[BUG] casting from float32 to Decimal64Dtype is resulting in incorrect values #14169
Closed
Description
Describe the bug
When there is a type-cast from float32 to Decimal64Dtype, the decimal values yield incorrect results. This issue was surfaced when testing arrow-13. arrow-12 has the same bug and it was fixed in arrow-13, we have similar issue in our libcudf too.
Steps/Code to reproduce bug
IIn [20]: import pyarrow as pa # This is pyarrow-13, not 12
In [21]: import cudf
In [22]: data = [14.12302, 97938.2, None, 0.0, -8.302014, None, 94.31304, -112.2314, 0.3333333]
In [23]: s = cudf.Series(data, dtype='float32')
In [24]: s
Out[24]:
0 14.12302017
1 97938.20313
2 <NA>
3 0.0
4 -8.302014351
5 <NA>
6 94.31304169
7 -112.2313995
8 0.333333313
dtype: float32
In [25]: parray = pa.array(data, type=pa.float32())
In [26]: parray
Out[26]:
<pyarrow.lib.FloatArray object at 0x7ff00e3bf700>
[
14.12302,
97938.2,
null,
0,
-8.302014,
null,
94.31304,
-112.2314,
0.3333333
]
In [27]: decimal_dtype = cudf.Decimal64Dtype(11, 4)
In [28]: s.astype(decimal_dtype)
Out[28]:
0 14.1230
1 97938.2016 # Incorrect, it should be 97938.2031
2 None
3 0.0000
4 -8.3020
5 None
6 94.3130
7 -112.2314
8 0.3333
dtype: decimal64
In [29]: parray.cast(decimal_dtype.to_arrow())
Out[29]:
<pyarrow.lib.Decimal128Array object at 0x7ff00e1bebc0>
[
14.1230,
97938.2031,
null,
0.0000,
-8.3020,
null,
94.3130,
-112.2314,
0.3333
]Expected behavior
In [28]: s.astype(decimal_dtype)
Out[28]:
0 14.1230
1 97938.2031 # Incorrect, it should be 97938.2031
2 None
3 0.0000
4 -8.3020
5 None
6 94.3130
7 -112.2314
8 0.3333
dtype: decimal64Environment overview (please complete the following information)
- Environment location: [Bare-metal]
- Method of cuDF install: [from source]
Environment details
Please run and paste the output of the cudf/print_env.sh script here, to gather any other relevant environment details
Click here to see environment details
**git*** commit 4b2a8e2ccdeff36ff58d28d80c8742a474e1d69a (HEAD -> arrow_13) Author: galipremsagar <sagarprem75@gmail.com> Date: Thu Sep 21 23:13:31 2023 -0700 Upgrade to arrow 13 **git submodules*** ***OS Information*** DISTRIB_ID=Ubuntu DISTRIB_RELEASE=18.04 DISTRIB_CODENAME=bionic DISTRIB_DESCRIPTION="Ubuntu 18.04.4 LTS" NAME="Ubuntu" VERSION="18.04.4 LTS (Bionic Beaver)" ID=ubuntu ID_LIKE=debian PRETTY_NAME="Ubuntu 18.04.4 LTS" VERSION_ID="18.04" HOME_URL="https://www.ubuntu.com/" SUPPORT_URL="https://help.ubuntu.com/" BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/" PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy" VERSION_CODENAME=bionic UBUNTU_CODENAME=bionic Linux dt07 4.15.0-76-generic #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux ***GPU Information*** Fri Sep 22 03:31:47 2023 +---------------------------------------------------------------------------------------+ | NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 | |-----------------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+======================+======================| | 0 Tesla T4 On | 00000000:3B:00.0 Off | 0 | | N/A 46C P0 27W / 70W| 1348MiB / 15360MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ | 1 Tesla T4 On | 00000000:5E:00.0 Off | 0 | | N/A 34C P8 9W / 70W| 4MiB / 15360MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ | 2 Tesla T4 On | 00000000:AF:00.0 Off | 0 | | N/A 29C P8 10W / 70W| 4MiB / 15360MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ | 3 Tesla T4 On | 00000000:D8:00.0 Off | 0 | | N/A 28C P8 10W / 70W| 4MiB / 15360MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ +---------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=======================================================================================| +---------------------------------------------------------------------------------------+ ***CPU*** Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 64 On-line CPU(s) list: 0-63 Thread(s) per core: 2 Core(s) per socket: 16 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 85 Model name: Intel(R) Xeon(R) Gold 6130 CPU @ 2.10GHz Stepping: 4 CPU MHz: 1194.971 BogoMIPS: 4200.00 Virtualization: VT-x L1d cache: 32K L1i cache: 32K L2 cache: 1024K L3 cache: 22528K NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62 NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke md_clear flush_l1d arch_capabilities ***CMake*** /nvme/0/pgali/envs/cudfdev/bin/cmake cmake version 3.27.6 CMake suite maintained and supported by Kitware (kitware.com/cmake). ***g++*** /nvme/0/pgali/envs/cudfdev/bin/g++ g++ (conda-forge gcc 11.4.0-2) 11.4.0 Copyright (C) 2021 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. ***nvcc*** /nvme/0/pgali/envs/cudfdev/bin/nvcc nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2022 NVIDIA Corporation Built on Wed_Sep_21_10:33:58_PDT_2022 Cuda compilation tools, release 11.8, V11.8.89 Build cuda_11.8.r11.8/compiler.31833905_0 ***Python*** /nvme/0/pgali/envs/cudfdev/bin/python Python 3.10.12 ***Environment Variables*** PATH : /nvme/0/pgali/envs/cudfdev/bin:/nvme/0/pgali/envs/cudfdev/bin:/nvme/0/pgali/anaconda3/bin:/nvme/0/pgali/envs/cudfdev/bin:/nvme/0/pgali/.cargo/bin:/home/nfs/pgali/.vscode-server/bin/abd2f3db4bdb28f9e95536dfa84d8479f1eb312d/bin/remote-cli:/nvme/0/pgali/.cargo/bin:/nvme/0/pgali/anaconda3/bin:/nvme/0/pgali/anaconda3/condabin:/nvme/0/pgali/.cargo/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/usr/local/cuda/bin:/usr/local/cuda/bin LD_LIBRARY_PATH : 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cuda11_py310_230922_gcd76d414_24 rapidsai-nightly rpds-py 0.10.3 py310hcb5633a_0 conda-forge rsa 4.9 pyhd8ed1ab_0 conda-forge s2n 1.3.51 h06160fa_0 conda-forge s3fs 2023.9.1 pyhd8ed1ab_0 conda-forge s3transfer 0.6.2 pyhd8ed1ab_0 conda-forge sacremoses 0.0.53 pyhd8ed1ab_0 conda-forge sarif-om 1.0.4 pyhd8ed1ab_0 conda-forge scikit-build 0.17.6 pyh4af843d_0 conda-forge scipy 1.11.2 py310hb13e2d6_1 conda-forge sed 4.8 he412f7d_0 conda-forge send2trash 1.8.2 pyh41d4057_0 conda-forge setuptools 68.2.2 pyhd8ed1ab_0 conda-forge six 1.16.0 pyh6c4a22f_0 conda-forge snappy 1.1.10 h9fff704_0 conda-forge sniffio 1.3.0 pyhd8ed1ab_0 conda-forge snowballstemmer 2.2.0 pyhd8ed1ab_0 conda-forge sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge soupsieve 2.5 pyhd8ed1ab_1 conda-forge spdlog 1.11.0 h9b3ece8_1 conda-forge sphinx 5.3.0 pyhd8ed1ab_0 conda-forge sphinx-autobuild 2021.3.14 pyhd8ed1ab_0 conda-forge sphinx-copybutton 0.5.2 pyhd8ed1ab_0 conda-forge sphinx-markdown-tables 0.0.17 pyh6c4a22f_0 conda-forge sphinxcontrib-applehelp 1.0.7 pyhd8ed1ab_0 conda-forge sphinxcontrib-devhelp 1.0.5 pyhd8ed1ab_0 conda-forge sphinxcontrib-htmlhelp 2.0.4 pyhd8ed1ab_0 conda-forge sphinxcontrib-jsmath 1.0.1 pyhd8ed1ab_0 conda-forge sphinxcontrib-qthelp 1.0.6 pyhd8ed1ab_0 conda-forge sphinxcontrib-serializinghtml 1.1.9 pyhd8ed1ab_0 conda-forge sphinxcontrib-websupport 1.2.6 pyhd8ed1ab_0 conda-forge sqlalchemy 2.0.21 py310h2372a71_0 conda-forge sshpubkeys 3.3.1 pyhd8ed1ab_0 conda-forge stack_data 0.6.2 pyhd8ed1ab_0 conda-forge streamz 0.6.4 pyh6c4a22f_0 conda-forge sympy 1.12 pypyh9d50eac_103 conda-forge sysroot_linux-64 2.17 h4a8ded7_13 conda-forge tabulate 0.9.0 pyhd8ed1ab_1 conda-forge tblib 2.0.0 pyhd8ed1ab_0 conda-forge terminado 0.17.1 pyh41d4057_0 conda-forge tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge tk 8.6.12 h27826a3_0 conda-forge tokenizers 0.13.1 py310h633acb5_2 conda-forge toml 0.10.2 pyhd8ed1ab_0 conda-forge tomli 2.0.1 pyhd8ed1ab_0 conda-forge toolz 0.12.0 pyhd8ed1ab_0 conda-forge 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conda-forge xxhash 0.8.2 hd590300_0 conda-forge xyzservices 2023.7.0 pyhd8ed1ab_0 conda-forge xz 5.2.6 h166bdaf_0 conda-forge yaml 0.2.5 h7f98852_2 conda-forge yarl 1.9.2 py310h2372a71_0 conda-forge zeromq 4.3.4 h9c3ff4c_1 conda-forge zict 3.0.0 pyhd8ed1ab_0 conda-forge zipp 3.17.0 pyhd8ed1ab_0 conda-forge zlib 1.2.13 hd590300_5 conda-forge zstd 1.5.5 hfc55251_0 conda-forge
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