[RELAX][ONNX][FIX] add a parser to handle expression in the shape dim names #17505
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expressions such as past_sequence_length + sequence_length where each variable becomes a tvm.tir.SizeVar
updated binary base to completely unpack relax.PrimValue if it contains tir.IntImm or tir.FloatImm added regression tests
Hzfengsy
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Nov 10, 2024
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Thanks for the improvements |
PatrikPerssonInceptron
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ShiboXing
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Aug 10, 2025
… names (apache#17505) * added a simple parser that can handle onnx variable names containing expressions such as past_sequence_length + sequence_length where each variable becomes a tvm.tir.SizeVar * added doc strings updated binary base to completely unpack relax.PrimValue if it contains tir.IntImm or tir.FloatImm added regression tests * updated formatting
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Problem
The shape names in an ONNX model can contain expressions such as the shape
int64[batch_size,past_sequence_length + sequence_length]of the attention mask of an LLM. In this case, the second dimension contains an expressionpast_sequence_length + sequence_lengthwherepast_sequence_lengthandsequence_lengthshould be individual variables added together. However, currently, a new variable named"past_sequence_length + sequence_length"is instead created when translating the graph.Fix
I added a simple parser that creates individual size variables for the variable names and generates the resulting prim expression. Note, in order to keep the parser simple, it evaluates expressions left to right. Not accounting for operator precedence.
Test
I added regression tests to verify that the onnx shape dim expression are evaluated correctly.
Additional small fixes
In the case when PrimValues are encountered in the BinaryBase, they are not always fully extracted before turning them into numpy arrays. I added an additional check that extracts the value from IntImm and FloatImm types before converting them to numpy arrays.