Deepmd-kit

New features:
- Atom type embedding
- Model deviation for virial

Enhancement:
- Improved documentation
- Better support for dipole and polarizability learning
- bit operations to encode neighbor information
- MPI support for atomic model deviation 628
- UT for GPU code 569
- UT for model compression 586
- Test Lammps build 600

Bug fixings
- cuda memory access error 566
- relative force model deviation is not copied back at single precision 599
- correct way of allocating memory in float precision 612
- fix TB logdir remove bug 617
- Append out_file when lammps restarts 640

- Training and inference the dipole (vector).
- Split of training and validation dataset.

Enhancement:
- Strict argument check in the input script.
- Update readme for v2.0
- Auto conversion of input file to v2.0 compatibility

Bug fixings:
- Fix bugs of broken examples.

Bug fixing:
- Fix lammps memory leak when initialized pair_style deepmd for multiple times. 392
- Fix GPU memory issues. 393 407 424

Improvements:
- Compiling with Cuda 11.0 and 11.1 390

Bug fixings:
- Fix stress tensor bug of ASE interface 338
- Fix neighbor list bug that may cause inconsistent results between CPU and GPU 334

Bug fixing:
- Compulsory label requirement if the corresponding prefactor is set to non-zero. The current behavior is when then label is missing, the corresponding term does not appear in the loss function
- Optional requirement of `loss` in dipole and polarizability training

Improvement:
- Recommend consistent TensorFlow versions for python and C++ interfaces.

- Training parameters: Several training parameters have been updated. Original training data is splited into training data and validation data. Please read the document to apply the changes. Old styles can still work but are not recommended.
- Model inference: Old models trained by v1 will not work in v2. Run `dp convert-from` to convert old models to v2.
- Python interface: `deepmd.DeepPot` has been moved to `deepmd.infer.DeepPot`. <!-- add an alias? -->
- C++ interface: `NNPInter` has been renamed to `deepmd::DeepPot` and `NNPInter.h` has been renamed to `DeepPot.h`. Use `-ldeepmd_cc` to link instead.

New features
- [Model compression](https://arxiv.org/abs/2107.02103) (#350 586 610 921 948 956 1000 1008 1020 1043)
- Parallel training (892 905 913 1030 1032) (Bytedance)
- ROCm device support (656 )
- New descriptor: three body embedding (`se_e3`)
- Hybridization of descriptors (`hybrid`)
- Type embedding
- Training and inference the dipole (vector) and polarizability (matrix). (495 538 927)
- Support derivatives of the tensor properties. (805)
- Split of training and validation dataset.
- Model deviation for virial
- Add subcommand and python interface to calculate model-deviation (715)
- Automatically determine the sel from the training data. (831)
- Building with lammps with plugin mode (930 945)

Performance improvement:
- More efficient training: all customized OPs are implemented with GPU.
- MPI support for atomic model deviation 628
- speedup ROCm kernels which use atomicAdd (809 815 ) (from ByteDance)
- speedup CUDA kernels (use atomicAdd inside) by reducing the global memory write (811)
- speedup tabulate cuda kernel by reducing shm using (830) (Bytedance)
- speedup `format_nlist_b` (832 845)
- speedup `scan_nlist` kernel (1028)

Enhancements
- Strict argument check in the input script.
- Auto conversion of input file to v2.0 compatibility
- Append out_file when lammps restarts 640
- Document and examples for the C++ interface 652 663
- Instructions for the i-pi 660
- Document for the network size and sel 657
- Use fmod to wrap the coord of atoms (solve slow PBC) (741)
- bit operations to encode neighbor information
- add CUDA/ROCM buidling documents (739)
- add type-embedding developer doc (762 967)
- add model compression support for models with exclude_types feature (754)
- improve the doc and user interface of model compression (772)
- support converting models generated in v1.3 to 2.0 compatibility (725)
- give a default value to T and convert models from v1.2 to 2.0 compatibility (789)
- improved documents for conda (798 925)
- throw a message if tf runtime is incompatible (797)
- capture OOM and print debug message (801)
- add message for DecodeError raised when using model compression (839)
- Passing error to TF instead of exit (918)
- refactor docs (952)
- add an example of `nopbc` and related docs (994)
- add `dp --version` (995)
- add the argument `tensorboard_freq` to control sampling ratio during training. (996)
- add sphinx plugins `viewcode` and `intersphinx` (997)
- generate Python API document automatically (998)
- give a clear message if `model.get_ntypes()<data.get_ntypes()` (1016)
- add docstring for `descrpt/se_e2_a` (1017)
- add docstring for `fit/ener` (1024)
- add `InputNlist` into API doc (1009)
- save checkpoint files with step and keep recent files (1031)


Improvement of the code for developers
- Support version of the model. Easily check model compatability
- Clear and pythonic python interface
- C++ lib that can be tested independently
- C++ API that can be tested independently
- OP supports multi-device.
- Added `deepmd` namespace for the C++ API
- UT for Cuda/ROCm code (569)
- UT for model compression (586)
- UT for prod_force/virial ops (703 741)
- CI test Lammps build (600)
- allow c++ tests to run without internet (785)
- build low and high precision at the same time (879)
- support to specify CUDA/ROCm root in python pkg building (834) (Bytedance)
- use cached Session to speed up py tests (833)
- remove cub include for CUDA>=11 (866)
- Add Errcheck after every kernel function runs And merge redundant code (855)
- adapt changes to auditwheel directory in manylinux (889)
- enhance the cli to generate doc json file (891)
- raise warning before training if `sel` is not enough (914)
- make native MD compatible with v2.0 (950)
- fix type hints and add doc for `exclude_types` (1005)
- use TF's built-in method to get numpy dtype (1035)


Bug fixings:
- Remove `using namespace std`. Solve compiling compatability problem.
- `cuda` memory access error 566
- Relative force model deviation is not copied back at single precision 599
- Correct way of allocating memory in float precision 612
- Fix TB logdir remove bug 617
- Illegal nlist 680
- Bug in `prod_virial_grad` that causes wrong results when training with virials 685
- Uniform random seed 691
- Illegal nlist 680
- Bug in `prod_virial_grad` that causes wrong results when training with virials 685
- Uniform random seed 691
- fix bug of adding int to a None random seed (705)
- reuse the zero layer rather than building a new one (714)
- fix bug in CI (739)
- fix bug 824 and Synchronize updates to CUDA cod (828)
- Fix the empty neighbor distance array in neighbor_stat.py (882)
- fix InvalidArgumentError caused by zero sel and optimize zero matrix (900)
- fix 'NoneType' has no len() in auto_sel (911)
- set input `DeepmdData.type_map` to input `type_map` (924)
- Fix member declartion of `deepmd` and `deepmd.entrypoints`. (922)
- add aliases to Arguments (933)
- fix bug of gelu activation function (939)
- convert `decay_rate` to `stop_lr` from old inputs (949)
- only enable link what you use on GNU compilers (962)
- Do not find protobuf for python (963)
- fix an error in stress by ase interface (964)
- remove bare `except` and limit the `try` clause (977)
- fix python cmake error (976)
- Instantiate RunOptions first when training. (1019)
- Fix complier type in cmake: `CMAKE_COMPILER_IS_GNUCXX` (1038)
- other cleanups of the code (968 970 975 999 1004 1002 1001 1010 1014 1012 1011 1021 1036 1037)


Contributors
* Han Bao
* Roberto Car
* Junhan Chang
* Yixiao Chen
* Ye Ding
* Weinan E
* Jiequn Han
* Li'ang Huang
* Weile Jia
* Zeyu Li
* Ziyao Li
* Yinnian Lin
* Yihao Liu
* Xinzijian Liu
* Denghui Lu
* Marián Rynik
* Shaochen Shi
* Ping Tuo
* Bo Wang
* Haidi Wang
* Han Wang
* Yingze Wang
* Yu Xia
* Fengbo Yuan
* Jiabin Yang
* Haotian Ye
* Jinzhe Zeng
* Duo Zhang
* Linfeng Zhang
* Yuzhi Zhang