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Minutes_2019_07_30

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Siu Kwan Lam edited this page Aug 13, 2019 · 1 revision

Attendees: Ehsan, Pearu, Stuart, Val, Stan, Siu, Todd, James

0. Feature Discussion

1. New issues

  • #4380 - numba fails to be imported in Termux
  • #4378 - CUDA flag to emulate -fdefault-real-*/force e.g. float32 throughout
    • good idea. Not sure how to implement this.
    • what should the scope of this be? Change typing of constants and getitem on containers?
    • maybe most of the problem is literals?
    • omg numpy cast rules 🤯 (float32 * 2 -> float64, float32[:] * 2 -> float32??)
  • **** #4377 - Update Py2.7 EOL statement.
    • Stan will update based on discussion
    • Numba 0.47 will be last Python 2.7 release
    • Need to update docs and sunsetting website PR
  • **** #4370 - Appending a Python int to a Numba typed list (of type np.intp) raises an error.
    • need to reject unsupported types (numpy dtypes not currently accepted)
    • should we accept NumPy dtypes as if they were Numba scalar types?
      • not yet
    • advertise public APIs for simplified creation of Numba types
    • should make numba.typeof more fancy to construct nested container types?
      • yes, type by example
    • TODO: work on delcarative type first
  • #4369 - NamedTuple.__init__ hangs with second argument as literal
    • need to strengthen type checking so that it rejects incorrect usage
  • #4368 - alloc-dealloc-mismatch on import
    • likely know cause
    • open PR on llvmlite to fix
  • #4367 - Numba could not be imported
    • still working with user
  • #4365 - Header in documentation cuts off the top of the page sometimes
    • open PR to fix
  • #4364 - typed Dict slower than array with custom dtype
    • hash table lookup are slow
    • user workaround is to manually cache dict lookup outside loop if that is appropriate to their problem
  • #4362 - [FEA] NVIDIA Jetson SoC (TX2, Xavier, Nano) Failure to Zero-Copy from CPU to GPU with numba.cuda.to_device()
    • direct people to pluggable allocator issue
  • #4358 - Meta issue: np1.17 fixes
    • review in progress
  • #4356 - getting the IR for library functions
    • answered user clarifying what Numba does
  • #4355 - typed-list: expose a view for numpy arrays
    • interesting idea, not high priority
  • #4352 - RAPIDS RMM + Numba Integration: context.deallocations is NoneType
    • PR ready to merge
  • #4351 - Errors with Cuda Memory Management (I suppose)
    • Still suspicious this is a watchdog problem
    • Maybe out of bounds error?

Already Closed

  • #4379 - windows 10, Ryzen1800X cpu, python ver 3.7 numba error
  • #4360 - Unsupported context manager in use
  • #4359 - Spurious logging messages

2. Open PRs

  • #4376 - [WIP] add np's flip functionality
  • #4375 - Add docstrings to inspect methods
    • needs review
  • #4374 - np.alen
  • #4373 - Set maximum name size to maximum allowable value
  • #4372 - Replace all "except BaseException" with "except Exception".
  • #4371 - Fix nump1.17 random function non-aliasing
  • #4366 - Offset search box to avoid wrapping on some pages with Safari. Fixes #4365.
  • #4363 - Fix np.interp for np1.17 nan handling
    • minor review suggestions to fix
  • #4361 - Add allocation hoisting info to LICM section at diagnostic L4
    • ready for review (5 seconds or less)
  • #4357 - Fix np1.17 isnan, isinf, isfinite ufuncs
    • minor review suggestions to fix
  • #4354 - Try to fix #4352.
    • ready to merge
  • #4353 - [WIP] Inspection tool to check what numba supports

Already merged

4. Next Release: Version 0.45.1, Final=August 2

  • bug fixes

  • Priorities for 0.46 - Target late Sept - 2) Rewrite passes - 3) Fix exception handling - (as time allows) Start work on new Numba IR implementation - Historical IR implementation is an object graph that do not make creating rewrite passes easy, and easy to create an inconsistent state. No "rollback" option. - Goal is create a new data structure that can solve these limitations. - Need to be able to round-trip between new IR container and old-style container so that existing rewrite passes will continue to work. - Need to prepare by refactoring existing rewrite passes to make them more amenable to a new IR representation. - Also need to document "best practices" for creating IR so that contributors will avoid known bad practices. (i.e Inline-closure-pass) - experimental repo for the new container: https://github.com/sklam/etude-okvmap - 1) Continuing on caching: - Catching transitive dependencies - More unusual cases (mixed mode, function parameters, etc) - New CI system!!!!!!!! - (proposal) Declarative typing option for @overload/@overload_method

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