torch.nn.BatchNorm1d missing check on values of parameters eps and momentum

[PhyllisJi]

🐛 Describe the bug

Use the eps parameter of torch.nn.BatchNorm1d to prevent divide-by-zero errors. Setting the eps parameter to 0.0 is non-compliant, as it leads to numerical instability and may trigger a divide-by-zero error when calculating the variance. However pytorch does not check for this parameter.

import torch
import torch.nn as nn

batch_norm = nn.BatchNorm1d(
    num_features=512,
    eps=0.0,  
    momentum=0.9
)

input_tensor = torch.randn(16, 512)  # (batch_size, num_features)
output = batch_norm(input_tensor)
print(output)

MindSpore framework throws the following exception：

ValueError: For 'BatchNorm', the 'epsilon' must be in range of (0, 1], but got 0.0 with type 'float'.

When using torch.nn.BatchNorm1d, the momentum parameter usually has a value between [0, 1). Setting momentum to a value greater than or equal to 1 is non-compliant and will cause the Batch Normalisation layer to behave abnormally. However pytorch does not check for this parameter.

import torch

batch_norm = torch.nn.BatchNorm1d(num_features=128, eps=1e-05, momentum=1.00001)

input_tensor = torch.randn(16, 128)  # (batch_size, num_features)
output = batch_norm(input_tensor)
print(output)

MindSpore framework throws the following exception：

ValueError: For 'BatchNorm1d', the 'momentum' must be a number in range [0, 1], but got 1.00001.

Versions

PyTorch version: 2.2.0+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 Clang version: Could not collect CMake version: version 3.16.3 Libc version: glibc-2.31

Python version: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-4.19.0-14-amd64-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 12.1.105 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3080 Ti Nvidia driver version: 535.98 cuDNN version: Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0 HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian Address sizes: 46 bits physical, 48 bits virtual CPU(s): 72 On-line CPU(s) list: 0-71 Thread(s) per core: 2 Core(s) per socket: 18 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2686 v4 @ 2.30GHz Stepping: 1 CPU MHz: 1200.011 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4599.86 Virtualization: VT-x L1d cache: 1.1 MiB L1i cache: 1.1 MiB L2 cache: 9 MiB L3 cache: 90 MiB NUMA node0 CPU(s): 0-17,36-53 NUMA node1 CPU(s): 18-35,54-71 Vulnerability Itlb multihit: KVM: Mitigation: Split huge pages Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Meltdown: Mitigation; PTI Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Full generic retpoline, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT vulnerable 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 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 ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a rdseed adx smap intel_pt xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts md_clear flush_l1d

Versions of relevant libraries: [pip3] numpy==1.26.4 [pip3] onnx==1.16.0 [pip3] torch==2.2.0 [pip3] triton==2.2.0 [conda] numpy 1.26.4 pypi_0 pypi [conda] torch 2.2.0 pypi_0 pypi [conda] triton 2.2.0 pypi_0 pypi

cc @albanD @mruberry @jbschlosser @walterddr @mikaylagawarecki

[PhyllisJi]

Any Update？