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[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

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

coding size:s skill:kotlin-core sub-issue

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

  1. DefaultCpuOps.convTranspose1d casts every element as Float, so it only works for FP32.
  2. Dispatch on dtype the way conv1d does, with tests for FP16 and Int8 (or document and reject unsupported dtypes explicitly).
  3. 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

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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