Bump deepmd-kit[cpu] from 2.2.11 to 3.0.0

[dependabot]

Bumps deepmd-kit[cpu] from 2.2.11 to 3.0.0.

Release notes

Sourced from deepmd-kit[cpu]'s releases.

v3.0.0

DeePMD-kit v3: Multiple-backend Framework, DPA-2 Large Atomic Model, and Plugin Mechanisms

After eight months of public tests, we are excited to present the first stable version of DeePMD-kit v3, an advanced version that enables deep potential models with TensorFlow, PyTorch, or JAX backends. Additionally, DeePMD-kit v3 introduces support for the DPA-2 model, a novel architecture optimized for large atomic models. This release enhances plugin mechanisms, making integrating and developing new models easier.

Highlights

Multiple-backend framework: TensorFlow, PyTorch, and JAX support

DeePMD-kit v3 adds a versatile, pluggable framework providing consistent training and inference experience across multiple backends. Version 3.0.0 includes:

• TensorFlow backend: Known for its computational efficiency with a static graph design.
• PyTorch backend: A dynamic graph backend that simplifies model extension and development.
• DP backend: Built with NumPy and Array API, a reference backend for development without heavy deep-learning frameworks.
• JAX backend: Based on the DP backend via Array API, a static graph backend.

Features	TensorFlow	PyTorch	JAX	DP
Descriptor local frame	✅
Descriptor se_e2_a	✅	✅	✅	✅
Descriptor se_e2_r	✅	✅	✅	✅
Descriptor se_e3	✅	✅	✅	✅
Descriptor se_e3_tebd		✅	✅	✅
Descriptor DPA1	✅	✅	✅	✅
Descriptor DPA2		✅	✅	✅
Descriptor Hybrid	✅	✅	✅	✅
Fitting energy	✅	✅	✅	✅
Fitting dipole	✅	✅	✅	✅
Fitting polar	✅	✅	✅	✅
Fitting DOS	✅	✅	✅	✅
Fitting property		✅	✅	✅
ZBL	✅	✅	✅	✅
DPLR	✅
DPRc	✅	✅	✅	✅
Spin	✅	✅		✅
Gradient calculation	✅	✅	✅
Model training	✅	✅
Model compression	✅	✅
Python inference	✅	✅	✅	✅
C++ inference	✅	✅	✅

Critical features of the multiple-backend framework include the ability to:

• Train models using different backends with the same training data and input script, allowing backend switching based on your efficiency or convenience needs.

# Training a model using the TensorFlow backend
</tr></table> 

... (truncated)

Commits

• e695a91 merge devel to master (v3.0.0) (#4407)
• 2303ff0 fix(pt): optimize createNlistTensor (#4403)
• 5a93798 chore: use xp.take_along_axis if Array API version >=2024.12 (#4406)
• 2ce3276 fix: add numb_fparam & numb_aparam to dipole & polar fitting (#4405)
• d38c398 fix(pt): use eval mode in the Python interface (#4404)
• cb7a0d3 fix(pt): use eval mode in the C++ interface (#4402)
• 5d589da fix(pt/dp): make strip more efficient (#4400)
• 7bd2e5a Fix: always output weighted average error (#4401)
• d1712c9 Chore(doc): merge multitask training doc (#4395)
• c27f630 breaking(pt/dp):change env_protection for spin (#4394)
• Additional commits viewable in compare view

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