non-persistent simple example does not work about deepspeed-mii HOT 5 OPEN

I cloned the cutlass repository and updated the CUTLASS_PATH so the [WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH is now gone
But I still get RuntimeError: Error building extension 'ragged_device_ops'

The error starts with this:
Building extension module ragged_device_ops...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] c++ -MMD -MF blocked_flash.o.d -DTORCH_EXTENSION_NAME=ragged_device_ops -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/includes -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/atom_builder -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/blocked_flash -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/embed -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/includes -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/linear_blocked_kv_rotary -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/logits_gather -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/moe_gather -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/moe_scatter -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/ragged_helpers -I/deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/top_k_gating -isystem /deepspeed/dsenv/lib/python3.10/site-packages/torch/include -isystem /deepspeed/dsenv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /deepspeed/dsenv/lib/python3.10/site-packages/torch/include/TH -isystem /deepspeed/dsenv/lib/python3.10/site-packages/torch/include/THC -isystem /Linux_x86_64/24.1/compilers/include -isystem /usr/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++17 -O3 -std=c++17 -g -Wno-reorder -DBF16_AVAILABLE -c /deepspeed/dsenv/lib/python3.10/site-packages/deepspeed/inference/v2/kernels/ragged_ops/blocked_flash/blocked_flash.cpp -o blocked_flash.o
FAILED: blocked_flash.o

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Hi @mohbay - can you share your ds_report? My guess is you don't have the deepspeed-kernels/cutlass kernels installed for those ops to build.

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Hi @loadams
This might be related to cutlass indeed.
Thanks a lot. Below is the ds_report

[INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.1), only 1.0.0 is known to be compatible

DeepSpeed C++/CUDA extension op report

NOTE: Ops not installed will be just-in-time (JIT) compiled at
runtime if needed. Op compatibility means that your system
meet the required dependencies to JIT install the op.

JIT compiled ops requires ninja
ninja .................. [OKAY]

op name ................ installed .. compatible

async_io ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
cpu_adam ............... [NO] ....... [OKAY]
cpu_adagrad ............ [NO] ....... [OKAY]
cpu_lion ............... [NO] ....... [OKAY]
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
evoformer_attn ......... [NO] ....... [NO]
fp_quantizer ........... [NO] ....... [OKAY]
fused_lamb ............. [NO] ....... [OKAY]
fused_lion ............. [NO] ....... [OKAY]
inference_core_ops ..... [NO] ....... [OKAY]
cutlass_ops ............ [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
ragged_device_ops ...... [NO] ....... [OKAY]
ragged_ops ............. [NO] ....... [OKAY]
random_ltd ............. [NO] ....... [OKAY]
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.1), only 1.0.0 is known to be compatible
sparse_attn ............ [NO] ....... [NO]
spatial_inference ...... [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]

DeepSpeed general environment info:
torch install path ............... ['deepspeed/dsenv/lib/python3.10/site-packages/torch']
torch version .................... 2.3.1+cu121
deepspeed install path ........... ['deepspeed/dsenv/lib/python3.10/site-packages/deepspeed']
deepspeed info ................... 0.14.4, unknown, unknown
torch cuda version ............... 12.1
torch hip version ................ None
nvcc version ..................... 12.3
deepspeed wheel compiled w. ...... torch 2.3, cuda 12.1
shared memory (/dev/shm) size .... 125.80 GB

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Can you share your pip list as well? Or have you installed deepspeed-kernels?

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deepspeed-kernels is installed. Here is the pip list.

Package Version

aniso8601 9.0.1
annotated-types 0.7.0
asyncio 3.4.3
blinker 1.8.2
certifi 2024.7.4
charset-normalizer 3.3.2
click 8.1.7
cmake 3.30.0
deepspeed 0.14.4
deepspeed-kernels 0.0.1.dev1698255861
deepspeed-mii 0.2.3
filelock 3.15.4
Flask 3.0.3
Flask-RESTful 0.3.10
fsspec 2024.6.1
grpcio 1.64.1
grpcio-tools 1.64.1
hjson 3.1.0
huggingface-hub 0.23.5
idna 3.7
itsdangerous 2.2.0
Jinja2 3.1.4
MarkupSafe 2.1.5
mpmath 1.3.0
networkx 3.3
ninja 1.11.1.1
numpy 1.26.4
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu12 12.1.0.106
nvidia-ml-py 12.555.43
nvidia-nccl-cu12 2.20.5
nvidia-nvjitlink-cu12 12.5.82
nvidia-nvtx-cu12 12.1.105
packaging 24.1
pillow 10.4.0
pip 22.0.2
protobuf 5.27.2
psutil 6.0.0
py-cpuinfo 9.0.0
pydantic 2.8.2
pydantic_core 2.20.1
pynvml 11.5.2
pytz 2024.1
PyYAML 6.0.1
pyzmq 26.0.3
regex 2024.5.15
requests 2.32.3
safetensors 0.4.3
setuptools 59.6.0
six 1.16.0
sympy 1.13.0
tokenizers 0.19.1
torch 2.3.1
tqdm 4.66.4
transformers 4.41.2
triton 2.3.1
typing_extensions 4.12.2
ujson 5.10.0
urllib3 2.2.2
Werkzeug 3.0.3
zmq 0.0.0

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