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Calling @show on Symmetric of a CuArray triggers Scalar Indexing #1294

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simsurace opened this issue Dec 23, 2021 · 3 comments
Closed

Calling @show on Symmetric of a CuArray triggers Scalar Indexing #1294

simsurace opened this issue Dec 23, 2021 · 3 comments
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bug Something isn't working

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@simsurace
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Describe the bug
When using the constructor of Symmetric on a CuArray, displaying the result gives a warning of scalar indexing:

To reproduce
The Minimal Working Example (MWE) for this bug:

using CUDA, LinearAlgebra
CUDA.allowscalar(false)

A = CUDA.randn(4, 4)
@show Symmetric(A)

output:

Error showing value of type Symmetric{Float32, CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}}:
ERROR: Scalar indexing is disallowed.
...
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Expected behavior
Output should be something like this (obtained with CUDA.allowscalar(true)):

Symmetric(A) = Float32[-1.5106043 -0.6005381 -0.30196136 2.218768; -0.6005381 0.38135245 -0.9146352 -0.9448997; -0.30196136 -0.9146352 -1.1485367 -0.090486825; 2.218768 -0.9448997 -0.090486825 -1.2290893]

Version info
Details on Julia:

Julia Version 1.6.4
Commit 35f0c911f4 (2021-11-19 03:54 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-11.0.1 (ORCJIT, skylake)

Details on CUDA:

CUDA toolkit 11.5, artifact installation
NVIDIA driver 465.19.1, for CUDA 11.3
CUDA driver 11.3

Libraries: 
- CUBLAS: 11.7.4
- CURAND: 10.2.7
- CUFFT: 10.6.0
- CUSOLVER: 11.3.2
- CUSPARSE: 11.7.0
- CUPTI: 16.0.0
- NVML: 11.0.0+465.19.1
- CUDNN: 8.30.1 (for CUDA 11.5.0)
- CUTENSOR: 1.3.3 (for CUDA 11.4.0)

Toolchain:
- Julia: 1.6.4
- LLVM: 11.0.1
- PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3, 6.4, 6.5, 7.0
- Device capability support: sm_35, sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75, sm_80

1 device:
  0: NVIDIA GeForce RTX 2070 (sm_75, 6.737 GiB / 7.792 GiB available)

@simsurace simsurace added the bug Something isn't working label Dec 23, 2021
@maleadt
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maleadt commented Dec 24, 2021

That's kind-of expected; there isn't a good way to implement methods for wrapped arrays without covering them all, which is impossible. We try our best, but missing one isn't a bug. If you want, you can add support for Symmetric to Adapt.jl. See JuliaLang/julia#31563 for a potential proper solution.

@maleadt maleadt closed this as completed Dec 24, 2021
@simsurace
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Thanks, I will give Adapt.jl a try.

@simsurace
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See PR #48 in Adapt.jl

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