultsAndTypesHelpFormatter, FlexibleArgumentParser, convert_args,
+                    get_speculative_config)
 
 
 class CLI(object):
@@ -44,12 +45,12 @@ def add_parser_chat():
                             ', "baichuan-inc/baichuan2-7b-chat" and so on')
         # common args
         ArgumentHelper.backend(parser)
-        # # chat template args
+        # chat template args
         ArgumentHelper.chat_template(parser)
         # model args
         ArgumentHelper.revision(parser)
         ArgumentHelper.download_dir(parser)
-        #
+
         # pytorch engine args
         pt_group = parser.add_argument_group('PyTorch engine arguments')
         ArgumentHelper.adapters(pt_group)
@@ -77,6 +78,9 @@ def add_parser_chat():
         ArgumentHelper.rope_scaling_factor(tb_group)
         ArgumentHelper.communicator(tb_group)
 
+        # speculative decoding
+        ArgumentHelper.add_spec_group(parser)
+
     @staticmethod
     def add_parser_checkenv():
         """Add parser for check_env command."""
@@ -168,7 +172,13 @@ def get_gpu_topo():
     @staticmethod
     def chat(args):
         from .chat import main
+
         kwargs = convert_args(args)
+        speculative_config = get_speculative_config(args)
+        to_remove = ['speculative_algorithm', 'speculative_draft_model', 'speculative_num_draft_tokens']
+        for key in to_remove:
+            kwargs.pop(key)
+        kwargs['speculative_config'] = speculative_config
         main(**kwargs)
 
     @staticmethod