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learning-at-home / hivemind

Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
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pydantic < 2.0.0 is starting to conflict with other dependencies #597

Closed Vectorrent closed 3 weeks ago

Vectorrent commented 12 months ago

Describe the bug The version constraint of pydantic < 2.0.0 is conflicting with other dependencies.

To Reproduce You could try to install both hivemind and horde-sdk with pip. It will fail with dependency conflicts. If you try to install horde-sdk in a venv, it breaks hivemind:

vtx-lab-1  |   File "/usr/local/lib/python3.10/dist-packages/hivemind/dht/schema.py", line 168, in __get_validators__
vtx-lab-1  |     yield from super().__get_validators__()
vtx-lab-1  | AttributeError: 'super' object has no attribute '__get_validators__'

Note At some point, I may attempt the fix myself. The problem is, I've never used pydantic, and I don't know what kind of cascading effects it may have on hivemind's dependent packages. For now, I'm stuck - and I would definitely appreciate a fix from someone else if possible.

Environment

OS: Ubuntu 22.04.3 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Clang version: 14.0.0-1ubuntu1.1 CMake version: Could not collect Libc version: glibc-2.35

Python version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime) Python platform: Linux-6.5.9-arch2-1-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: 12.2.140 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1070 Nvidia driver version: 535.113.01 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: 39 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 8 On-line CPU(s) list: 0-7 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-4790K CPU @ 4.00GHz CPU family: 6 Model: 60 Thread(s) per core: 2 Core(s) per socket: 4 Socket(s): 1 Stepping: 3 CPU max MHz: 4400.0000 CPU min MHz: 800.0000 BogoMIPS: 7998.77 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt dtherm ida arat pln pts md_clear flush_l1d L1d cache: 128 KiB (4 instances) L1i cache: 128 KiB (4 instances) L2 cache: 1 MiB (4 instances) L3 cache: 8 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-7 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported Vulnerability L1tf: Mitigation; PTE Inversion Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Meltdown: Mitigation; PTI Vulnerability Mmio stale data: Unknown: No mitigations Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl 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: Mitigation; Microcode Vulnerability Tsx async abort: Not affected

Versions of relevant libraries: [pip3] numpy==1.26.2 [pip3] onnxruntime==1.16.2 [pip3] pytorch-lightning==2.1.2 [pip3] pytorch_optimizer==2.12.0 [pip3] torch==2.1.1 [pip3] torchmetrics==1.2.0 [pip3] torchvision==0.16.1 [pip3] triton==2.1.0 [conda] Could not collect

gaborkukucska commented 5 months ago

Hello :) Any chance to get pydantic 2+ working with Hivemind any time soon?

EDIT: pydantic < 2 is breaking other packages like LiteLLM I'm trying to use Petals with.

Vectorrent commented 3 weeks ago

The related PR was recently merged, upgrading pydantic to a newer version. We can probably close this now.