Error: stress property not implemented

mettler commented 2 weeks ago

Hi! I'm trying to run a hello world:

from fairchem.core import OCPCalculator
from ase.optimize import FIRE # Import your optimizer of choice
from ase.filters import FrechetCellFilter  # to include cell relaxations
from ase.io import read

from fairchem.core.datasets import AseDBDataset

dataset_path = "validation_models/rattled-relax"
config_kwargs = {} # see tutorial on additional configuration

dataset = AseDBDataset(config=dict(src=dataset_path, **config_kwargs))
atoms = dataset.get_atoms(0)

calc = OCPCalculator(checkpoint_path="eqV2_86M_omat_mp_salex.pt")
atoms.calc = calc

dyn = FIRE(FrechetCellFilter(atoms))
dyn.run(fmax=0.05)

And getting the following error:

/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/scn/spherical_harmonics.py:23: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  _Jd = torch.load(os.path.join(os.path.dirname(__file__), "Jd.pt"))
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/escn/so3.py:23: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  _Jd = torch.load(os.path.join(os.path.dirname(__file__), "Jd.pt"))
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/escn/so3_exportable.py:17: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  __Jd = torch.load(os.path.join(os.path.dirname(__file__), "Jd.pt"))
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/equiformer_v2/wigner.py:10: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  _Jd = torch.load(os.path.join(os.path.dirname(__file__), "Jd.pt"))
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/equiformer_v2/layer_norm.py:75: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  @torch.cuda.amp.autocast(enabled=False)
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/equiformer_v2/layer_norm.py:175: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  @torch.cuda.amp.autocast(enabled=False)
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/equiformer_v2/layer_norm.py:263: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  @torch.cuda.amp.autocast(enabled=False)
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/models/equiformer_v2/layer_norm.py:357: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  @torch.cuda.amp.autocast(enabled=False)
/Users/mm/fairchem/lib/python3.12/site-packages/fairchem/core/common/relaxation/ase_utils.py:150: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=torch.device("cpu"))
WARNING:root:No seed has been set in modelcheckpoint or OCPCalculator! Results may not be reproducible on re-run
Traceback (most recent call last):
  File "/Users/mm/fairchem/helloworld.py", line 22, in <module>
    dyn.run(fmax=0.05)
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/optimize/optimize.py", line 430, in run
    return Dynamics.run(self, steps=steps)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/optimize/optimize.py", line 275, in run
    for converged in Dynamics.irun(self, steps=steps):
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/optimize/optimize.py", line 225, in irun
    self.optimizable.get_forces()
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/filters.py", line 29, in get_forces
    return self.filterobj.get_forces()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/filters.py", line 612, in get_forces
    stress = self.atoms.get_stress(**kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/atoms.py", line 844, in get_stress
    stress = self._calc.get_stress(self)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/calculators/abc.py", line 33, in get_stress
    return self.get_property('stress', atoms)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/mm/fairchem/lib/python3.12/site-packages/ase/calculators/calculator.py", line 517, in get_property
    raise PropertyNotImplementedError(
ase.calculators.calculator.PropertyNotImplementedError: stress property not implemented

Is there something else I should be doing here or is this an issue somewhere in ase?

lbluque commented 2 weeks ago

Hi @mettler,

Are you using the code in this branch? https://github.com/FAIR-Chem/fairchem/tree/omat24

mettler commented 2 weeks ago

Yes!

(fairchem) mm@mm fairchem % python3 -m pip install fairchem-core                                       
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corinwagen commented 1 week ago

This is causing issues for us too — will stress make it into the main installable branch at some point?

Seems like it should be a simple enough autodiff, right?

lbluque commented 1 week ago

Hi @mettler and @corinwagen,

Direct install from PyPi (ie pip install fairchem-core) will not come with the stress calculations enabled since we have not released this functionality yet. @corinwagen we are working on adding it to the main branch and making a release ASAP, but we need to make sure that the code is reviewed and tested.

For now I recommend cloning the repository and installing from source using this branch

corinwagen commented 1 week ago

Thanks for the update! We'll hang tight and wait for the release, since pixi gets a little complicated/unstable with specific branch pinning.

Appreciate all the hard work!

yumxcode commented 3 days ago

there is another error. I have done the following steps：

git clone https://github.com/FAIR-Chem/fairchem.git cd fairchem git switch omat24 pip install -e packages/fairchem-core

the error is Obtaining file:///home/yumx/env/fairchem/packages/fairchem-core Installing build dependencies ... done Checking if build backend supports build_editable ... done Getting requirements to build editable ... done Installing backend dependencies ... done Preparing editable metadata (pyproject.toml) ... error error: subprocess-exited-with-error

× Preparing editable metadata (pyproject.toml) did not run successfully. │ exit code: 1 ╰─> [52 lines of output] Traceback (most recent call last): File "/root/anaconda3/envs/omat24/lib/python3.11/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 167, in prepare_metadata_for_build_editable hook = backend.prepare_metadata_for_build_editable ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ AttributeError: module 'hatchling.build' has no attribute 'prepare_metadata_for_build_editable'

  During handling of the above exception, another exception occurred:

  Traceback (most recent call last):
    File "/root/anaconda3/envs/omat24/lib/python3.11/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in <module>
      main()
    File "/root/anaconda3/envs/omat24/lib/python3.11/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
      json_out['return_val'] = hook(**hook_input['kwargs'])
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/root/anaconda3/envs/omat24/lib/python3.11/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 176, in prepare_metadata_for_build_editable
      whl_basename = build_hook(metadata_directory, config_settings)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatchling/build.py", line 83, in build_editable
      return os.path.basename(next(builder.build(directory=wheel_directory, versions=['editable'])))
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatchling/builders/plugin/interface.py", line 90, in build
      self.metadata.validate_fields()
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatchling/metadata/core.py", line 265, in validate_fields
      _ = self.version
          ^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatchling/metadata/core.py", line 149, in version
      self._version = self._get_version()
                      ^^^^^^^^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatchling/metadata/core.py", line 244, in _get_version
      core_metadata = self.core
                      ^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatchling/metadata/core.py", line 196, in core
      metadata_hook.update(self.core_raw_metadata)
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatch_fancy_pypi_readme/hooks.py", line 23, in update
      config = load_and_validate_config(self.config)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatch_fancy_pypi_readme/_config.py", line 38, in load_and_validate_config
      fragments = _load_fragments(config.get("fragments"))
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatch_fancy_pypi_readme/_config.py", line 83, in _load_fragments
      frags.append(frag.from_config(frag_cfg))
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/tmp/pip-build-env-rj41pgts/overlay/lib/python3.11/site-packages/hatch_fancy_pypi_readme/_fragments.py", line 77, in from_config
      contents = path.read_text(encoding="utf-8")
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/root/anaconda3/envs/omat24/lib/python3.11/pathlib.py", line 1058, in read_text
      with self.open(mode='r', encoding=encoding, errors=errors) as f:
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/root/anaconda3/envs/omat24/lib/python3.11/pathlib.py", line 1044, in open
      return io.open(self, mode, buffering, encoding, errors, newline)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  NotADirectoryError: [Errno 20] Not a directory: 'src/fairchem/core/README.md'
  [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip. hint: See above for details.

lbluque commented 2 days ago

Hi @yumxcode,

Are you trying to install on a windows machine?

If so please follow the windows specific install instructions in the documentation to allow symlinks.

yumxcode commented 2 days ago

No, I actually installed it on a linux system( ubuntu 22.04 )

FAIR-Chem / fairchem

Error: stress property not implemented #888