Caffe-GPU-py27 General Template¶
Introduction¶
AI engine: GPU-based Caffe 1.0; Environment: Python 2.7; Input and output mode: Undefined. Select an appropriate input and output mode based on the model function or application scenario. When using the template to import a model, select the model directory containing the model files.
Template Input¶
The template input is the Caffe-based model package stored on OBS. Ensure that the OBS directory you use and ModelArts are in the same region. For details about model package requirements, see Model Package Example.
Input and Output Mode¶
Undefined Mode can be overwritten. You can select another input and output mode during model creation.
Model Package Specifications¶
The model package must be stored in the OBS folder named model. Model files and the model inference code file are stored in the model folder.
The model inference code file is optional, but if there is one, it must be named customize_service.py. There can only be one such file in the model folder. For details about how to write model inference code, see Specifications for Writing Model Inference Code.
The structure of the model package imported using the template is as follows:
model/ │ ├── Model file //(Mandatory) The model file format varies depending on the engine. For details, see the model package example. ├── Custom Python package //(Optional) Your Python package, which can be directly referenced in model inference code ├── customize_service.py //(Optional) Model inference code file. The file name must be customize_service.py, otherwise it will not be recognized.
Model Package Example¶
Structure of the Caffe-based model package
When publishing the model, you only need to specify the model directory.
OBS bucket/directory name
|── model (Mandatory) The folder must be named model and is used to store model-related files.
|── <<Custom Python package>> (Optional) User's Python package, which can be directly referenced in model inference code
|── deploy.prototxt (Mandatory) Caffe model file, which contains information such as the model network structure
|── resnet.caffemodel (Mandatory) Caffe model file, which contains variable and weight information
|── customize_service.py (Optional) Model inference code file. The file must be named customize_service.py. Only one inference code file exists. The .py file on which customize_service.py depends can be directly put in the model directory.