[Lane 2 · kotlin-core] NotImplemented stubs — convTranspose1d for non-FP32 dtypes on CPU
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 76/100
- Issue type
- Bug
- Clarity
- Clearly specified
- Activity status
- Active
- Tech stack
- kotlin
- Domain
- backend, machine-learning
Research direction
Read DefaultCpuOps.convTranspose1d and compare its dtype handling with conv1d; the issue says the current implementation casts every element to Float. Add coverage for FP16 and Int8, then run ./gradlew :skainet-backends:skainet-backend-cpu:jvmTest. Done means non-FP32 inputs compute correctly or fail with a clear dtype error.
Written by the indexing model from the issue text.
Description
Sub-issue of #1414 ([Feature]: Close the remaining NotImplemented stubs outside the operator surface).
Lane: 2 · Kotlin core
Skill needed: Kotlin; CPU kernels.
Size: s (a few hours)
Blocked by: nothing
What to do
DefaultCpuOps.convTranspose1dcasts every elementas Float, so it only works for FP32.- Dispatch on dtype the way
conv1ddoes, with tests for FP16 and Int8 (or document and reject unsupported dtypes explicitly). - Run
./gradlew :skainet-backends:skainet-backend-cpu:jvmTest.
Acceptance
- Non-FP32 inputs either compute correctly or fail with a clear dtype error
- Result reported back on the parent issue
Notes
If something here turns out to be wrong or much bigger than the size label, comment on this issue or open a specific bug instead of blocking the parent.
Coverage matrix: docs/modules/ROOT/pages/reference/ops-status-matrix.adoc · How lanes work: Issue taxonomy
- Dominant language
- Kotlin
- Stars
- 52
- Forks
- 15
- Avg merge
- 1d 2h
- Merged PRs (30d)
- 63
Getting set up
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First steps
- Read the whole issue, then the project's contributing guide.
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