4.1.2. PTQ Tools Guide

The purpose of this section is to introduce the toolkit of the PTQ model conversion scheme provided by the D-Robotics X3 algorithm toolchain.

Tip

It is recommended that you finish the following preparations before reading this section:

1. Read Toolchain Overview about the PTQ and PTQ Principle and Steps to understand the PTQ scheme and model conversion steps.

2. Complete the Docker environment installation and configuration as well as the image pulling according to Docker Container Deployment.

3. Run the model conversion related to the samples described in PTQ Model Conversion Samples Guide.

This section introduces the model conversion toolkit for the D-Robotics PTQ scheme.

The toolkit can be run on a development PC or in a Docker environment.

If you choose to run the toolkit on your development PC, you should run install.sh under ddk/package/host in the horizon_xj3_open_explorer installation package to install the toolkit. Once the installation is complete, run hb_mapper --help to verify the installation.

If you choose to run the toolkit in a Docker container, the above installation steps are not required.

Follow Docker Container Deployment to install the toolkit. Enter the Docker container and run hb_mapper --help to verify the installation.

The following sections will describe the model conversion process and the use of the tools in the toolkit.

• 4.1.2.1. Model Conversion Process
  • 4.1.2.1.1. Model Checking (hb_mapper checker)
  • 4.1.2.1.2. Calibration Image Preparation
  • 4.1.2.1.3. Model Conversion (hb_mapper makertbin)
  • 4.1.2.1.4. Single Image Inference
  • 4.1.2.1.5. Model Accuracy Evaluations
  • 4.1.2.1.6. Model Performance Evaluations
  • 4.1.2.1.7. [Reference] Supported Calibration Methods
  • 4.1.2.1.8. [Reference] OP List
• 4.1.2.2. The hb_mapper Tools
  • 4.1.2.2.1. Model Checking Tool (hb_mapper checker)
  • 4.1.2.2.2. Model Compiling Tool (hb_mapper makertbin)
  • 4.1.2.2.3. Inference Tool (hb_mapper infer)
  • 4.1.2.2.4. Key Configuration Parameter (calibration_parameters.preprocess_on)
  • 4.1.2.2.5. Configuration File Reference Example
    • 4.1.2.2.5.1. Reference and Descriptions
    • 4.1.2.2.5.2. About input_type_rt/ input_type_train
• 4.1.2.3. The hb_perf Tool
  • 4.1.2.3.1. How to Use
  • 4.1.2.3.2. Parameters
  • 4.1.2.3.3. Output Contents
• 4.1.2.4. The vec_diff Tool
  • 4.1.2.4.1. How to Use
  • 4.1.2.4.2. Parameters
  • 4.1.2.4.3. Output Contents
• 4.1.2.5. The hb_model_info Tool
  • 4.1.2.5.1. How to Use
  • 4.1.2.5.2. Parameters
  • 4.1.2.5.3. Output Contents
• 4.1.2.6. The hb_pack Tool
  • 4.1.2.6.1. How to Use
  • 4.1.2.6.2. Parameters
  • 4.1.2.6.3. Output Contents
• 4.1.2.7. The hb_verifier Tool
  • 4.1.2.7.1. How to Use
  • 4.1.2.7.2. Parameters
  • 4.1.2.7.3. Examples of Reference Usage
  • 4.1.2.7.4. Description of the Output Content
• 4.1.2.8. The hb_model_modifier Tool
  • 4.1.2.8.1. How to Use
  • 4.1.2.8.2. Parameters
  • 4.1.2.8.3. Output Contents
• 4.1.2.9. The hb_custom_op Tool
  • 4.1.2.9.1. How to Use
  • 4.1.2.9.2. Parameters
  • 4.1.2.9.3. Output Contents
• 4.1.2.10. The hb_eval_preprocess Tool
  • 4.1.2.10.1. How to Use
  • 4.1.2.10.2. Parameters
  • 4.1.2.10.3. Output Contents
• 4.1.2.11. The HB_ONNXRuntime Inference Library
  • 4.1.2.11.1. How to Use
  • 4.1.2.11.2. Parameters
• 4.1.2.12. Accuracy Debug Tool
  • 4.1.2.12.1. Quickstart
    • 4.1.2.12.1.1. Calibration Models and Data Storage
    • 4.1.2.12.1.2. Accuracy Debug Module Import and Usage
    • 4.1.2.12.1.3. Analysis Result Display
  • 4.1.2.12.2. Function Description
    • 4.1.2.12.2.1. get_sensitivity_of_nodes
    • 4.1.2.12.2.2. plot_acc_error
    • 4.1.2.12.2.3. plot_distribution
    • 4.1.2.12.2.4. get_channelwise_data_distribution
    • 4.1.2.12.2.5. sensitivity_analysis
    • 4.1.2.12.2.6. runall