Description
Describe the bug
Hi,
ipex does not work at least for Adan from the package pytorch_optimizer.
Here is a toy example:
import torch
import torch.nn as nn
import numpy as np
import intel_extension_for_pytorch as ipex
from pytorch_optimizer import Adan
input_size = 1
output_size = 1
# hyper-parameters
num_epochs = 1
learning_rate = 0.001
# toy dataset
x = np.random.randn(10, input_size).astype(np.float32)
y = np.random.randn(10, output_size).astype(np.float32)
# linear regression model
model = nn.Linear(input_size, output_size)
# loss and optimizer
criterion = nn.MSELoss()
optimizer = Adan(model.parameters(), lr=learning_rate)
# ipex
model, optimizer = ipex.optimize(model, optimizer=optimizer)
# train the model
for epoch in range(num_epochs):
inputs = torch.from_numpy(x)
targets = torch.from_numpy(y)
# forward pass
outputs = model(inputs)
loss = criterion(outputs, targets)
# backward and optimize
optimizer.zero_grad()
loss.backward()
optimizer.step()
Result:
AttributeError: 'Adan' object has no attribute 'use_gc'
Versions
PyTorch version: 2.0.1+cpu
PyTorch CXX11 ABI: No
IPEX version: 2.0.100+cpu
IPEX commit: 6a341a3
Build type: Release
OS: openSUSE Leap 15.5 (x86_64)
GCC version: (SUSE Linux) 7.5.0
Clang version: N/A
IGC version: N/A
CMake version: version 3.20.4
Libc version: glibc-2.31
Python version: 3.11.4 (main, Jul 06 2023, 16:27:46) [GCC] (64-bit runtime)
Python platform: Linux-5.14.21-150500.55.19-default-x86_64-with-glibc2.31
Is XPU available: False
DPCPP runtime version: N/A
MKL version: N/A
GPU models and configuration:
Intel OpenCL ICD version: N/A
Level Zero version: N/A
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 39 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 8
On-line CPU(s) list: 0-7
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i7-4700MQ CPU @ 2.40GHz
CPU family: 6
Model: 60
Thread(s) per core: 2
Core(s) per socket: 4
Socket(s): 1
Stepping: 3
CPU max MHz: 3400.0000
CPU min MHz: 800.0000
BogoMIPS: 4788.84
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 est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt dtherm ida arat pln pts md_clear flush_l1d
Virtualization: VT-x
L1d cache: 128 KiB (4 instances)
L1i cache: 128 KiB (4 instances)
L2 cache: 1 MiB (4 instances)
L3 cache: 6 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-7
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Unknown: No mitigations
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
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; Retpolines, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Mitigation; Microcode
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] intel-extension-for-pytorch==2.0.100
[pip3] numpy==1.25.2
[pip3] pytorch_optimizer==2.11.2
[pip3] torch==2.0.1+cpu
[pip3] torch-cluster==1.6.1+pt20cpu
[pip3] torch-geometric==2.3.1
[pip3] torch-scatter==2.1.1+pt20cpu
[pip3] torch-sparse==0.6.17+pt20cpu
[pip3] torch-spline-conv==1.2.2+pt20cpu
[pip3] torchaudio==2.0.2+cpu
[pip3] torchvision==0.15.2+cpu
[pip3] vector-quantize-pytorch==1.7.1
[conda] N/A