24 lines
1.8 KiB
Markdown
24 lines
1.8 KiB
Markdown
# Import ONNX specifications into ONNF
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The specifications of ONNX are defined under onnx/defs directory in ONNX projects.
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There is a python script onnx/defs/gen_doc.py that automatically generate documents about operations in ONNX (docs/Operations.md).
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ONNF modified this script to import ONNX specifications into ONNF. There are two files generated for ONNF with the modified gen_doc.py:
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1. src/dialect/onnx/onnxop.inc: Operation defintion for MLIR tablegen. Will be included in src/dialect/onnx/onnx.td
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2. src/builder/op_build_table.inc: c code for ONNF frontend to import operation nodes from ONNX model. Will be included in src/builder/frontend_dialect_transformer.cpp
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## How to use the script
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1. Get ONNX. You can use ONNF/third_party/onnx
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2. In your ONNX directory, copy the script docs/gen_doc.py in your ONNF to onnx/defs in ONNX
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3. Run the script: python onnx/defs/gen_doc.py
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4. Two files, onnxop.inc and op_buid_table.inc should be generated in current directory
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5. copy the two file into your ONNF: cp onnxop.inc your_ONNF/src/dialect/onnx/onnxop.inc; cp op_build_table.inc your_ONNF/src/builder
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6. go to your ONNF and build
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## Customization
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In addition to following the ONNF specification, the modified gen_doc.py provides some mechanism for you to customize the output.
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Several tables are defined at the beginning of the script:
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1. special_attr_defaults: gives attribute special default value.
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2. special_op_handler: creates special import function in frontend_dialect_transformer.cpp. Currently special handler is used for operations with oprational arguments
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3. ShapeInferenceList: list of operations which has shape inference defined
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4. CanonicalList : list of operations which has canonical form
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5. manual_code_in_op_def: provides a way to specify any code for an operation in its tablegen
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