使用Docker服务多个Tensorflow模型

Question

看到这个 github问题和这个 stackoverflow帖子后，我希望这会简单地起作用。

似乎传递环境变量MODEL_CONFIG_FILE没有任何影响。我一直在运行，docker-compose但是使用却遇到了同样的问题docker-run。

---

错误：

I tensorflow_serving/model_servers/server.cc:82] Building single TensorFlow model file config:  model_name: model model_base_path: /models/model
I tensorflow_serving/model_servers/server_core.cc:461] Adding/updating models.
I tensorflow_serving/model_servers/server_core.cc:558]  (Re-)adding model: model
E tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:369] FileSystemStoragePathSource encountered a file-system access error: Could not find base path /models/model for servable model

---

Dockerfile

FROM tensorflow/serving:nightly

COPY ./models/first/ /models/first
COPY ./models/second/ /models/second

COPY ./config.conf /config/config.conf

ENV MODEL_CONFIG_FILE=/config/config.conf

---

撰写文件

version: '3'

services:
  serving:
    build: .
    image: testing-models
    container_name: tf

---

配置文件

model_config_list: {
  config: {
    name:  "first",
    base_path:  "/models/first",
    model_platform: "tensorflow",
    model_version_policy: {
        all: {}
    }
  },
  config: {
    name:  "second",
    base_path:  "/models/second",
    model_platform: "tensorflow",
    model_version_policy: {
        all: {}
    }
  }
}

Answer 1

我在 Windows 上遇到了 git bash这个双斜杠问题。

因此，我command在docker-compose.

新的docker-compose看起来像这样并与提供的一起工作dockerfile：

version: '3'

services:
  serving:
    build: .
    image: testing-models
    container_name: tf
    command: --model_config_file=/config/config.conf

Answer 2

没有名为“MODEL_CONFIG_FILE”的 docker 环境变量（这是一个 tensorflow/serving 变量，请参阅 docker 镜像链接），因此docker镜像将仅使用默认的 docker 环境变量（“MODEL_NAME=model”和“MODEL_BASE_PATH=/models”） ，并在 docker 镜像启动时运行模型“/models/model”。“config.conf”应该在“tensorflow/serving”启动时用作输入。尝试运行这样的东西：

docker run -p 8500:8500 8501:8501 \
  --mount type=bind,source=/path/to/models/first/,target=/models/first \
  --mount type=bind,source=/path/to/models/second/,target=/models/second \
  --mount type=bind,source=/path/to/config/config.conf,target=/config/config.conf\
  -t tensorflow/serving --model_config_file=/config/config.conf