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  • 3.2.0

    • The hb_model_info Tool

    The hb_model_info tool is used to parse the dependencies and parameters of the *.hbm, the *.bc in compilation and the basic information of the *.onnx model, at the same time support the checking of *.bc deletable nodes, and you can view the model structure by starting the webserver.

    hb_mpdel_info_tool

    How to Use

    hb_model_info ${model_file}

    Parameters

    PARAMETERDESCRIPTION
    -h, --helpDisplay help information and exit.
    --versionDisplay version information and exit.
    -n, --nameFollowed by the model name. Specify the desired model when HGM_FILE is a pack model for dumping model compilation information for this specified model.
    -v, --visualizeStart netron server to view the model structure, you can close it with Ctrl+C when you finish viewing.

    Output Contents

    The outputs will be part of the inputs when the model is compiled, as follows:

    Note

    The version number information and other content in the following code block will change with the release package version, and here is only as an example.

    log will be stored in /open_explorer/samples/ai_toolchain/horizon_model_convert_sample/03_classification/03_resnet50/hb_model_info.log
Start hb_model_info....
hb_model_info version 3.3.0
hbm_path: /open_explorer/samples/ai_toolchain/horizon_model_convert_sample/03_classification/03_resnet50/model_output/resnet50_224x224_nv12.hbm
desc file path: resnet50_224x224_nv12_desc.json
************* resnet50_224x224_nv12 *************
############# model deps info #############
builder version     : 3.3.0
hbdk version        : 4.1.2
horizon nn version  : 2.0.5
############# model_parameters info #############
onnx_model         : /open_explorer/samples/ai_toolchain/horizon_model_convert_sample/01_common/model_zoo/mapper/classification/resnet50/resnet50.onnx
BPU march           : nash-e
layer_out_dump      : False
working dir         : /open_explorer/samples/ai_toolchain/horizon_model_convert_sample/03_classification/03_resnet50/model_output
output_model_file_prefix: resnet50_224x224_nv12
node_info           : {}
############# input_parameters info #############
------------------------------------------
---------input info : input  ---------
input_name          : input 
input_type_rt       : nv12
input_space&range   : regular
input_type_train    : rgb
input_layout_train  : NCHW
input_shape         : 1x3x224x224
mean_value          : [123.675, 116.28, 103.53]
scale_value         : [0.01712475, 0.017507, 0.01742919]
separate_batch      : False
---------input info : input end -------
------------------------------------------
############# calibration_parameters info #############
calibration_type    : default
max_percentile      : None
per_channel         : False
cal_data_dir        : /open_explorer/samples/ai_toolchain/horizon_model_convert_sample/03_classification/03_resnet50/calibration_data_rgb
############# compiler_parameters info #############
debug               : True
optimize_level      : O2
compile_mode        : latency
core_num            : 1
balance_factor      : 100
input_source        : {'input': 'pyramid'}
hbm_path: /open_explorer/samples/ai_toolchain/horizon_model_convert_sample/03_classification/03_resnet50/model_output/resnet50_224x224_nv12.hbm
############# Model input/output info #############
NAME   TYPE   SHAPE            DATA_TYPE
------ ------ ---------------- ---------
input_y  input  [1, 224, 224, 1] UINT8
input_uv input  [1, 112, 112, 2] UINT8
output   output [1, 1000]        FLOAT32