Open unclemusclez opened 3 months ago
Hello!
I'm not very familiar with AMD GPUs and their kernel images, etc. However, the operation on which you're failing (torch.sum(token_embeddings * input_mask_expanded, 1)
) is rather simple, so this strikes me as 1) an incompatibility of some kind between your softwares (e.g. WSL2 on Windows with the ROCm image) or 2) an installation issue.
If you ran a very simple torch script with your AMD GPU, does that one work correctly? E.g.
import torch
device = torch.device("cuda")
matrix = torch.randn(3, 2, device=device) @ torch.randn(2, 5, device=device)
sum = matrix.sum()
print(sum)
# => tensor(3.7824, device='cuda:0')
$ HIP_VISIBLE_DEVICES=0 python test.py
/home/musclez/test.py:4: UserWarning: Attempting to use hipBLASLt on an unsupported architecture! Overriding blas backend to hipblas (Triggered internally at ../aten/src/ATen/Context.cpp:288.)
matrix = torch.randn(3, 2, device=device) @ torch.randn(2, 5, device=device)
tensor(3.5258, device='cuda:0')
i think we are getting warmer. This may work fine on MI300 CDNA3 architecture, which i believe would be the priority of AMD. I've had issues in the past with hipBLASLt
working with gfx1100 (Navi 31, Radeon 7900)
with "device = torch.device("hip")
"
import torch
device = torch.device("hip")
matrix = torch.randn(3, 2, device=device) @ torch.randn(2, 5, device=device)
sum = matrix.sum()
print(sum)
# => tensor(3.7824, device='cuda:0')
$HIP_VISIBLE_DEVICES=0 python test.py
Traceback (most recent call last):
File "/home/musclez/test.py", line 4, in <module>
matrix = torch.randn(3, 2, device=device) @ torch.randn(2, 5, device=device)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
NotImplementedError: Could not run 'aten::empty.memory_format' with arguments from the 'HIP' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'aten::empty.memory_format' is only available for these backends: [CPU, CUDA, Meta, QuantizedCPU, QuantizedCUDA, QuantizedMeta, MkldnnCPU, SparseCPU, SparseCUDA, SparseMeta, SparseCsrCPU, SparseCsrCUDA, SparseCsrMeta, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradHIP, AutogradXLA, AutogradMPS, AutogradIPU, AutogradXPU, AutogradHPU, AutogradVE, AutogradLazy, AutogradMTIA, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, AutogradMeta, AutogradNestedTensor, Tracer, AutocastCPU, AutocastXPU, AutocastCUDA, FuncTorchBatched, BatchedNestedTensor, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PreDispatch, PythonDispatcher].
CPU: registered at aten/src/ATen/RegisterCPU.cpp:30476 [kernel]
CUDA: registered at aten/src/ATen/RegisterCUDA.cpp:44679 [kernel]
Meta: registered at aten/src/ATen/RegisterMeta.cpp:26996 [kernel]
QuantizedCPU: registered at aten/src/ATen/RegisterQuantizedCPU.cpp:954 [kernel]
QuantizedCUDA: registered at aten/src/ATen/RegisterQuantizedCUDA.cpp:462 [kernel]
QuantizedMeta: registered at aten/src/ATen/RegisterQuantizedMeta.cpp:108 [kernel]
MkldnnCPU: registered at aten/src/ATen/RegisterMkldnnCPU.cpp:534 [kernel]
SparseCPU: registered at aten/src/ATen/RegisterSparseCPU.cpp:1406 [kernel]
SparseCUDA: registered at aten/src/ATen/RegisterSparseCUDA.cpp:1576 [kernel]
SparseMeta: registered at aten/src/ATen/RegisterSparseMeta.cpp:290 [kernel]
SparseCsrCPU: registered at aten/src/ATen/RegisterSparseCsrCPU.cpp:1154 [kernel]
SparseCsrCUDA: registered at aten/src/ATen/RegisterSparseCsrCUDA.cpp:1279 [kernel]
SparseCsrMeta: registered at aten/src/ATen/RegisterSparseCsrMeta.cpp:1068 [kernel]
BackendSelect: registered at aten/src/ATen/RegisterBackendSelect.cpp:792 [kernel]
Python: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:153 [backend fallback]
FuncTorchDynamicLayerBackMode: registered at ../aten/src/ATen/functorch/DynamicLayer.cpp:497 [backend fallback]
Functionalize: registered at ../aten/src/ATen/FunctionalizeFallbackKernel.cpp:349 [backend fallback]
Named: registered at ../aten/src/ATen/core/NamedRegistrations.cpp:7 [backend fallback]
Conjugate: fallthrough registered at ../aten/src/ATen/ConjugateFallback.cpp:21 [kernel]
Negative: fallthrough registered at ../aten/src/ATen/native/NegateFallback.cpp:22 [kernel]
ZeroTensor: fallthrough registered at ../aten/src/ATen/ZeroTensorFallback.cpp:90 [kernel]
ADInplaceOrView: fallthrough registered at ../aten/src/ATen/core/VariableFallbackKernel.cpp:96 [backend fallback]
AutogradOther: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradCPU: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradCUDA: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradHIP: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradXLA: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradMPS: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradIPU: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradXPU: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradHPU: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradVE: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradLazy: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradMTIA: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradPrivateUse1: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradPrivateUse2: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradPrivateUse3: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradMeta: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
AutogradNestedTensor: registered at ../torch/csrc/autograd/generated/VariableType_2.cpp:19981 [autograd kernel]
Tracer: registered at ../torch/csrc/autograd/generated/TraceType_2.cpp:17715 [kernel]
AutocastCPU: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:209 [backend fallback]
AutocastXPU: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:351 [backend fallback]
AutocastCUDA: fallthrough registered at ../aten/src/ATen/autocast_mode.cpp:165 [backend fallback]
FuncTorchBatched: registered at ../aten/src/ATen/functorch/LegacyBatchingRegistrations.cpp:731 [backend fallback]
BatchedNestedTensor: registered at ../aten/src/ATen/functorch/LegacyBatchingRegistrations.cpp:758 [backend fallback]
FuncTorchVmapMode: fallthrough registered at ../aten/src/ATen/functorch/VmapModeRegistrations.cpp:27 [backend fallback]
Batched: registered at ../aten/src/ATen/LegacyBatchingRegistrations.cpp:1075 [backend fallback]
VmapMode: fallthrough registered at ../aten/src/ATen/VmapModeRegistrations.cpp:33 [backend fallback]
FuncTorchGradWrapper: registered at ../aten/src/ATen/functorch/TensorWrapper.cpp:207 [backend fallback]
PythonTLSSnapshot: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:161 [backend fallback]
FuncTorchDynamicLayerFrontMode: registered at ../aten/src/ATen/functorch/DynamicLayer.cpp:493 [backend fallback]
PreDispatch: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:165 [backend fallback]
PythonDispatcher: registered at ../aten/src/ATen/core/PythonFallbackKernel.cpp:157 [backend fallback]
attempting to use
autotrainer-advanced
with pytoch 2.4.0 ROCm on WSL2 Ubuntu 22.04 Windows 11