Support for opset 14#239
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Swopper050 wants to merge 5 commits intoAdvancedClimateSystems:developfrom
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Pull Request Overview
This PR adds support for ONNX opset 14 across several operators. Key changes include:
- Addition of version 14 operator constructors and related type constraints for multiple ops (trilu, sub, rnn, relu, mul, lstm, identity, gru, div, cumsum, and add).
- Introduction of a new layout attribute and associated reshape logic in RNN, LSTM, and GRU operators to support batch-first tensor layouts.
- Updates to corresponding test files and documentation to reflect opset 14 support.
Reviewed Changes
Copilot reviewed 25 out of 25 changed files in this pull request and generated 1 comment.
Show a summary per file
| File | Description |
|---|---|
| ops/trilu/* | Added tests and implementation updates for opset 14 support |
| ops/sub/versions.go | Added version 14 operator constructor and type constraints |
| ops/rnn/* | Extended operator and tests with layout support and version 14 |
| ops/relu/versions.go | Added version 14 support and new type constraints |
| ops/mul/versions.go | Added version 14 operator constructor and type constraints |
| ops/lstm/* | Extended operator and tests with layout support and version 14 |
| ops/identity/versions.go | Added version 14 operator constructor |
| ops/gru/* | Extended operator and tests with layout support and version 14 |
| ops/div/versions.go | Added version 14 operator constructor and type constraints |
| ops/cumsum/versions.go | Added version 14 operator constructor |
| ops/add/versions.go | Added version 14 operator constructor and type constraints |
| README.md | Updated documentation to reflect support for opset 14 |
Comments suppressed due to low confidence (2)
ops/rnn/rnn_test.go:407
- Ensure that the package 'math/rand' is imported explicitly in this test file if it is not already, as the use of rand.New requires it.
r := rand.New(rand.NewSource(13))
ops/rnn/rnn.go:111
- Reshaping the input tensor X directly may result in unintended side effects if the original tensor is reused elsewhere. Consider cloning the tensor before reshaping.
err := X.Reshape(seqLength, batchSize, inputSize)
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Closes #216