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can_cast() with from argument doesn't work but can_cast() without from argument works #126012

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hyperkai opened this issue May 11, 2024 · 1 comment
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module: python frontend For issues relating to PyTorch's Python frontend topic: fuzzer triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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@hyperkai
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hyperkai commented May 11, 2024

馃悰 Describe the bug

The doc shows can_cast() with from argument but can_cast() with from argument doesn't work while can_cast() without from argument works as shown below:

import torch


torch.can_cast(from=torch.bool, to=torch.int64) # SyntaxError: invalid syntax

torch.can_cast(torch.bool, to=torch.int64) # True

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

@tringwald
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Thank you for your bug report. The actual function signature uses from_, but the doc string uses from. I will create a PR to fix it.

@ezyang ezyang added triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module module: python frontend For issues relating to PyTorch's Python frontend topic: fuzzer labels May 14, 2024
pytorchmergebot pushed a commit that referenced this issue May 16, 2024
Fixes #126012.

`from` is a reserved keyword in Python, thus we can't make the C++ impl available with `from` as function parameter. This PR changes the name to `from_` and also adjusts the docs.

If we want to preserve backwards compatibility, we can leave the C++ name as-is and only fix the docs. However, `torch.can_cast(from_=torch.int, to=torch.int)` won't work then.

Pull Request resolved: #126030
Approved by: https://github.com/albanD
ZelboK pushed a commit to ZelboK/pytorch that referenced this issue May 19, 2024
Fixes pytorch#126012.

`from` is a reserved keyword in Python, thus we can't make the C++ impl available with `from` as function parameter. This PR changes the name to `from_` and also adjusts the docs.

If we want to preserve backwards compatibility, we can leave the C++ name as-is and only fix the docs. However, `torch.can_cast(from_=torch.int, to=torch.int)` won't work then.

Pull Request resolved: pytorch#126030
Approved by: https://github.com/albanD
ZelboK pushed a commit to ZelboK/pytorch that referenced this issue May 19, 2024
Fixes pytorch#126012.

`from` is a reserved keyword in Python, thus we can't make the C++ impl available with `from` as function parameter. This PR changes the name to `from_` and also adjusts the docs.

If we want to preserve backwards compatibility, we can leave the C++ name as-is and only fix the docs. However, `torch.can_cast(from_=torch.int, to=torch.int)` won't work then.

Pull Request resolved: pytorch#126030
Approved by: https://github.com/albanD
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