A scalar with `elements` or `test_elements` argument of `isin()` doesn't work

[hyperkai]

🐛 Describe the bug

isin():

• A scalar(e.g. 3, 4, 5, etc) with elements or test_elements argument doesn't work. <- Problem(Bug)
• A scalar without elements or test_elements argument works.

import torch

t1 = torch.tensor([3, 4, 5])
t2 = torch.tensor(4)

torch.isin(elements=3, test_elements=t2) # Error 1
torch.isin(elements=t1, test_elements=4) # Error 2
torch.isin(t1, test_elements=4) # Error 3

torch.isin(3, test_elements=t2)
torch.isin(3, t2)
# tensor(False)

torch.isin(t1, 4)
# tensor([False, True, False])

""" ↓↓↓ Additional ↓↓↓ """

torch.isin(elements=t1, test_elements=t2)
torch.isin(t1, test_elements=t2)
torch.isin(t1, t2)
# tensor([False,  True, False])

Error 1:

TypeError: isin() received an invalid combination of arguments - got (test_elements=Tensor, elements=int, ), but expected one of:
 * (Tensor elements, Tensor test_elements, *, bool assume_unique, bool invert, Tensor out)
 * (Number element, Tensor test_elements, *, bool assume_unique, bool invert, Tensor out)
 * (Tensor elements, Number test_element, *, bool assume_unique, bool invert, Tensor out)

Error 2:

TypeError: isin() received an invalid combination of arguments - got (test_elements=int, elements=Tensor, ), but expected one of:
 * (Tensor elements, Tensor test_elements, *, bool assume_unique, bool invert, Tensor out)
 * (Number element, Tensor test_elements, *, bool assume_unique, bool invert, Tensor out)
 * (Tensor elements, Number test_element, *, bool assume_unique, bool invert, Tensor out)

Error 3:

TypeError: isin() received an invalid combination of arguments - got (Tensor, test_elements=int), but expected one of:
 * (Tensor elements, Tensor test_elements, *, bool assume_unique, bool invert, Tensor out)
 * (Number element, Tensor test_elements, *, bool assume_unique, bool invert, Tensor out)
 * (Tensor elements, Number test_element, *, bool assume_unique, bool invert, Tensor out)

Versions

PyTorch version: N/A Is debug build: N/A CUDA used to build PyTorch: N/A ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Clang version: Could not collect CMake version: version 3.22.1 Libc version: glibc-2.35

Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime) Python platform: Linux-6.1.75+-x86_64-with-glibc2.35 Is CUDA available: N/A CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: Could not collect Nvidia driver version: Could not collect cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: N/A

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 46 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 4 On-line CPU(s) list: 0-3 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) CPU @ 2.20GHz CPU family: 6 Model: 79 Thread(s) per core: 2 Core(s) per socket: 2 Socket(s): 1 Stepping: 0 BogoMIPS: 4399.99 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities Hypervisor vendor: KVM Virtualization type: full L1d cache: 64 KiB (2 instances) L1i cache: 64 KiB (2 instances) L2 cache: 512 KiB (2 instances) L3 cache: 55 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-3 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Mitigation; PTE Inversion Vulnerability Mds: Mitigation; Clear CPU buffers; SMT Host state unknown Vulnerability Meltdown: Mitigation; PTI Vulnerability Mmio stale data: Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown Vulnerability Retbleed: Mitigation; IBRS Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; IBRS, IBPB conditional, STIBP conditional, RSB filling, PBRSB-eIBRS Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT Host state unknown

Versions of relevant libraries: [pip3] flake8==3.8.4 [pip3] mypy==1.10.0 [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.26.4 [pip3] optree==0.11.0 [pip3] pyls-mypy==0.1.8 [conda] Could not collect

cc @albanD

[shevisj]

same issue

[themw123]

same

[albanD]

This looks like expected behavior? This is quite confusing the but argument for this function take plural or not depending on the type: element vs elements for example. All the errors and signatures look accurate to me?

[zylo117]

+1

[gante]

Can confirm the issue as of torch 2.4.0, exactly as described in the header.