[Installation]: I tried compile GFX1100 on WSL2 but it does not seems work #780
Comments
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Could you compile aphrodite from source? I don't think there's a package for rocm. Here's how to do it. |
I did try to compile but the patch doesn't seems to work |
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What error did you get? EDIT: Sorry, I have the stupid and didn't notice you gave build logs |
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Your pytorch is way too out of date. Could you update to 2.5? |
I update it to pytorch 2.5, and now it show |
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So first check if aphrodite compiles. If it fails like "__test is ambiguous" or something like that you will need to patch it yourself. It would be nice if you could send where __clang_hip_cmath.h is, since I can't test rocm 6.1 (slow internet), so I could edit the script. |
I cannot compile it and when I check the exact folder. root@x:/opt/rocm/lib/llvm/lib/clang/18/include# |
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Is there different version of clang? Like under /opt/rocm/lib/llvm/lib/clang/ |
clang 17 should work. |
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Does this work? |
Not quite. cd aphrodite-engine/ and I try to run it anyway. |
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So patch actually works, but you're missing a different file for some reason. I'm not sure if it's a WSL thing. I guess you could try to do this, though I have no idea if it will work. location=`pip show torch | grep Location | awk -F ": " '{print $2}'
cd ${location}/torch/lib/
rm libhsa-runtime64.so*
cp /opt/rocm/lib/libhsa-runtime64.so.1.2 libhsa-runtime64.soHonestly, I don't recommend using WSL and if you can, you should probably just dualboot linux for ROCM |
Your current environment
python env.py
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.1.2 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
Traceback (most recent call last): File "/home/sora/aphrodite-engine/env.py", line 17, in
import torch
File "/usr/local/lib/python3.10/dist-packages/torch/init.py", line 1382, in
from .functional import * # noqa: F403
File "/usr/local/lib/python3.10/dist-packages/torch/functional.py", line 7, in
import torch.nn.functional as F
File "/usr/local/lib/python3.10/dist-packages/torch/nn/init.py", line 1, in
from .modules import * # noqa: F403
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/init.py", line 35, in
from .transformer import TransformerEncoder, TransformerDecoder,
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/transformer.py", line 20, in
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
/usr/local/lib/python3.10/dist-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at /pytorch/torch/csrc/utils/tensor_n umpy.cpp:84.)
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
Collecting environment information...
/usr/local/lib/python3.10/dist-packages/torch/cuda/init.py:611: UserWarning: Can't initialize NVML
warnings.warn("Can't initialize NVML")
PyTorch version: 2.1.2+rocm6.1.3
Is debug build: False
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: 6.1.40093-bd86f1708
OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.30.4
Libc version: glibc-2.35
Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 11.5.119
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: AMD Radeon RX 7900 XTXNoGCNArchNameOnOldPyTorch
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: 6.1.40093
MIOpen runtime version: 3.1.0
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 48 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 32
On-line CPU(s) list: 0-31
Vendor ID: AuthenticAMD
Model name: AMD Ryzen 9 7950X3D 16-Core Processor
CPU family: 25
Model: 97
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 1
Stepping: 2
BogoMIPS: 8399.84
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc re p_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misal ignsse 3dnowprefetch osvw topoext perfctr_core ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx 512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx512_bf16 clzero xsaveerptr arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm
Virtualization: AMD-V
Hypervisor vendor: Microsoft
Virtualization type: full
L1d cache: 512 KiB (16 instances)
L1i cache: 512 KiB (16 instances)
L2 cache: 16 MiB (16 instances)
L3 cache: 96 MiB (1 instance)
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Mitigation; safe RET
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: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==2.1.2
[pip3] pytorch-triton-rocm==2.1.0+rocm6.1.3.4d510c3a44
[pip3] torch==2.1.2+rocm6.1.3
[pip3] torchvision==0.16.1+rocm6.1.3
[conda] Could not collect
ROCM Version: 6.1.40093-bd86f1708
Neuron SDK Version: N/A
Aphrodite Version: N/A
Aphrodite Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect
root@SORANET:/home/sora/aphrodite-engine# sudo python env.py
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.1.2 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
Traceback (most recent call last): File "/home/sora/aphrodite-engine/env.py", line 17, in
import torch
File "/usr/local/lib/python3.10/dist-packages/torch/init.py", line 1382, in
from .functional import * # noqa: F403
File "/usr/local/lib/python3.10/dist-packages/torch/functional.py", line 7, in
import torch.nn.functional as F
File "/usr/local/lib/python3.10/dist-packages/torch/nn/init.py", line 1, in
from .modules import * # noqa: F403
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/init.py", line 35, in
from .transformer import TransformerEncoder, TransformerDecoder,
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/transformer.py", line 20, in
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
/usr/local/lib/python3.10/dist-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:84.)
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
Collecting environment information...
/usr/local/lib/python3.10/dist-packages/torch/cuda/init.py:611: UserWarning: Can't initialize NVML
warnings.warn("Can't initialize NVML")
PyTorch version: 2.1.2+rocm6.1.3
Is debug build: False
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: 6.1.40093-bd86f1708
OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.30.4
Libc version: glibc-2.35
Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 11.5.119
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: AMD Radeon RX 7900 XTXNoGCNArchNameOnOldPyTorch
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: 6.1.40093
MIOpen runtime version: 3.1.0
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 48 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 32
On-line CPU(s) list: 0-31
Vendor ID: AuthenticAMD
Model name: AMD Ryzen 9 7950X3D 16-Core Processor
CPU family: 25
Model: 97
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 1
Stepping: 2
BogoMIPS: 8399.84
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx512_bf16 clzero xsaveerptr arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm
Virtualization: AMD-V
Hypervisor vendor: Microsoft
Virtualization type: full
L1d cache: 512 KiB (16 instances)
L1i cache: 512 KiB (16 instances)
L2 cache: 16 MiB (16 instances)
L3 cache: 96 MiB (1 instance)
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Mitigation; safe RET
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: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==2.1.2
[pip3] pytorch-triton-rocm==2.1.0+rocm6.1.3.4d510c3a44
[pip3] torch==2.1.2+rocm6.1.3
[pip3] torchvision==0.16.1+rocm6.1.3
[conda] Could not collect
ROCM Version: 6.1.40093-bd86f1708
Neuron SDK Version: N/A
Aphrodite Version: N/A
Aphrodite Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect
How did you install Aphrodite?
sudo apt update
wget https://repo.radeon.com/amdgpu-install/6.1.3/ubuntu/jammy/amdgpu-install_6.1.60103-1_all.deb
sudo apt install ./amdgpu-install_6.1.60103-1_all.deb
sudo amdgpu-install --list-usecase
If --usecase option is not present, the default selection is
"dkms,graphics,opencl,hip"
Available use cases:
dkms (to only install the kernel mode driver)
graphics (for users of graphics applications)
multimedia (for users of open source multimedia)
multimediasdk (for developers of open source multimedia)
workstation (for users of legacy WS applications)
rocm (for users and developers requiring full ROCm stack)
wsl (for using ROCm in a WSL context)
rocmdev (for developers requiring ROCm runtime and
profiling/debugging tools)
rocmdevtools (for developers requiring ROCm profiling/debugging tools)
amf (for users of AMF based multimedia)
lrt (for users of applications requiring ROCm runtime)
opencl (for users of applications requiring OpenCL on Vega or later
products)
openclsdk (for application developers requiring ROCr based OpenCL)
hip (for users of HIP runtime on AMD products)
hiplibsdk (for application developers requiring HIP on AMD products)
openmpsdk (for users of openmp/flang on AMD products)
mllib (for users executing machine learning workloads)
mlsdk (for developers executing machine learning workloads)
asan (for users of ASAN enabled ROCm packages)
rocminfo
HSA System Attributes
Runtime Version: 1.1
System Timestamp Freq.: 1000.000000MHz
Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model: LARGE
System Endianness: LITTLE
Mwaitx: DISABLED
DMAbuf Support: NO
==========
HSA Agents
Agent 1
Name: CPU
Uuid: CPU-XX
Marketing Name: CPU
Vendor Name: CPU
Feature: None specified
Profile: FULL_PROFILE
Float Round Mode: NEAR
Max Queue Number: 0(0x0)
Queue Min Size: 0(0x0)
Queue Max Size: 0(0x0)
Queue Type: MULTI
Node: 0
Device Type: CPU
Cache Info:
Chip ID: 0(0x0)
Cacheline Size: 64(0x40)
Internal Node ID: 0
Compute Unit: 32
SIMDs per CU: 0
Shader Engines: 0
Shader Arrs. per Eng.: 0
Features: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED
Size: 49137460(0x2edc734) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 2
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 49137460(0x2edc734) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
ISA Info:
Agent 2
Name: gfx1100
Marketing Name: AMD Radeon RX 7900 XTX
Vendor Name: AMD
Feature: KERNEL_DISPATCH
Profile: BASE_PROFILE
Float Round Mode: NEAR
Max Queue Number: 16(0x10)
Queue Min Size: 4096(0x1000)
Queue Max Size: 131072(0x20000)
Queue Type: MULTI
Node: 1
Device Type: GPU
Cache Info:
L1: 32(0x20) KB
L2: 6144(0x1800) KB
L3: 98304(0x18000) KB
Chip ID: 29772(0x744c)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 2526
Internal Node ID: 1
Compute Unit: 96
SIMDs per CU: 2
Shader Engines: 6
Shader Arrs. per Eng.: 2
Coherent Host Access: FALSE
Features: KERNEL_DISPATCH
Fast F16 Operation: TRUE
Wavefront Size: 32(0x20)
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Max Waves Per CU: 32(0x20)
Max Work-item Per CU: 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
Max fbarriers/Workgrp: 32
Packet Processor uCode:: 2280
SDMA engine uCode:: 21
IOMMU Support:: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 25086124(0x17ec8ac) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 2
Segment: GROUP
Size: 64(0x40) KB
Allocatable: FALSE
Alloc Granule: 0KB
Alloc Recommended Granule:0KB
Alloc Alignment: 0KB
Accessible by all: FALSE
ISA Info:
ISA 1
Name: amdgcn-amd-amdhsa--gfx1100
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
*** Done ***
build log
rocm_gfx1100_wsl2.txt
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