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[Bug]: DeepseekR1 model load fails with weights tied error #12541

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gdagur opened this issue Jan 29, 2025 · 1 comment
Open
1 task done

[Bug]: DeepseekR1 model load fails with weights tied error #12541

gdagur opened this issue Jan 29, 2025 · 1 comment
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@gdagur
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gdagur commented Jan 29, 2025 •
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Your current environment

Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

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: Could not collect
Libc version: glibc-2.35

Python version: 3.11.11 (main, Dec 4 2024, 08:55:07) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA H100 80GB HBM3
GPU 1: NVIDIA H100 80GB HBM3
GPU 2: NVIDIA H100 80GB HBM3
GPU 3: NVIDIA H100 80GB HBM3
GPU 4: NVIDIA H100 80GB HBM3
GPU 5: NVIDIA H100 80GB HBM3
GPU 6: NVIDIA H100 80GB HBM3
GPU 7: NVIDIA H100 80GB HBM3

Nvidia driver version: 550.144.03
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
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): 192
On-line CPU(s) list: 0-191
Vendor ID: AuthenticAMD
Model name: AMD EPYC 7R13 Processor
CPU family: 25
Model: 1
Thread(s) per core: 2
Core(s) per socket: 48
Socket(s): 2
Stepping: 1
BogoMIPS: 5300.00
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 nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch topoext perfctr_core invpcid_single ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 clzero xsaveerptr rdpru wbnoinvd arat npt nrip_save vaes vpclmulqdq rdpid
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 3 MiB (96 instances)
L1i cache: 3 MiB (96 instances)
L2 cache: 48 MiB (96 instances)
L3 cache: 384 MiB (12 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-47,96-143
NUMA node1 CPU(s): 48-95,144-191
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 Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Mitigation; safe RET, no microcode
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 always-on, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] flashinfer==0.1.6+cu124torch2.4
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] onnx==1.17.0
[pip3] onnxruntime==1.20.1
[pip3] pyzmq==26.2.0
[pip3] sentence-transformers==3.3.1
[pip3] torch==2.5.1+cu124
[pip3] torchvision==0.20.1+cu124
[pip3] transformers==4.45.2
[pip3] triton==3.1.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.7.0
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 0-47,96-143 0 N/A
GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 0-47,96-143 0 N/A
GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 0-47,96-143 0 N/A
GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 0-47,96-143 0 N/A
GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 48-95,144-191 1 N/A
GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 48-95,144-191 1 N/A
GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 48-95,144-191 1 N/A
GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X 48-95,144-191 1 N/A

Legend:

X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks

PYTORCH_LIBRARY_PATH=/usr/local/lib/python3.11/dist-packages/torch/lib
NVIDIA_VISIBLE_DEVICES=all
PYTORCH_PRECXX11=true
NVIDIA_REQUIRE_CUDA=cuda>=12.4 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526 brand=tesla,driver>=535,driver<536 brand=unknown,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=geforce,driver>=535,driver<536 brand=geforcertx,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=titan,driver>=535,driver<536 brand=titanrtx,driver>=535,driver<536
NCCL_VERSION=2.21.5-1
NVIDIA_DRIVER_CAPABILITIES=compute,utility
VLLM_WORKER_MULTIPROC_METHOD=spawn
NVIDIA_PRODUCT_NAME=CUDA
TORCH_NCCL_BLOCKING_WAIT=0
CUDA_VERSION=12.4.1
PYTORCH_FLAVOR=cu124-precxx11
PYTORCH_VERSION=2.5.1
PYTORCH_KERNEL_CACHE_PATH=/tmp/.cache
TORCH_NCCL_ASYNC_ERROR_HANDLING=1
TORCH_NCCL_AVOID_RECORD_STREAMS=1
LD_LIBRARY_PATH=/usr/local/lib/python3.11/dist-packages/cv2/../../lib64:/usr/local/lib/python3.11/dist-packages/nvidia/cudnn/lib/
VLLM_NO_USAGE_STATS=1
NCCL_CUMEM_ENABLE=0
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY

Model Input Dumps

No response

🐛 Describe the bug

Below model load code fails with tied model weights error while loading deepseekR1 model weights-
https://huggingface.co/deepseek-ai/DeepSeek-R1

model = LLM("/deepseekR1/model_weights", tensor_parallel_size=8, cpu_offload_gb=10, trust_remote_code=True)

Error stacktrace -

INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240] Traceback (most recent call last):
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/vllm/executor/multiproc_worker_utils.py", line 234, in _run_worker_process
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     output = run_method(worker, method, args, kwargs)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/vllm/utils.py", line 2208, in run_method
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     return func(*args, **kwargs)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]            ^^^^^^^^^^^^^^^^^^^^^
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     return func(*args, **kwargs)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]            ^^^^^^^^^^^^^^^^^^^^^
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/vllm/worker/worker.py", line 228, in determine_num_available_blocks
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     self.model_runner.profile_run()
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     return func(*args, **kwargs)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]            ^^^^^^^^^^^^^^^^^^^^^
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/vllm/worker/model_runner.py", line 1235, in profile_run
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     self._dummy_run(max_num_batched_tokens, max_num_seqs)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/vllm/worker/model_runner.py", line 1346, in _dummy_run
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     self.execute_model(model_input, kv_caches, intermediate_tensors)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     return func(*args, **kwargs)
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]            ^^^^^^^^^^^^^^^^^^^^^
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]   File "/usr/local/lib/python3.11/dist-packages/vllm/worker/model_runner_base.py", line 152, in _wrapper
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240]     raise type(err)(
INFO  PyProcess W-5226-model_code-stdout: (VllmWorkerProcess pid=5246) ERROR 01-29 09:20:28 multiproc_worker_utils.py:240] ValueError: Error in model execution (input dumped to /tmp/err_execute_model_input_20250129-092028.pkl): functional_call got multiple values for keys ['mlp.experts.e_score_correction_bias', 'mlp.gate.e_score_correction_bias'], which are tied. Consider using tie_weights=False

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@gdagur gdagur added the bug Something isn't working label Jan 29, 2025
@gdagur gdagur changed the title [Bug]: Deepseek model load is failing [Bug]: DeepseekR1 model load fails with error weights are tied Jan 29, 2025
@gdagur gdagur changed the title [Bug]: DeepseekR1 model load fails with error weights are tied [Bug]: DeepseekR1 model load fails with weights tied error Jan 29, 2025
@hrukalive
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Have the same issue with DeepSeek V3 (AWQ). I believe this is a problem with CPU offloading, hopefully this could be addressed soon.

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