fix and doc:

- fix tune attribute error
- add chinese llava doc

docs/zh_cn/multi_modal/llava.md

@@ -1,3 +1,135 @@
 # LLaVA
 
-TODO
+LMDeploy 支持以下 LLaVA 系列模型，具体如下表所示：
+
+|                 模型                 | 大小 |   支持的推理引擎   |
+| :----------------------------------: | :--: | :----------------: |
+| llava-hf/Llava-interleave-qwen-7b-hf |  7B  | TurboMind, PyTorch |
+|       llava-hf/llava-1.5-7b-hf       |  7B  | TurboMind, PyTorch |
+|   liuhaotian/llava-v1.6-vicuna-7b    |  7B  | TurboMind, PyTorch |
+|   liuhaotian/llava-v1.6-mistral-7b   |  7B  | TurboMind, PyTorch |
+
+接下来的章节将演示如何使用 LMDeploy 部署 LLaVA 模型，并以 [llava-hf/llava-interleave](https://huggingface.co/llava-hf/llava-interleave-qwen-7b-hf) 为例。
+
+## 安装
+
+请按照[安装指南](../get_started/installation.md)安装 LMDeploy。
+
+或者，您也可以使用官方的 Docker 镜像：
+
+```shell
+docker pull openmmlab/lmdeploy:latest
+```
+
+## 离线推理
+
+以下示例代码展示了 VLM pipeline 的基本用法。有关详细信息，请参考 [VLM 离线推理流程](./vl_pipeline.md)。
+
+```python
+from lmdeploy import GenerationConfig, TurbomindEngineConfig, pipeline
+from lmdeploy.vl import load_image
+
+pipe = pipeline("llava-hf/llava-interleave-qwen-7b-hf", backend_config=TurbomindEngineConfig(cache_max_entry_count=0.5),
+    gen_config=GenerationConfig(max_new_tokens=512))
+
+image = load_image('https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg')
+prompt = 'Describe the image.'
+print(f'prompt:{prompt}')
+response = pipe((prompt, image))
+print(response)
+```
+
+更多示例：
+
+<details>
+  <summary><b>多图片多轮对话，组合图片</b></summary>
+
+```python
+from lmdeploy import pipeline, GenerationConfig
+
+pipe = pipeline('llava-hf/llava-interleave-qwen-7b-hf', log_level='INFO')
+messages = [
+    dict(role='user', content=[
+        dict(type='text', text='Describe the two images in detail.'),
+        dict(type='image_url', image_url=dict(url='https://raw.githubusercontent.com/QwenLM/Qwen-VL/master/assets/mm_tutorial/Beijing_Small.jpeg')),
+        dict(type='image_url', image_url=dict(url='https://raw.githubusercontent.com/QwenLM/Qwen-VL/master/assets/mm_tutorial/Chongqing_Small.jpeg'))
+    ])
+]
+out = pipe(messages, gen_config=GenerationConfig(top_k=1))
+
+messages.append(dict(role='assistant', content=out.text))
+messages.append(dict(role='user', content='What are the similarities and differences between these two images.'))
+out = pipe(messages, gen_config=GenerationConfig(top_k=1))
+```
+
+</details>
+
+## 在线服务
+
+可以使用 `lmdeploy serve api_server` CLI 启动服务器：
+
+```shell
+lmdeploy serve api_server llava-hf/llava-interleave-qwen-7b-hf
+```
+
+或者，使用前面提到的 Docker 镜像启动服务：
+
+```shell
+docker run --runtime nvidia --gpus all \
+    -v ~/.cache/huggingface:/root/.cache/huggingface \
+    --env "HUGGING_FACE_HUB_TOKEN=<secret>" \
+    -p 23333:23333 \
+    --ipc=host \
+    openmmlab/lmdeploy:latest \
+    lmdeploy serve api_server llava-hf/llava-interleave-qwen-7b-hf
+```
+
+采用 Docker Compose 部署也是一种常见选择。在 lmdeploy 项目的根目录创建 `docker-compose.yml` 文件，如下：
+
+```yaml
+version: '3.5'
+
+services:
+  lmdeploy:
+    container_name: lmdeploy
+    image: openmmlab/lmdeploy:latest
+    ports:
+      - "23333:23333"
+    environment:
+      HUGGING_FACE_HUB_TOKEN: <secret>
+    volumes:
+      - ~/.cache/huggingface:/root/.cache/huggingface
+    stdin_open: true
+    tty: true
+    ipc: host
+    command: lmdeploy serve api_server llava-hf/llava-interleave-qwen-7b-hf
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: "all"
+              capabilities: [gpu]
+```
+
+然后，可以执行以下命令启动服务：
+
+```shell
+docker-compose up -d
+```
+
+当运行 `docker logs -f lmdeploy` 后看到如下日志，说明服务启动成功：
+
+```text
+HINT:    Please open  http://0.0.0.0:23333   in a browser for detailed api usage!!!
+HINT:    Please open  http://0.0.0.0:23333   in a browser for detailed api usage!!!
+HINT:    Please open  http://0.0.0.0:23333   in a browser for detailed api usage!!!
+INFO:     Started server process [2439]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     Uvicorn running on  http://0.0.0.0:23333  (Press CTRL+C to quit)
+```
+
+可以通过 `lmdeploy serve api_server -h` 查看 `lmdeploy serve api_server` 的参数详情。
+
+关于 `api_server` 以及如何访问服务的更多信息可以在[这里](api_server_vl.md)找到。

lmdeploy/turbomind/generate_gemm_config.py

@@ -54,19 +54,14 @@ def main(head_num: int = 32,
             from transformers import AutoConfig
             config = AutoConfig.from_pretrained(model_path,
                                                 trust_remote_code=True)
-            try:
-                head_num = config.num_attention_heads
-                size_per_head = config.hidden_size // head_num
-                inter_size = config.intermediate_size
-                vocab_size = config.vocab_size
-            except AttributeError:
-                for key in ['language_config', 'llm_config', 'text_config']:
-                    config = getattr(config, key, config)
-
-                head_num = config.num_attention_heads
-                size_per_head = config.hidden_size // head_num
-                inter_size = config.intermediate_size
-                vocab_size = config.vocab_size
+
+            for key in ['language_config', 'llm_config', 'text_config']:
+                config = getattr(config, key, config)
+            head_num = config.num_attention_heads
+            size_per_head = config.hidden_size // head_num
+            inter_size = config.intermediate_size
+            vocab_size = config.vocab_size
+
     for bsz in range(1, max_batch_size + 1):
         subprocess.call(
             f'{get_llama_gemm()} {bsz} 1 1 {head_num} {size_per_head}'

lmdeploy/turbomind/supported_models.py

@@ -98,6 +98,9 @@ def _is_head_dim_supported(cfg):
                 # internvl2-4b,internlm2-1b are not working yet
                 support_by_turbomind = _is_head_dim_supported(cfg.llm_config)
             elif arch == 'LlavaForConditionalGeneration':
-                support_by_turbomind = _is_head_dim_supported(cfg.text_config)
+                sub_arch = cfg.text_config.architectures[0]
+                if sub_arch in ['Qwen2ForCausalLM', 'LlamaForCausalLM']:
+                    support_by_turbomind = _is_head_dim_supported(
+                        cfg.text_config)
 
     return support_by_turbomind