openforcefield / openff-toolkit

The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io
http://openforcefield.org
MIT License
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Partial charge methods fail in clean environment #1911

Open slochower opened 4 months ago

slochower commented 4 months ago

Describe the bug In a new, clean OpenFF environment on an x86-64 Mac (14.4.1), partial charge methods fail. This is either from antechamber or possibly sqm and probably related to issues that I've seen @mattwthompson talking about with the Amber folks.

For this test script:

from openff.toolkit.utils import get_data_file_path
from openff.toolkit.topology import Molecule, Topology
from openff.toolkit.typing.engines.smirnoff import ForceField

# This prepared PDB file from the toolkit's test suite is a box of solvents
pdb_path = get_data_file_path(
    "systems/packmol_boxes/propane_methane_butanol_0.2_0.3_0.5.pdb"
)
molecules = [Molecule.from_smiles(smi) for smi in ["CCC", "C", "CCCCO"]]

# The OpenFF Toolkit can directly read PDB files!
topology = Topology.from_pdb(pdb_path, unique_molecules=molecules)

# Construct the Interchange with the OpenFF "Sage" force field
interchange = ForceField("openff-2.0.0.offxml").create_interchange(topology)

I'm seeing:

 ToolkitWrapper around The RDKit version 2024.03.5 <class 'openff.toolkit.utils.exceptions.ChargeMethodUnavailableError'> : partial_charge_method 'am1bcc' is not available from RDKitToolkitWrapper. Available charge methods are {'mmff94': {}, 'gasteiger': {}}
 ToolkitWrapper around AmberTools version 23.6 <class 'subprocess.CalledProcessError'> : Command '['antechamber', '-i', 'molecule.sdf', '-fi', 'sdf', '-o', 'charged.mol2', '-fo', 'mol2', '-pf', 'yes', '-dr', 'n', '-c', 'bcc', '-nc', '0.0']' returned non-zero exit status 1.
 ToolkitWrapper around Built-in Toolkit version None <class 'openff.toolkit.utils.exceptions.ChargeMethodUnavailableError'> : Partial charge method "am1bcc"" is not supported by the Built-in toolkit. Available charge methods are {'zeros': {'rec_confs': 0, 'min_confs': 0, 'max_confs': 0}, 'formal_charge': {'rec_confs': 0, 'min_confs': 0, 'max_confs': 0}}

The test cases also fail.

To Reproduce

  1. conda create --name openff-clean
  2. mamba install -c conda-forge openff-toolkit
  3. Save snippet as tmp.py
  4. python tmp.py

Output

/Users/slochowe/miniforge3/envs/openff-clean/bin/wrapped_progs/antechamber: Fatal Error!
Cannot properly run "/Users/slochowe/miniforge3/envs/openff-clean/bin/sqm -O -i sqm.in -o sqm.out".
Traceback (most recent call last):
  File "/Users/slochowe/tmp/tmp.py", line 15, in <module>
    interchange = ForceField("openff-2.0.0.offxml").create_interchange(topology)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/utilities/utilities.py", line 80, in wrapper
    return function(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/toolkit/typing/engines/smirnoff/forcefield.py", line 1252, in create_interchange
    return Interchange.from_smirnoff(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/components/interchange.py", line 268, in from_smirnoff
    return _create_interchange(
           ^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_create.py", line 112, in _create_interchange
    _electrostatics(
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_create.py", line 267, in _electrostatics
    "Electrostatics": SMIRNOFFElectrostaticsCollection.create(
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_nonbonded.py", line 449, in create
    handler.store_matches(
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_nonbonded.py", line 860, in store_matches
    matches, potentials = self._find_reference_matches(
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_nonbonded.py", line 718, in _find_reference_matches
    ) = cls._find_charge_model_matches(
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_nonbonded.py", line 654, in _find_charge_model_matches
    partial_charges = cls._compute_partial_charges(
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/interchange/smirnoff/_nonbonded.py", line 469, in _compute_partial_charges
    molecule.assign_partial_charges(method)
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/toolkit/topology/molecule.py", line 2677, in assign_partial_charges
    toolkit_registry.call(
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/toolkit/utils/toolkit_registry.py", line 280, in call
    raise ValueError(msg)
ValueError: No registered toolkits can provide the capability "assign_partial_charges" for args "()" and kwargs "{'molecule': Molecule with name '' and SMILES '[H][O][C]([H])([H])[C]([H])([H])[C]([H])([H])[C]([H])([H])[H]', 'partial_charge_method': 'am1bcc', 'use_conformers': None, 'strict_n_conformers': False, 'normalize_partial_charges': True, '_cls': <class 'openff.toolkit.topology.molecule.Molecule'>}"
Available toolkits are: [ToolkitWrapper around The RDKit version 2024.03.5, ToolkitWrapper around AmberTools version 23.6, ToolkitWrapper around Built-in Toolkit version None]
 ToolkitWrapper around The RDKit version 2024.03.5 <class 'openff.toolkit.utils.exceptions.ChargeMethodUnavailableError'> : partial_charge_method 'am1bcc' is not available from RDKitToolkitWrapper. Available charge methods are {'mmff94': {}, 'gasteiger': {}}
 ToolkitWrapper around AmberTools version 23.6 <class 'subprocess.CalledProcessError'> : Command '['antechamber', '-i', 'molecule.sdf', '-fi', 'sdf', '-o', 'charged.mol2', '-fo', 'mol2', '-pf', 'yes', '-dr', 'n', '-c', 'bcc', '-nc', '0.0']' returned non-zero exit status 1.
 ToolkitWrapper around Built-in Toolkit version None <class 'openff.toolkit.utils.exceptions.ChargeMethodUnavailableError'> : Partial charge method "am1bcc"" is not supported by the Built-in toolkit. Available charge methods are {'zeros': {'rec_confs': 0, 'min_confs': 0, 'max_confs': 0}, 'formal_charge': {'rec_confs': 0, 'min_confs': 0, 'max_confs': 0}}
`conda list` ``` āÆ conda list # packages in environment at /Users/slochowe/miniforge3/envs/openff-clean: # # Name Version Build Channel ambertools 23.6 cuda_None_nompi_py312hc98840c_105 conda-forge amberutils 21.0 pypi_0 pypi annotated-types 0.7.0 pyhd8ed1ab_0 conda-forge anyio 4.4.0 pyhd8ed1ab_0 conda-forge appnope 0.1.4 pyhd8ed1ab_0 conda-forge argon2-cffi 23.1.0 pyhd8ed1ab_0 conda-forge argon2-cffi-bindings 21.2.0 py312h104f124_4 conda-forge arpack 3.9.1 nompi_hf81eadf_101 conda-forge arrow 1.3.0 pyhd8ed1ab_0 conda-forge asttokens 2.4.1 pyhd8ed1ab_0 conda-forge astunparse 1.6.3 pyhd8ed1ab_0 conda-forge async-lru 2.0.4 pyhd8ed1ab_0 conda-forge attrs 23.2.0 pyh71513ae_0 conda-forge babel 2.14.0 pyhd8ed1ab_0 conda-forge beautifulsoup4 4.12.3 pyha770c72_0 conda-forge bleach 6.1.0 pyhd8ed1ab_0 conda-forge blosc 1.21.6 h7d75f6d_0 conda-forge brotli 1.1.0 h0dc2134_1 conda-forge brotli-bin 1.1.0 h0dc2134_1 conda-forge brotli-python 1.1.0 py312heafc425_1 conda-forge bson 0.5.9 py_0 conda-forge bzip2 1.0.8 hfdf4475_7 conda-forge c-ares 1.32.3 h51dda26_0 conda-forge c-blosc2 2.15.0 hb9356d3_1 conda-forge ca-certificates 2024.7.4 h8857fd0_0 conda-forge cached-property 1.5.2 hd8ed1ab_1 conda-forge cached_property 1.5.2 pyha770c72_1 conda-forge cachetools 5.4.0 pyhd8ed1ab_0 conda-forge cairo 1.18.0 h37bd5c4_3 conda-forge certifi 2024.7.4 pyhd8ed1ab_0 conda-forge cffi 1.16.0 py312h38bf5a0_0 conda-forge chardet 5.2.0 py312hb401068_1 conda-forge charset-normalizer 3.3.2 pyhd8ed1ab_0 conda-forge colorama 0.4.6 pyhd8ed1ab_0 conda-forge comm 0.2.2 pyhd8ed1ab_0 conda-forge contourpy 1.2.1 py312h9230928_0 conda-forge cycler 0.12.1 pyhd8ed1ab_0 conda-forge debugpy 1.8.2 py312h28f332c_0 conda-forge decorator 5.1.1 pyhd8ed1ab_0 conda-forge defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge edgembar 0.2 pypi_0 pypi entrypoints 0.4 pyhd8ed1ab_0 conda-forge exceptiongroup 1.2.2 pyhd8ed1ab_0 conda-forge executing 2.0.1 pyhd8ed1ab_0 conda-forge expat 2.6.2 h73e2aa4_0 conda-forge fftw 3.3.10 nompi_h292e606_110 conda-forge font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge font-ttf-inconsolata 3.000 h77eed37_0 conda-forge font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge font-ttf-ubuntu 0.83 h77eed37_2 conda-forge fontconfig 2.14.2 h5bb23bf_0 conda-forge fonts-conda-ecosystem 1 0 conda-forge fonts-conda-forge 1 0 conda-forge fonttools 4.53.1 py312hbd25219_0 conda-forge fqdn 1.5.1 pyhd8ed1ab_0 conda-forge freetype 2.12.1 h60636b9_2 conda-forge freetype-py 2.3.0 pyhd8ed1ab_0 conda-forge greenlet 3.0.3 py312hede676d_0 conda-forge h11 0.14.0 pyhd8ed1ab_0 conda-forge h2 4.1.0 pyhd8ed1ab_0 conda-forge hdf4 4.2.15 h8138101_7 conda-forge hdf5 1.14.3 nompi_h687a608_105 conda-forge hpack 4.0.0 pyh9f0ad1d_0 conda-forge httpcore 1.0.5 pyhd8ed1ab_0 conda-forge httpx 0.27.0 pyhd8ed1ab_0 conda-forge hyperframe 6.0.1 pyhd8ed1ab_0 conda-forge icu 75.1 h120a0e1_0 conda-forge idna 3.7 pyhd8ed1ab_0 conda-forge importlib-metadata 8.2.0 pyha770c72_0 conda-forge importlib_metadata 8.2.0 hd8ed1ab_0 conda-forge importlib_resources 6.4.0 pyhd8ed1ab_0 conda-forge ipykernel 6.29.5 pyh57ce528_0 conda-forge ipython 8.26.0 pyh707e725_0 conda-forge ipywidgets 8.1.3 pyhd8ed1ab_0 conda-forge isoduration 20.11.0 pyhd8ed1ab_0 conda-forge jedi 0.19.1 pyhd8ed1ab_0 conda-forge jinja2 3.1.4 pyhd8ed1ab_0 conda-forge joblib 1.4.2 pyhd8ed1ab_0 conda-forge json5 0.9.25 pyhd8ed1ab_0 conda-forge jsonpointer 3.0.0 py312hb401068_0 conda-forge jsonschema 4.23.0 pyhd8ed1ab_0 conda-forge jsonschema-specifications 2023.12.1 pyhd8ed1ab_0 conda-forge jsonschema-with-format-nongpl 4.23.0 hd8ed1ab_0 conda-forge jupyter-lsp 2.2.5 pyhd8ed1ab_0 conda-forge jupyter_client 8.6.2 pyhd8ed1ab_0 conda-forge jupyter_core 5.7.2 py312hb401068_0 conda-forge jupyter_events 0.10.0 pyhd8ed1ab_0 conda-forge jupyter_server 2.14.2 pyhd8ed1ab_0 conda-forge jupyter_server_terminals 0.5.3 pyhd8ed1ab_0 conda-forge jupyterlab 4.2.4 pyhd8ed1ab_0 conda-forge jupyterlab_pygments 0.3.0 pyhd8ed1ab_1 conda-forge jupyterlab_server 2.27.3 pyhd8ed1ab_0 conda-forge jupyterlab_widgets 3.0.11 pyhd8ed1ab_0 conda-forge khronos-opencl-icd-loader 2023.04.17 h37ebe6b_1 conda-forge kiwisolver 1.4.5 py312h49ebfd2_1 conda-forge krb5 1.21.3 h37d8d59_0 conda-forge lcms2 2.16 ha2f27b4_0 conda-forge lerc 4.0.0 hb486fe8_0 conda-forge libaec 1.1.3 h73e2aa4_0 conda-forge libblas 3.9.0 22_osx64_openblas conda-forge libboost 1.84.0 hcca3243_4 conda-forge libboost-python 1.84.0 py312h44e70fa_4 conda-forge libbrotlicommon 1.1.0 h0dc2134_1 conda-forge libbrotlidec 1.1.0 h0dc2134_1 conda-forge libbrotlienc 1.1.0 h0dc2134_1 conda-forge libcblas 3.9.0 22_osx64_openblas conda-forge libcurl 8.9.0 hfcf2730_0 conda-forge libcxx 18.1.8 hef8daea_0 conda-forge libdeflate 1.20 h49d49c5_0 conda-forge libedit 3.1.20191231 h0678c8f_2 conda-forge libev 4.33 h10d778d_2 conda-forge libexpat 2.6.2 h73e2aa4_0 conda-forge libffi 3.4.2 h0d85af4_5 conda-forge libgfortran 5.0.0 13_2_0_h97931a8_3 conda-forge libgfortran5 13.2.0 h2873a65_3 conda-forge libglib 2.80.3 h736d271_1 conda-forge libiconv 1.17 hd75f5a5_2 conda-forge libintl 0.22.5 h5ff76d1_2 conda-forge libjpeg-turbo 3.0.0 h0dc2134_1 conda-forge liblapack 3.9.0 22_osx64_openblas conda-forge libnetcdf 4.9.2 nompi_h7334405_114 conda-forge libnghttp2 1.58.0 h64cf6d3_1 conda-forge libopenblas 0.3.27 openmp_h8869122_1 conda-forge libpng 1.6.43 h92b6c6a_0 conda-forge libpq 16.3 h4501773_0 conda-forge librdkit 2024.03.5 hbc19afa_1 conda-forge libsodium 1.0.18 hbcb3906_1 conda-forge libsqlite 3.46.0 h1b8f9f3_0 conda-forge libssh2 1.11.0 hd019ec5_0 conda-forge libtiff 4.6.0 h129831d_3 conda-forge libwebp-base 1.4.0 h10d778d_0 conda-forge libxcb 1.16 h0dc2134_0 conda-forge libxml2 2.12.7 heaf3512_4 conda-forge libzip 1.10.1 hc158999_3 conda-forge libzlib 1.3.1 h87427d6_1 conda-forge llvm-openmp 18.1.8 h15ab845_0 conda-forge lz4-c 1.9.4 hf0c8a7f_0 conda-forge markupsafe 2.1.5 py312h41838bb_0 conda-forge matplotlib-base 3.9.1 py312h0d5aeb7_0 conda-forge matplotlib-inline 0.1.7 pyhd8ed1ab_0 conda-forge mda-xdrlib 0.2.0 pyhd8ed1ab_0 conda-forge mdtraj 1.10.0 py312h00f8f5a_0 conda-forge mistune 3.0.2 pyhd8ed1ab_0 conda-forge mmpbsa-py 16.0 pypi_0 pypi munkres 1.1.4 pyh9f0ad1d_0 conda-forge nbclient 0.10.0 pyhd8ed1ab_0 conda-forge nbconvert-core 7.16.4 pyhd8ed1ab_1 conda-forge nbformat 5.10.4 pyhd8ed1ab_0 conda-forge ncurses 6.5 h5846eda_0 conda-forge nest-asyncio 1.6.0 pyhd8ed1ab_0 conda-forge netcdf-fortran 4.6.1 nompi_h3a6982b_104 conda-forge networkx 3.3 pyhd8ed1ab_1 conda-forge notebook 7.2.1 pyhd8ed1ab_0 conda-forge notebook-shim 0.2.4 pyhd8ed1ab_0 conda-forge numexpr 2.10.0 py312h1171441_0 conda-forge numpy 1.26.4 py312he3a82b2_0 conda-forge ocl_icd_wrapper_apple 1.0.0 hbcb3906_0 conda-forge openff-amber-ff-ports 0.0.4 pyhca7485f_0 conda-forge openff-forcefields 2024.07.0 pyhff2d567_0 conda-forge openff-interchange 0.3.28 pyhd8ed1ab_0 conda-forge openff-interchange-base 0.3.28 pyhd8ed1ab_0 conda-forge openff-models 0.1.2 pyhca7485f_0 conda-forge openff-toolkit 0.16.2 pyhd8ed1ab_0 conda-forge openff-toolkit-base 0.16.2 pyhd8ed1ab_0 conda-forge openff-units 0.2.2 pyhca7485f_0 conda-forge openff-utilities 0.1.12 pyhd8ed1ab_0 conda-forge openjpeg 2.5.2 h7310d3a_0 conda-forge openmm 8.1.2 py312hacce00b_2_khronos conda-forge openssl 3.3.1 h87427d6_2 conda-forge overrides 7.7.0 pyhd8ed1ab_0 conda-forge packaging 24.1 pyhd8ed1ab_0 conda-forge packmol-memgen 2024.2.9 pypi_0 pypi pandas 2.2.2 py312h1171441_1 conda-forge pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge panedr 0.8.0 pyhd8ed1ab_0 conda-forge parmed 4.2.2 py312h444b7ae_1 conda-forge parso 0.8.4 pyhd8ed1ab_0 conda-forge pcre2 10.44 h7634a1b_0 conda-forge pdb4amber 22.0 pypi_0 pypi perl 5.32.1 7_h10d778d_perl5 conda-forge pexpect 4.9.0 pyhd8ed1ab_0 conda-forge pickleshare 0.7.5 py_1003 conda-forge pillow 10.4.0 py312hbd70edc_0 conda-forge pint 0.23 pyhd8ed1ab_1 conda-forge pip 24.0 pyhd8ed1ab_0 conda-forge pixman 0.43.4 h73e2aa4_0 conda-forge pkgutil-resolve-name 1.3.10 pyhd8ed1ab_1 conda-forge platformdirs 4.2.2 pyhd8ed1ab_0 conda-forge prometheus_client 0.20.0 pyhd8ed1ab_0 conda-forge prompt-toolkit 3.0.47 pyha770c72_0 conda-forge psutil 6.0.0 py312hbd25219_0 conda-forge pthread-stubs 0.4 hc929b4f_1001 conda-forge ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge pure_eval 0.2.3 pyhd8ed1ab_0 conda-forge py-cpuinfo 9.0.0 pyhd8ed1ab_0 conda-forge pycairo 1.26.1 py312h4a9e434_0 conda-forge pycparser 2.22 pyhd8ed1ab_0 conda-forge pydantic 2.8.2 pyhd8ed1ab_0 conda-forge pydantic-core 2.20.1 py312ha47ea1c_0 conda-forge pyedr 0.8.0 pyhd8ed1ab_0 conda-forge pygments 2.18.0 pyhd8ed1ab_0 conda-forge pymsmt 22.0 pypi_0 pypi pyobjc-core 10.3.1 py312he77c50b_0 conda-forge pyobjc-framework-cocoa 10.3.1 py312he77c50b_0 conda-forge pyparsing 3.1.2 pyhd8ed1ab_0 conda-forge pysocks 1.7.1 pyha2e5f31_6 conda-forge pytables 3.9.2 py312hd51072b_3 conda-forge python 3.12.4 h37a9e06_0_cpython conda-forge python-constraint 1.4.0 py_0 conda-forge python-dateutil 2.9.0 pyhd8ed1ab_0 conda-forge python-fastjsonschema 2.20.0 pyhd8ed1ab_0 conda-forge python-json-logger 2.0.7 pyhd8ed1ab_0 conda-forge python-tzdata 2024.1 pyhd8ed1ab_0 conda-forge python_abi 3.12 4_cp312 conda-forge pytraj 2.0.6 pypi_0 pypi pytz 2024.1 pyhd8ed1ab_0 conda-forge pyyaml 6.0.1 py312h104f124_1 conda-forge pyzmq 26.0.3 py312ha04878a_0 conda-forge qhull 2020.2 h3c5361c_5 conda-forge rdkit 2024.03.5 py312hcfd6466_1 conda-forge readline 8.2 h9e318b2_1 conda-forge referencing 0.35.1 pyhd8ed1ab_0 conda-forge reportlab 4.2.2 py312hbd25219_0 conda-forge requests 2.32.3 pyhd8ed1ab_0 conda-forge rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge rlpycairo 0.2.0 pyhd8ed1ab_0 conda-forge rpds-py 0.19.1 py312ha47ea1c_0 conda-forge sander 22.0 pypi_0 pypi scipy 1.14.0 py312hb9702fa_1 conda-forge send2trash 1.8.3 pyh31c8845_0 conda-forge setuptools 71.0.4 pyhd8ed1ab_0 conda-forge six 1.16.0 pyh6c4a22f_0 conda-forge smirnoff99frosst 1.1.0 pyh44b312d_0 conda-forge snappy 1.2.1 he1e6707_0 conda-forge sniffio 1.3.1 pyhd8ed1ab_0 conda-forge soupsieve 2.5 pyhd8ed1ab_1 conda-forge sqlalchemy 2.0.31 py312hbd25219_0 conda-forge stack_data 0.6.2 pyhd8ed1ab_0 conda-forge terminado 0.18.1 pyh31c8845_0 conda-forge tinycss2 1.3.0 pyhd8ed1ab_0 conda-forge tk 8.6.13 h1abcd95_1 conda-forge tomli 2.0.1 pyhd8ed1ab_0 conda-forge tornado 6.4.1 py312hbd25219_0 conda-forge tqdm 4.66.4 pyhd8ed1ab_0 conda-forge traitlets 5.14.3 pyhd8ed1ab_0 conda-forge types-python-dateutil 2.9.0.20240316 pyhd8ed1ab_0 conda-forge typing-extensions 4.12.2 hd8ed1ab_0 conda-forge typing_extensions 4.12.2 pyha770c72_0 conda-forge typing_utils 0.1.0 pyhd8ed1ab_0 conda-forge tzdata 2024a h0c530f3_0 conda-forge uri-template 1.3.0 pyhd8ed1ab_0 conda-forge urllib3 2.2.2 pyhd8ed1ab_0 conda-forge wcwidth 0.2.13 pyhd8ed1ab_0 conda-forge webcolors 24.6.0 pyhd8ed1ab_0 conda-forge webencodings 0.5.1 pyhd8ed1ab_2 conda-forge websocket-client 1.8.0 pyhd8ed1ab_0 conda-forge wheel 0.43.0 pyhd8ed1ab_1 conda-forge widgetsnbextension 4.0.11 pyhd8ed1ab_0 conda-forge xmltodict 0.13.0 pyhd8ed1ab_0 conda-forge xorg-kbproto 1.0.7 h35c211d_1002 conda-forge xorg-libice 1.1.1 h0dc2134_0 conda-forge xorg-libsm 1.2.4 h0dc2134_0 conda-forge xorg-libx11 1.8.9 h7022169_1 conda-forge xorg-libxau 1.0.11 h0dc2134_0 conda-forge xorg-libxdmcp 1.1.3 h35c211d_0 conda-forge xorg-libxext 1.3.4 hb7f2c08_2 conda-forge xorg-libxt 1.3.0 h0dc2134_1 conda-forge xorg-xextproto 7.3.0 hb7f2c08_1003 conda-forge xorg-xproto 7.0.31 h35c211d_1007 conda-forge xz 5.2.6 h775f41a_0 conda-forge yaml 0.2.5 h0d85af4_2 conda-forge zeromq 4.3.5 hde137ed_4 conda-forge zipp 3.19.2 pyhd8ed1ab_0 conda-forge zlib 1.3.1 h87427d6_1 conda-forge zlib-ng 2.2.1 hf036a51_0 conda-forge zstd 1.5.6 h915ae27_0 conda-forge ```

CC @mikemhenry

j-wags commented 4 months ago

Thanks for the detailed writeup. I'm unable to reproduce on an ARM mac, but I'm charging my old intel mac to try it there.

j-wags commented 4 months ago

Some of our CI should be testing on intel macs, and I'm not seeing any issues there, though

j-wags commented 4 months ago

Unable to reproduce with intel mac on OSX 13.2.1, updating to 14 and will report back.

slochower commented 4 months ago

Thanks! And on my end, this is reproducible (not related to this specific molecule/solvent box). Hit the bug trying to use OpenFE stuff (on real ligands) with @mikemhenry and we initially thought it might be related to RDKit, but it does not seem to be. I'm happy to do additional debugging if you need.

j-wags commented 4 months ago

Darn, my intel macbook isn't compatible with OSX 14. If you're up to iterate a bit, could you let me know if this reproduces the issue?

from openff.toolkit import Molecule
mol = Molecule.from_smiles('[H][O][C]([H])([H])[C]([H])([H])[C]([H])([H])[C]([H])([H])[H]')
mol.assign_partial_charges("am1bcc")
j-wags commented 4 months ago

And if that DOES reproduce the issue, could you run

mol.generate_conformers()
mol.to_file('temp.sdf', file_format='sdf')

and in the terminal

antechamber -i molecule.sdf -fi sdf -o charged.mol2 -fo mol2 -pf yes -dr n -c bcc  -nc 0.0

and let me know what happens?

slochower commented 4 months ago

The small snippet does not reproduce the error.

slochower commented 4 months ago

Oh wait!

I ran it once and it completed without error.

I ran it a second time and it did reproduce the error. Fun.

~/tmp is šŸ“¦ v0.1.0 via šŸ v3.12.4 via šŸ…’ openff-clean took 10s
āÆ python tmp5.py
(openff-clean)
~/tmp is šŸ“¦ v0.1.0 via šŸ v3.12.4 via šŸ…’ openff-clean took 27s
āÆ python tmp5.py
/Users/slochowe/miniforge3/envs/openff-clean/bin/wrapped_progs/antechamber: Fatal Error!
Cannot properly run "/Users/slochowe/miniforge3/envs/openff-clean/bin/sqm -O -i sqm.in -o sqm.out".
Traceback (most recent call last):
  File "/Users/slochowe/tmp/tmp5.py", line 3, in <module>
    mol.assign_partial_charges("am1bcc")
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/toolkit/topology/molecule.py", line 2677, in assign_partial_charges
    toolkit_registry.call(
  File "/Users/slochowe/miniforge3/envs/openff-clean/lib/python3.12/site-packages/openff/toolkit/utils/toolkit_registry.py", line 280, in call
    raise ValueError(msg)
ValueError: No registered toolkits can provide the capability "assign_partial_charges" for args "()" and kwargs "{'molecule': Molecule with name '' and SMILES '[H][O][C]([H])([H])[C]([H])([H])[C]([H])([H])[C]([H])([H])[H]', 'partial_charge_method': 'am1bcc', 'use_conformers': None, 'strict_n_conformers': False, 'normalize_partial_charges': True, '_cls': <class 'openff.toolkit.topology.molecule.Molecule'>}"
Available toolkits are: [ToolkitWrapper around The RDKit version 2024.03.5, ToolkitWrapper around AmberTools version 23.6, ToolkitWrapper around Built-in Toolkit version None]
 ToolkitWrapper around The RDKit version 2024.03.5 <class 'openff.toolkit.utils.exceptions.ChargeMethodUnavailableError'> : partial_charge_method 'am1bcc' is not available from RDKitToolkitWrapper. Available charge methods are {'mmff94': {}, 'gasteiger': {}}
 ToolkitWrapper around AmberTools version 23.6 <class 'subprocess.CalledProcessError'> : Command '['antechamber', '-i', 'molecule.sdf', '-fi', 'sdf', '-o', 'charged.mol2', '-fo', 'mol2', '-pf', 'yes', '-dr', 'n', '-c', 'bcc', '-nc', '0.0']' returned non-zero exit status 1.
 ToolkitWrapper around Built-in Toolkit version None <class 'openff.toolkit.utils.exceptions.ChargeMethodUnavailableError'> : Partial charge method "am1bcc"" is not supported by the Built-in toolkit. Available charge methods are {'zeros': {'rec_confs': 0, 'min_confs': 0, 'max_confs': 0}, 'formal_charge': {'rec_confs': 0, 'min_confs': 0, 'max_confs': 0}}
mikemhenry commented 4 months ago

:melting_face:

mikemhenry commented 4 months ago

@slochower can you try this? for i in (seq 10); python tmp5.py; end and lets see how often this happens... (assuming you are using fish shell)

slochower commented 4 months ago

Looks like 5/10. Perfect.

I made a slight modification for i in (seq 10); python tmp5.py && echo "Pass"; end and counted "Pass" five times.

Here's another version:

ā†Ŗ for i in (seq 10); python tmp5.py &> /dev/null && echo "Pass $i"; end
Pass 5
Pass 7
Pass 8
slochower commented 4 months ago

Okay, so it's Ambertools that is leading to the mess.

ā†Ŗ for i in (seq 10); antechamber -i temp.sdf -fi sdf -o charged.mol2 -fo mol2 -pf yes -dr n -c bcc -nc 0.0 &> /dev/null && echo "Pass $i"; end
Pass 2
Pass 4
Pass 5
Pass 8
Pass 10

WHen it fails, it's linked to sqm.

And this is what happens when sqm fails.

āÆ cat sqm.in
Run semi-empirical minimization
 &qmmm
    qm_theory='AM1', grms_tol=0.0005,
 scfconv=1.d-10, ndiis_attempts=700,   qmcharge=0,
 /
āÆ cat sqm.out
            --------------------------------------------------------
                             AMBER SQM VERSION 19

                                     By
              Ross C. Walker, Michael F. Crowley, Scott Brozell,
                         Tim Giese, Andreas W. Goetz,
                        Tai-Sung Lee and David A. Case

            --------------------------------------------------------

 QM ATOM VALIDATION: nquant has a value of        0
 SANDER BOMB in subroutine validate_qm_atoms
 nquant illegal
 Need 0 < nquant <= natom
slochower commented 4 months ago

The input file should have the coordinates in it after the / but in cases where it fails, it just ends like above, without coordinates. A correct file would be something like this:

Run semi-empirical minimization
 &qmmm
    qm_theory='AM1', grms_tol=0.0005,
 scfconv=1.d-10, ndiis_attempts=700,   qmcharge=0,
 /
   1    H1        2.5450        1.2970        0.8130
   8    O1        2.5880        0.3750        0.4790
   6    C1        1.3640        0.0320       -0.1430
   1    H2        1.6070       -0.8440       -0.7780
   1    H3        1.0220        0.8280       -0.8300
   6    C2        0.4040       -0.2880        0.9570
   1    H4        0.8200       -1.1770        1.4820
   1    H5        0.3520        0.5510        1.6630
   6    C3       -0.9630       -0.6780        0.4760
   1    H6       -1.6150       -0.8110        1.3650
   1    H7       -1.0030       -1.6010       -0.0910
   6    C4       -1.6300        0.4120       -0.3350
   1    H8       -0.9920        0.7070       -1.1940
   1    H9       -1.9350        1.2690        0.3110
   1   H10       -2.5640       -0.0710       -0.7400
mikemhenry commented 4 months ago

Can you try installing ambertools 22? Hopefully it doesn't cause too much package churn, on my system it looks like this:

   - ambertools=22

  Package              Version  Build                    Channel           Size
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€
  Install:
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€

  + boost-cpp           1.78.0  h2c5509c_4               conda-forge     Cached
  + cython              3.0.10  py310hc6cd4ac_0          conda-forge     Cached
  + packmol            20.15.0  hc8b2c43_0               conda-forge      130kB
  + boost               1.78.0  py310hcb52e73_5          conda-forge     Cached

  Remove:
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€

  - libboost            1.84.0  hba137d9_3               conda-forge     Cached
  - libboost-python     1.84.0  py310he6ccd79_3          conda-forge     Cached

  Downgrade:
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€

  - arpack               3.9.1  nompi_h77f6705_101       conda-forge     Cached
  + arpack               3.7.0  hdefa2d7_2               conda-forge     Cached
  - ambertools            23.6  nompi_py310hcbc9ba0_103  conda-forge     Cached
  + ambertools            22.5  py310hd182041_0          conda-forge     Cached
  - rdkit            2024.03.3  py310h6f17f40_0          conda-forge     Cached
  + rdkit            2023.03.3  py310h399bcf7_0          conda-forge     Cached

which for our testing purposes isn't too bad, another option would be to keep ambertools 23, but just install an older build, like before mpi support was added for example.

slochower commented 4 months ago

Oof. Couldn't install with the existing 3.12 environment. Stepped back to 3.11, also dependency conflicts. Stepped back to 3.10, also dependency conflicts...

warning  libmamba Added empty dependency for problem type SOLVER_RULE_UPDATE
Could not solve for environment specs
The following packages are incompatible
ā”œā”€ ambertools 22**  is installable with the potential options
ā”‚  ā”œā”€ ambertools 22.0 would require
ā”‚  ā”‚  ā””ā”€ boost-cpp >=1.74.0,<1.74.1.0a0  with the potential options
ā”‚  ā”‚     ā”œā”€ boost-cpp 1.74.0 would require
ā”‚  ā”‚     ā”‚  ā””ā”€ icu >=68.1,<69.0a0 , which can be installed;
ā”‚  ā”‚     ā”œā”€ boost-cpp [1.74.0|1.78.0] would require
ā”‚  ā”‚     ā”‚  ā””ā”€ icu >=70.1,<71.0a0 , which can be installed;
ā”‚  ā”‚     ā”œā”€ boost-cpp 1.74.0 would require
ā”‚  ā”‚     ā”‚  ā””ā”€ icu >=69.1,<70.0a0 , which can be installed;
ā”‚  ā”‚     ā””ā”€ boost-cpp 1.74.0 would require
ā”‚  ā”‚        ā””ā”€ icu >=67.1,<68.0a0 , which can be installed;
ā”‚  ā”œā”€ ambertools 22.0 would require
ā”‚  ā”‚  ā””ā”€ python >=3.7,<3.8.0a0 , which can be installed;
ā”‚  ā”œā”€ ambertools [22.0|22.1|...|22.5] would require
ā”‚  ā”‚  ā””ā”€ python >=3.8,<3.9.0a0 , which can be installed;
ā”‚  ā”œā”€ ambertools [22.0|22.1|...|22.5] would require
ā”‚  ā”‚  ā””ā”€ python >=3.9,<3.10.0a0 , which can be installed;
ā”‚  ā””ā”€ ambertools [22.0|22.1|...|22.5] would require
ā”‚     ā””ā”€ boost-cpp >=1.78.0,<1.78.1.0a0  with the potential options
ā”‚        ā”œā”€ boost-cpp [1.74.0|1.78.0], which can be installed (as previously explained);
ā”‚        ā”œā”€ boost-cpp 1.78.0 would require
ā”‚        ā”‚  ā”œā”€ icu >=73.2,<74.0a0 , which conflicts with any installable versions previously reported;
ā”‚        ā”‚  ā””ā”€ libboost <0 , which can be installed;
ā”‚        ā””ā”€ boost-cpp 1.78.0 would require
ā”‚           ā””ā”€ icu >=72.1,<73.0a0 , which can be installed;
ā”œā”€ libboost is installable with the potential options
ā”‚  ā”œā”€ libboost [1.84.0|1.85.0] would require
ā”‚  ā”‚  ā””ā”€ icu >=75.1,<76.0a0 , which conflicts with any installable versions previously reported;
ā”‚  ā”œā”€ libboost 1.84.0 would require
ā”‚  ā”‚  ā”œā”€ boost-cpp 1.84.0* , which conflicts with any installable versions previously reported;
ā”‚  ā”‚  ā””ā”€ icu >=73.2,<74.0a0 , which conflicts with any installable versions previously reported;
ā”‚  ā”œā”€ libboost 1.82.0 would require
ā”‚  ā”‚  ā””ā”€ icu >=72.1,<73.0a0 , which can be installed;
ā”‚  ā”œā”€ libboost 1.82.0 would require
ā”‚  ā”‚  ā””ā”€ boost-cpp 1.82.0* , which conflicts with any installable versions previously reported;
ā”‚  ā”œā”€ libboost 1.83.0 would require
ā”‚  ā”‚  ā””ā”€ boost-cpp 1.83.0* , which conflicts with any installable versions previously reported;
ā”‚  ā”œā”€ libboost 1.85.0 would require
ā”‚  ā”‚  ā””ā”€ boost-cpp 1.85.0* , which conflicts with any installable versions previously reported;
ā”‚  ā”œā”€ libboost [1.65.1|1.67.0|1.71.0|1.73.0] would require
ā”‚  ā”‚  ā””ā”€ icu >=58.2,<59.0a0 , which can be installed;
ā”‚  ā””ā”€ libboost 1.82.0 conflicts with any installable versions previously reported;
ā””ā”€ librdkit is not installable because it requires
   ā””ā”€ libboost >=1.84.0,<1.85.0a0 , which cannot be installed (as previously explained).
mikemhenry commented 4 months ago

sigh, how about ambertools=23.3

slochower commented 4 months ago

Sadly not. Looks like libboost is the culprit, at least when trying in the original environment.

ā†Ŗ mamba install ambertools=23.3                                  (openff-clean)

Looking for: ['ambertools=23.3']

conda-forge/osx-64                                          Using cache
conda-forge/noarch                                          Using cache
pkgs/main/noarch                                              No change
pkgs/r/osx-64                                                 No change
pkgs/r/noarch                                                 No change
pkgs/main/osx-64                                              No change

Pinned packages:
  - python 3.12.*

warning  libmamba Added empty dependency for problem type SOLVER_RULE_UPDATE
Could not solve for environment specs
The following packages are incompatible
ā”œā”€ ambertools 23.3**  is installable with the potential options
ā”‚  ā”œā”€ ambertools 23.3 would require
ā”‚  ā”‚  ā””ā”€ libboost >=1.82.0,<1.83.0a0  with the potential options
ā”‚  ā”‚     ā”œā”€ libboost 1.82.0 would require
ā”‚  ā”‚     ā”‚  ā””ā”€ icu >=72.1,<73.0a0 , which can be installed;
ā”‚  ā”‚     ā”œā”€ libboost 1.82.0 would require
ā”‚  ā”‚     ā”‚  ā””ā”€ icu >=73.2,<74.0a0 , which can be installed;
ā”‚  ā”‚     ā””ā”€ libboost 1.82.0 would require
ā”‚  ā”‚        ā””ā”€ icu >=73.1,<74.0a0 , which can be installed;
ā”‚  ā”œā”€ ambertools 23.3 would require
ā”‚  ā”‚  ā””ā”€ python >=3.10,<3.11.0a0 , which can be installed;
ā”‚  ā”œā”€ ambertools 23.3 would require
ā”‚  ā”‚  ā””ā”€ python >=3.11,<3.12.0a0 , which can be installed;
ā”‚  ā”œā”€ ambertools 23.3 would require
ā”‚  ā”‚  ā””ā”€ python >=3.8,<3.9.0a0 , which can be installed;
ā”‚  ā””ā”€ ambertools 23.3 would require
ā”‚     ā””ā”€ python >=3.9,<3.10.0a0 , which can be installed;
ā””ā”€ librdkit is not installable because it requires
   ā””ā”€ libboost >=1.84.0,<1.85.0a0  but there are no viable options
      ā”œā”€ libboost 1.84.0 would require
      ā”‚  ā””ā”€ icu >=75.1,<76.0a0 , which conflicts with any installable versions previously reported;
      ā””ā”€ libboost 1.84.0 conflicts with any installable versions previously reported.
mikemhenry commented 4 months ago

Is that making a fresh env? Using some hacks (I am on linux) it looks like it should solve on osx-arm64 CONDA_SUBDIR="osx-arm64" micromamba create -n foooooobar --dry-run -c conda-forge ambertools=23.3 "openff-toolkit=0.16.*" BUT I know sometimes when you have an env, the solver can get stuck trying to figure things out but a fresh one can help it out.

slochower commented 4 months ago

Good point. Although 23.3 is still flaky. I can step back to 22 in a new environment.

ā†Ŗ for i in (seq 10); antechamber -i temp.sdf -fi sdf -o charged.mol2 -fo mol2 -pf yes -dr n -c bcc -nc 0.0 &> /dev/null && echo "Pass $i"; end

Pass 1
Pass 3
Pass 4
Pass 5
Pass 6
Pass 7

Here's ambertools=22 ...

ā†Ŗ for i in (seq 10); antechamber -i temp.sdf -fi sdf -o charged.mol2 -fo mol2 -pf yes -dr n -c bcc -nc 0.0 &> /dev/null && echo "Pass $i"; end

Pass 2
Pass 3
Pass 4
Pass 5
Pass 7
Pass 8

šŸ˜°

mikemhenry commented 4 months ago

okay one more idea, antechamber -i molecule.sdf -fi sdf -o charged.mol2 -fo mol2 -pf yes -dr n -c bcc -nc 0.0 -ek

see if adding the -ek arg helps at all

slochower commented 4 months ago

I think that needs something after it?

mikemhenry commented 4 months ago

You are correct! -ek pseudo_diag=0 We can use -ek to pass in arguments to sqm, I've seen some weird things where diagonalization options/methods causes sqm to not be deterministic -- this is a bit of a rabbit hole since even if we figure out some collection of arguments that makes sqm work consistently, it is unclear if we can get those options upstreamed into the toolkit.

Another option to pass in is diag_routine=3, so try -ek "pseudo_diag=0, diag_routine=3" and see if that gets us 10 passes.

slochower commented 4 months ago
ā†Ŗ antechamber -i temp.sdf -fi sdf -o charged.mol2 -fo mol2 -pf yes -dr n -c bcc -nc 0.0 -ek pseudo_diag=0

Welcome to antechamber 22.0: molecular input file processor.

Info: The atom type is set to gaff; the options available to the -at flag are
      gaff, gaff2, amber, bcc, and sybyl.

Info: Total number of electrons: 0; net charge: 0

Running: /Users/slochowe/miniforge3/envs/foo2/bin/sqm -O -i sqm.in -o sqm.out
/Users/slochowe/miniforge3/envs/foo2/bin/wrapped_progs/antechamber: Fatal Error!
Cannot properly run "/Users/slochowe/miniforge3/envs/foo2/bin/sqm -O -i sqm.in -o sqm.out".

I don't think this is a problem inside sqm but rather -- the input file is not being written correctly:

ā†Ŗ bat sqm.in                                                             (foo2)
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€
       ā”‚ File: sqm.in
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¼ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€
   1   ā”‚ Run semi-empirical minimization
   2   ā”‚  &qmmm
   3   ā”‚   pseudo_diag=0  qmcharge=0,
   4   ā”‚  /
   5   ā”‚
ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”“ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€
mattwthompson commented 1 month ago

IIUC, the toolkit doesn't actually write that file, so something before that step is failing?

I can't reproduce this behavior this morning using cuda_None_nompi_py312hc98840c_105