# PyTorch-py27 General Template

#### Introduction

AI engine: PyTorch 1.0; Environment: Python 2.7; Input and output mode: undefined mode. 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 PyTorch-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. That is, 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. If the file exists, the file name must be customize_service.py. Only one inference code file can exist in the model folder. For details about how to compile the model inference code file, see Specifications for Compiling 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 according to the engine. For details, see the model package example.
      ├── Custom Python package           //(Optional) User's Python package, which can be directly referenced in the model inference code
      ├── customize_service.py  //(Optional) Model inference code file. The file name must be customize_service.py. Otherwise, the code is not considered as inference code.

#### Model Package Example

Structure of the PyTorch-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 the model inference code
       ├── resnet50.pth           (Mandatory) PyTorch 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.

Parent topic: Template Description