init
Function Usage
Initializes AMCT, saves the quantization factor record file, and parses the user model into a graph that can be used for the quantize_model and save_model calls.
Prototype
graph = init(config_file, model_file, weights_file, scale_offset_record_file)
Command-line options
Option |
Input/Return |
Description |
Restriction |
|---|---|---|---|
config_file |
Input |
Quantization configuration file generated by the user. |
A string |
model_file |
Input |
Caffe model definition file (.prototxt), the same as model_file passed to the create_quant_config call. |
A string Restriction: For layers for inference, the settings in LayerParameter in model_file must meet inference requirements. For example, use_global_stats of the BatchNorm layer must be set to 1. |
weights_file |
Input |
Already-trained Caffe model file (.caffemodel), the same as weights_file passed to the create_quant_config call. |
A string |
scale_offset_record_file |
Input |
Path of the file that stores quantization factors. If the file exists in the path, it will be overwritten. |
A string |
graph |
Returns |
Graph structure parsed from the user model. |
An AMCT-defined Graph. |
Returns
graph: graph structure parsed from the user model.
Outputs
A quantization factor record file (scale_offset_record_file).
When quantization is performed again, the preceding file output by the API will be overwritten.
Examples
1 2 3 4 5 6 | from amct_caffe import init Initializing the Tool graph = init(config_file="./configs/config.json", model_file="./pretrained_model/model.prototxt", weights_file="./pretrained_model/model.caffemodel", scale_offset_record_file="./recording.txt") |