TensorFlow 1.x - 2.5 English

Vitis AI User Guide (UG1414)

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2.5 English

WeGO-TensorFlow1.x is a sub-project of WeGO, which is designed to improveVitis AI EoU by integrating the Vitis AI toolchain into TensorFlow 1.x framework. Vitis AI 2.5 supports TensorFlow v1.15. The input for WeGO-TensorFlow1.x is the quantized model usually named as quantize_eval_model.pb, which is generated by vai_q_tensorflow. The core WeGO API create_wego_graph() automatically converts the quantized graph into a new TensorFlow graph called as WeGO graph, where the cloud DPU compatible subgraphs are transformed into TensorFlow operator with the kind of VaiWeGOOp.

The whole WeGO-TensorFlow1.x inference can be abstracted into the following for steps

  1. Execute some graph-level optimizations on the original graph to meet DPU-specific requirements.
  2. Traverse the whole graph of the input quantized model and detect nodes which are supported by cloud DPU.
  3. Perform graph auto-partitioning over the quantized graph over the node list detected in step 2.
  4. Transform all cloud DPU compatible subgraphs into new TensorFlow nodes with kind of VaiWeGOOp within the input quantized model.
  5. Return the optimized new WeGO graph and then invoke TensorFlow sess.run() to execute the whole graph.