The corresponding Vitis AI compiler for Caffe and TensorFlow frameworks are vai_c_caffe, vai_c_tensorflow, vai_c_tensorflow2, and vai_c_xir across Cloud-to-Edge DPU. The common options for VAI_C are illustrated in the following table.
Parameters | Description |
---|---|
--arch | The DPU architecture configuration file for the VAI_C compiler in JSON format. For pre-built DPU xclbins in Vitis AI releases, you can find the corresponding arch.json file in Vitis AI docker (/opt/vitis_ai/compiler/arch). The contents should be something like {"target": "DPUCZDX8G_ISA0_B4096_MAX_BG2"}. For customized DPU IPs, the corresponding arch.json files are generated by the DPU TRD along with the DPU IPs. The contents should be something like {“fingerprint”:"0x1000000f7014407"}. The fingerprint is a 64-bit digital signature to identify a DPU target. It consists of 1 byte to indicate the DPU type, 1 byte to indicate the ISA version, and 6 bytes to indicate specific configurations. The fingerprint is unique to each DPU configuration and runtime relies on it to identify DPU instance running on the current platform and to verify that the model is compiled for the same DPU target. "DPUCZDX8G_ISA0_B4096_MAX_BG2" is an alias for a specific fingerprint which is pre-defined in the compiler. |
--output_dir | Path of output directory for vai_c_caffe and vai_c_tensorflow after compilation process. |
--net_name | Name of DPU kernel for network model after compiled by VAI_C. |
--options | The list for the extra options in the format of 'key':'value'. If
there are multiple options to be specified, they are separated by
‘,’. Use --options '{"input_shape": "1,224,224,3"}' to specify input shape manually. Use --options '{"plugins": "plugin0,plugin1"}' to specify plugin libraries. Use --options '{"output_ops": "op_name0,op_name1"}' to specify output ops Note: Arguments specified with “--options”
have the highest priorities and will override the values
specified in other places.
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