Documentation

Preparing Dump Data of an Offline Model

Prerequisites

Refer to the ATC Instructions to convert the model and prepare the model file. If model quantization is involved, perform quantization before model conversion. For details, see the AMCT Instructions. In addition, build and run the application project with the generated model file and ensure that the project runs properly.

Generating Dump Data

Perform the following steps to dump data of the offline model:

  1. Open the project file, find the path of the acl.json file in the aclInit() or aclmdlSetDump() call.

    If aclInit() or aclmdlSetDump() is initialized to empty, pass the acl.json path created in Step 2 to the call. The acl.json path is relative to the path of the binary file generated during project build.

  2. Modify the acl.json file in the directory (if the file does not exist, create it in the out directory after project build) and add the dump configuration in the following format.
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    {                                                                                            
	"dump":{                                                                                 
		"dump_list":[                                                                        
			{	"model_name":"ResNet-101"
			},
			{                                                                                
				"model_name":"ResNet-50",
				"layer":[
				      "conv1conv1_relu",
				      "res2a_branch2ares2a_branch2a_relu",
				      "res2a_branch1",
				      "pool1"
				] 
			}  
		],  
		"dump_path":"$HOME/output",
                "dump_mode":"output",
		"dump_op_switch":"off"
	}                                                                                        
}
    The dump configuration rules are as follows:
    • In the sample, the dump, dump_list, and dump_path fields are required, while the model_name, layer, dump_mode, and dump_op_switch fields are optional.
    • To dump all operators of a model, the layer field does not need to be included.
    • To dump certain operators, configure each operator in a line in the layer field and separate them with commas (,).
    • To dump multiple models, add the dump configuration for each model and separate them with commas (,).
    • To dump a single-operator model, leave dump_list empty and set dump_op_switch to on.
    The configuration items are as follows:
    • dump_list: a list of network-wide models for data dump
      • model_name: model name

        To load a model from a file, enter the model file name without the file name extension. You can also set this parameter to the value of the outermost name field in the .json file after ATC-based model conversion. To load a model from memory, set this parameter to the value of the name field in the .json file after model conversion. For details about how to load a model, see " aclprofCreateConfig" in the CANN AscendCL Application Software Development Guide (C&C++).

      • layer: operator name
    • dump_path: dump path in the {dump_path} directory in the operating environment

      Both the absolute path and relative path (relative to the path where the command is run) are supported.

      • An absolute path starts with a slash (/), for example, $HOME/output.
      • If set to a relative path, the path starts with a directory name, for example, output.

      For example, if dump_path is set to $HOME/output, dump data is generated to the $HOME/output directory in the operating environment.

      The directory specified by this parameter must be created in advance and the user configured during installation must have the read and write permissions on the directory.

    • dump_mode: (optional) data dump mode, either input, output (default), or all
      • input: dumps only operator inputs.
      • output: dumps only operator outputs.
      • all: dumps both operator inputs and outputs.
    • dump_op_switch: (optional) dump switch of the single-operator model, either on or off (default)
      • on: enables dump for the single-operator model.
      • off: disables dump for the single-operator model.
    • For TBE and AI CPU operators that do not output results, (for example, StreamActive, Send, Recv, and const), dump data is not generated. For operators that are not executed on AI CPU or AI Core (for example, concatD) after build, dump data cannot be generated.
    • If only certain operators are to be dumped, since the Data operators are not executed on AI CPU or AI Core, you need to select all the downstream operators of the Data operator.
    • When modifying the acl.json file, ensure that each model_name is unique.
    • If the model is loaded from a file, model_name can also be set to the value of the name field in the .json file after model conversion. Model name and operator names can be obtained using either of the following methods:

      If the value of model_name in the acl.json file contains both the model file name and the model name, the model file name takes effect.

  1. Run the application project to generate a dump file.

    Find the generated dump file in {dump_path} in the operating environment. The path and format are described as follows:

    {dump_path}/{time}/{deviceid}/{model_name}/{model_id}/{data_index}/{dump_file}

    For a single-operator model, the dump path is as follows:

    {dump_path}/{deviceid}/{op_name}/{dump file}
    • time: dump time, formatted as YYYYMMDDHHMMSS
    • deviceid: device ID
    • model_name: model name
    • model_id: model ID
    • data_index: execution sequence number of each task, indexed starting at 0. This value is increased by 1 every dump.
    • dump_file: formatted as {op_type}.{op_name}.{taskid}.{timestamp}

    Periods (.), forward slashes (/), backslashes (\), and spaces in model_name, op_type, or op_name are replaced with underscores (_).

Parent topic: Data Preparation