Core Python APIs - 3.5 English

Vitis AI User Guide (UG1414)

Document ID
Release Date
3.5 English
Table 1. get_target_info()
Description Parameters Return
Gets target information including batch, fingerprint, and target name. You can use info for batching or get target name information. None A DeviceInfo object. For more details about this object type, see the core classes section.
Table 2. create_wego_graph(input_graph_def, feed_dict={}, accuracy_mode= vitis_vai.enums.AccuracyMode.Default)
Description Parameters Return
Python wrapper for the VAI transformation.
  1. input_graph_def: GraphDef object containing a model to be transformed.
  2. feed_dict: Infer shape configuration when input model without fixed input shape.
  3. accuracy_mode:
    • vitis_vai.enums.AccuracyMode.Default: Running without CPU FixNeuron.
    • vitis_vai.enums.AccuracyMode.ReserveReduantFixNeurons: Running with CPU FixNeruon
New GraphDef with VaiWeGOOps placed in graph replacing subgraphs.
Note: WeGO eliminates CPU FixNeurons operators within a quantized model to achieve optimal performance by default. However, for those models containing many CPU FixNeurons operators, their accuracy might decrease by deploying them with the default value(Vitis_vai.enums.AccuracyMode.Default).In such cases, you can switch to Vitis_vai.enums.AccuracyMode.ReserveReduantFixNeurons to achieve better accuracy.