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Enzyme.make_zero
Describe the bug
Enzyme.make_zero(CuArray) doesn't create a new array of the same shape filled with zeros, but instead returns the same array.
Enzyme.make_zero(CuArray)
To reproduce
The Minimal Working Example (MWE) for this bug:
julia> using CUDA, Enzyme julia> A = CUDA.rand(1) 1-element CuArray{Float32, 1, CUDA.DeviceMemory}: 0.068770334 julia> make_zero(A) == A true julia> B = rand(1) 1-element Vector{Float64}: 0.12168917809683022 julia> make_zero(B) == B false
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Expected behavior
make_zero should return the zero-initialised copy of the CUDA device array.
make_zero
Version info
Details on Julia:
Julia Version 1.11.2 Commit 5e9a32e7af2 (2024-12-01 20:02 UTC) Build Info: Official https://julialang.org/ release Platform Info: OS: Linux (x86_64-linux-gnu) CPU: 32 × AMD EPYC 7282 16-Core Processor WORD_SIZE: 64 LLVM: libLLVM-16.0.6 (ORCJIT, znver2) Threads: 4 default, 0 interactive, 2 GC (on 32 virtual cores) Environment: JULIA_HDF5_PATH = /scratch-1/soft/spack/opt/spack/linux-ubuntu20.04-zen2/gcc-9.4.0/hdf5-1.14.3-hzicuphosrqicmxhl66fzdjdkjkmzxdy JULIA_LOAD_PATH = :/scratch-1/julia_prefs/ JULIA_NUM_THREADS = 4
Details on CUDA:
CUDA runtime 12.3, local installation CUDA driver 12.3 NVIDIA driver 545.23.8 CUDA libraries: - CUBLAS: 12.3.4 - CURAND: 10.3.4 - CUFFT: 11.0.12 - CUSOLVER: 11.5.4 - CUSPARSE: 12.2.0 - CUPTI: 2023.3.1 (API 21.0.0) - NVML: 12.0.0+545.23.8 Julia packages: - CUDA: 5.5.2 - CUDA_Driver_jll: 0.10.4+0 - CUDA_Runtime_jll: 0.15.5+0 - CUDA_Runtime_Discovery: 0.3.5 Toolchain: - Julia: 1.11.2 - LLVM: 16.0.6 Preferences: - CUDA_Runtime_jll.version: local 8 devices: 0: NVIDIA A100-SXM4-40GB (sm_80, 38.893 GiB / 40.000 GiB available) 1: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available) 2: NVIDIA A100-SXM4-40GB (sm_80, 30.848 GiB / 40.000 GiB available) 3: NVIDIA A100-SXM4-40GB (sm_80, 30.848 GiB / 40.000 GiB available) 4: NVIDIA A100-SXM4-40GB (sm_80, 30.848 GiB / 40.000 GiB available) 5: NVIDIA A100-SXM4-40GB (sm_80, 30.848 GiB / 40.000 GiB available) 6: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available) 7: NVIDIA A100-SXM4-40GB (sm_80, 39.385 GiB / 40.000 GiB available)
Additional context
Related to EnzymeAD/Enzyme.jl#2186
The text was updated successfully, but these errors were encountered:
@maleadt I made a new Enzyme label if that's fine (and I'll autoassign/handle any such issues)
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wsmoses
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Describe the bug
Enzyme.make_zero(CuArray)
doesn't create a new array of the same shape filled with zeros, but instead returns the same array.To reproduce
The Minimal Working Example (MWE) for this bug:
Manifest.toml
Expected behavior
make_zero
should return the zero-initialised copy of the CUDA device array.Version info
Details on Julia:
Details on CUDA:
Additional context
Related to EnzymeAD/Enzyme.jl#2186
The text was updated successfully, but these errors were encountered: