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  1. AI Platform Core Components
  2. AIPCC-6062

torch.nn.functional.softshrink throws overflow error on CUDA but not on CPU

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    • PyTorch Sprint 15, PyTorch Sprint 16, PyTorch Sprint 18, PyTorch Sprint 19, PyTorch Sprint 20, PyTorch Sprint 21

          1. 🐛 Describe the bug

      Running `torch.nn.functional.softshrink` with a `float16` tensor and a `lambda` value that exceeds the `float16` limits (e.g. 65507) throws an overflow error on CUDA but on CPU it does not cause any errors.

      Reproduction code:

      ```python
      import torch

      input_tensor = torch.randn(34, 43, dtype=torch.float16)
      lambd = 65507.0

      out_cpu = torch.nn.functional.softshrink(input_tensor, lambd)
      print("No errors on CPU")
      out_gpu = torch.nn.functional.softshrink(input_tensor.cuda(), lambd)

      1. RuntimeError: value cannot be converted to type at::Half without overflow
        print("No errors on CUDA") # does not reach here
        ```

      Also here's a [colab](https://colab.research.google.com/drive/17nWHeQm5IIk31kykYr7DOEwYahYy64-H?usp=sharing)

          1. Versions

      Vendor ID: GenuineIntel
      Model name: Intel(R) Xeon(R) CPU @ 2.00GHz
      CPU family: 6
      Model: 85
      Thread(s) per core: 2
      Core(s) per socket: 1
      Socket(s): 1
      Stepping: 3
      BogoMIPS: 4000.37
      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 ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat md_clear arch_capabilities
      Hypervisor vendor: KVM
      Virtualization type: full
      L1d cache: 32 KiB (1 instance)
      L1i cache: 32 KiB (1 instance)
      L2 cache: 1 MiB (1 instance)
      L3 cache: 38.5 MiB (1 instance)
      NUMA node(s): 1
      NUMA node0 CPU(s): 0,1
      Vulnerability Gather data sampling: Not affected
      Vulnerability Itlb multihit: Not affected
      Vulnerability L1tf: Mitigation; PTE Inversion
      Vulnerability Mds: Vulnerable; SMT Host state unknown
      Vulnerability Meltdown: Vulnerable
      Vulnerability Mmio stale data: Vulnerable
      Vulnerability Reg file data sampling: Not affected
      Vulnerability Retbleed: Vulnerable
      Vulnerability Spec rstack overflow: Not affected
      Vulnerability Spec store bypass: Vulnerable
      Vulnerability Spectre v1: Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
      Vulnerability Spectre v2: Vulnerable; IBPB: disabled; STIBP: disabled; PBRSB-eIBRS: Not affected; BHI: Vulnerable
      Vulnerability Srbds: Not affected
      Vulnerability Tsx async abort: Vulnerable

      Versions of relevant libraries:
      [pip3] numpy==2.0.2
      [pip3] nvidia-cublas-cu12==12.5.3.2
      [pip3] nvidia-cuda-cupti-cu12==12.5.82
      [pip3] nvidia-cuda-nvrtc-cu12==12.5.82
      [pip3] nvidia-cuda-runtime-cu12==12.5.82
      [pip3] nvidia-cudnn-cu12==9.3.0.75
      [pip3] nvidia-cufft-cu12==11.2.3.61
      [pip3] nvidia-curand-cu12==10.3.6.82
      [pip3] nvidia-cusolver-cu12==11.6.3.83
      [pip3] nvidia-cusparse-cu12==12.5.1.3
      [pip3] nvidia-cusparselt-cu12==0.6.2
      [pip3] nvidia-nccl-cu12==2.21.5
      [pip3] nvidia-nvjitlink-cu12==12.5.82
      [pip3] nvidia-nvtx-cu12==12.4.127
      [pip3] nvtx==0.2.11
      [pip3] optree==0.15.0
      [pip3] pynvjitlink-cu12==0.5.2
      [pip3] torch==2.6.0+cu124
      [pip3] torchaudio==2.6.0+cu124
      [pip3] torchsummary==1.5.1
      [pip3] torchvision==0.21.0+cu124
      [pip3] triton==3.2.0
      [conda] Could not collect

      cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki @malfet

              rh-ee-visgoyal Vishal Goyal
              rh-ee-visgoyal Vishal Goyal
              PyTorch Core
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                Created:
                Updated:
                Resolved: