Hello, I’m new to Pytorch and learning through the documentation.
The pytorch version is the CPU version on Windows 10 python 3. My laptop only has an Intel Iris graphic card.
When I was learning scaled dot product attention on:
https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html
I was trying to reproduce the example on this page. Since my pytorch is not a cuda version so I typed the following on my Jupyter:
query = torch.rand(32, 8, 128, 64, dtype=torch.float16)
key = torch.rand(32, 8, 128, 64, dtype=torch.float16)
value = torch.rand(32, 8, 128, 64, dtype=torch.float16)
atten1 = F.scaled_dot_product_attention(query,key,value)
And I get the following error:
RuntimeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_15000\311139239.py in
2 key = torch.rand(32, 8, 128, 64, dtype=torch.float16)
3 value = torch.rand(32, 8, 128, 64, dtype=torch.float16)
----> 4 atten1 = F.scaled_dot_product_attention(query,key,value)
RuntimeError: “baddbmm_with_gemm” not implemented for ‘Half’
Any help is greatly appreciated. Thanks!
Versions
PyTorch version: 2.0.1+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: Microsoft Windows 10 Enterprise
GCC version: Could not collect
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A
Python version: 3.9.13 (main, Aug 25 2022, 23:51:50) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.19044-SP0
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture=9
CurrentClockSpeed=2611
DeviceID=CPU0
Family=205
L2CacheSize=5120
L2CacheSpeed=
Manufacturer=GenuineIntel
MaxClockSpeed=2611
Name=11th Gen Intel(R) Core™ i5-1145G7 @ 2.60GHz
ProcessorType=3
Revision=
Versions of relevant libraries:
[pip3] flake8==4.0.1
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.21.5
[pip3] numpydoc==1.4.0
[pip3] torch==2.0.1
[pip3] torchaudio==2.0.2
[pip3] torchvision==0.15.2
[conda] blas 1.0 mkl
[conda] mkl 2021.4.0 haa95532_640
[conda] mkl-service 2.4.0 py39h2bbff1b_0
[conda] mkl_fft 1.3.1 py39h277e83a_0
[conda] mkl_random 1.2.2 py39hf11a4ad_0
[conda] numpy 1.21.5 py39h7a0a035_3
[conda] numpy-base 1.21.5 py39hca35cd5_3
[conda] numpydoc 1.4.0 py39haa95532_0
[conda] torch 2.0.1 pypi_0 pypi
[conda] torchaudio 2.0.2 pypi_0 pypi
[conda] torchvision 0.15.2 pypi_0 pypi