PyTorch-py37 General Template

Introduction

AI engine: PyTorch 1.0; Environment: Python 3.7; 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 containingSpecifications for Compiling Model Inference Code 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.