diff --git a/.claude/skills/generate-scripts/references/results_metadata.md b/.claude/skills/generate-scripts/references/results_metadata.md index 97a71c14b2..2a35a095ee 100644 --- a/.claude/skills/generate-scripts/references/results_metadata.md +++ b/.claude/skills/generate-scripts/references/results_metadata.md @@ -39,4 +39,3 @@ If the minimum objective value is exactly 0.0, check whether those rows have `sim_ended == True`. Unevaluated rows often have fields initialized to zero. This is common for the last few rows when the simulation budget is exhausted — they were allocated by the generator but never evaluated. - diff --git a/.github/workflows/extra.yml b/.github/workflows/extra.yml index 4022c3bef3..f3f6fd2239 100644 --- a/.github/workflows/extra.yml +++ b/.github/workflows/extra.yml @@ -22,10 +22,6 @@ jobs: python-version: "py312e" mpi-version: mpich comms-type: l - - os: ubuntu-latest - python-version: "py312e" - mpi-version: mpich - comms-type: t - os: ubuntu-latest mpi-version: openmpi python-version: "py312e" diff --git a/.readthedocs.yml b/.readthedocs.yml index d7c674392b..e6e5750a73 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -23,7 +23,8 @@ build: - asdf plugin add pixi - asdf install pixi latest - asdf global pixi latest - - pixi run -e docs build-docs + - pixi run -e docs sphinx-build -b html docs docs/_build/html -W --keep-going + - pixi run -e docs sphinx-build -b linkcheck docs docs/_build/linkcheck - mkdir -p $READTHEDOCS_OUTPUT/html/ - cp -r docs/_build/html/** $READTHEDOCS_OUTPUT/html/ - pixi run -e docs build-pdf diff --git a/README.rst b/README.rst index c593aec87a..06b593981b 100644 --- a/README.rst +++ b/README.rst @@ -144,7 +144,6 @@ Resources - Ask questions or report issues on GitHub_. - Email ``libEnsemble@lists.mcs.anl.gov`` to request `libEnsemble Slack page`_. -- Join the `libEnsemble mailing list`_ for updates about new releases. **Further Information:** @@ -197,7 +196,6 @@ Resources .. _docs: https://libensemble.readthedocs.io/en/main/advanced_installation.html .. _gest-api: https://gest-api.readthedocs.io/en/latest/ .. _GitHub: https://github.com/Libensemble/libensemble -.. _libEnsemble mailing list: https://lists.mcs.anl.gov/mailman/listinfo/libensemble .. _libEnsemble Slack page: https://libensemble.slack.com .. _MPICH: http://www.mpich.org/ .. _mpmath: http://mpmath.org/ diff --git a/SUPPORT.rst b/SUPPORT.rst index bf6f68d9cb..7b082b7b4b 100644 --- a/SUPPORT.rst +++ b/SUPPORT.rst @@ -5,10 +5,6 @@ Open issues on Github at: * https://github.com/Libensemble/libensemble/issues -Join the libEnsemble mailing list at: - -* https://lists.mcs.anl.gov/mailman/listinfo/libensemble - or email questions to: * libensemble@lists.mcs.anl.gov diff --git a/docs/FAQ.rst b/docs/FAQ.rst index 931a2eda1d..0987e66f62 100644 --- a/docs/FAQ.rst +++ b/docs/FAQ.rst @@ -145,8 +145,6 @@ HPC Errors and Questions is to either switch fabric or turn off matching probes. See the answer to "Why does libEnsemble hang on certain systems when running with MPI?" - For more information see https://bitbucket.org/mpi4py/mpi4py/issues/102/unpicklingerror-on-commrecv-after-iprobe. - .. dropdown:: **srun: Job \*\*\*\*\*\* step creation temporarily disabled, retrying (Requested nodes are busy)** Note that this message has been observed on Perlmutter when none of the problems @@ -161,7 +159,7 @@ HPC Errors and Questions See question **can't open hfi unit: -1 (err=23)** for more info. - All the memory is assigned to the first job-step (srun application), due to a default - exclusive mode scheduling policy. This has been observed on `Perlmutter`_ and `SDF`_. + exclusive mode scheduling policy. This has been observed on `Perlmutter`_. In some cases using these environment variables will stop the issue:: @@ -302,6 +300,5 @@ macOS and Windows Errors .. _option to srun: https://docs.nersc.gov/systems/perlmutter/running-jobs/#single-gpu-tasks-in-parallel .. _Perlmutter: https://docs.nersc.gov/systems/perlmutter/architecture/ .. _Python multiprocessing docs: https://docs.python.org/3/library/multiprocessing.html -.. _SDF: https://sdf.slac.stanford.edu/public/doc/#/?id=what-is-the-sdf .. _Support: https://libensemble.readthedocs.io/en/main/introduction.html#resources .. _xQuartz: https://www.xquartz.org/ diff --git a/docs/advanced_installation/advanced_installation.rst b/docs/advanced_installation/advanced_installation.rst index 0ac8018ffb..540fbec60b 100644 --- a/docs/advanced_installation/advanced_installation.rst +++ b/docs/advanced_installation/advanced_installation.rst @@ -1,7 +1,7 @@ Advanced Installation ===================== -`pip `__ || `uv `__ || `pixi `__ || `conda `__ || `Spack `__ +:doc:`pip ` || :doc:`uv ` || :doc:`pixi ` || :doc:`conda ` || :doc:`Spack ` libEnsemble can be installed from ``pip``, ``uv``, ``pixi``, ``Conda``, or ``Spack``. diff --git a/docs/advanced_installation/advanced_installation_conda.rst b/docs/advanced_installation/advanced_installation_conda.rst index c34ce25b1a..b67db2bd55 100644 --- a/docs/advanced_installation/advanced_installation_conda.rst +++ b/docs/advanced_installation/advanced_installation_conda.rst @@ -1,7 +1,7 @@ conda ===== -`Advanced Installation `__ \|\| `pip `__ \|\| `uv `__ \|\| `pixi `__ \|\| **conda** \|\| `Spack `__ +:doc:`Advanced Installation ` || :doc:`pip ` || :doc:`uv ` || :doc:`pixi ` || **conda** || :doc:`Spack ` Install libEnsemble with Conda_ from the conda-forge channel:: diff --git a/docs/advanced_installation/advanced_installation_pip.rst b/docs/advanced_installation/advanced_installation_pip.rst index 9416765b1c..e80ac0b315 100644 --- a/docs/advanced_installation/advanced_installation_pip.rst +++ b/docs/advanced_installation/advanced_installation_pip.rst @@ -1,7 +1,7 @@ pip === -`Advanced Installation `__ \|\| **pip** \|\| `uv `__ \|\| `pixi `__ \|\| `conda `__ \|\| `Spack `__ +:doc:`Advanced Installation ` || **pip** || :doc:`uv ` || :doc:`pixi ` || :doc:`conda ` || :doc:`Spack ` To install the latest PyPI_ release:: diff --git a/docs/advanced_installation/advanced_installation_pixi.rst b/docs/advanced_installation/advanced_installation_pixi.rst index 8227fcbd87..b0ef65467a 100644 --- a/docs/advanced_installation/advanced_installation_pixi.rst +++ b/docs/advanced_installation/advanced_installation_pixi.rst @@ -1,7 +1,7 @@ pixi ==== -`Advanced Installation `__ \|\| `pip `__ \|\| `uv `__ \|\| **pixi** \|\| `conda `__ \|\| `Spack `__ +:doc:`Advanced Installation ` || :doc:`pip ` || :doc:`uv ` || **pixi** || :doc:`conda ` || :doc:`Spack ` Add to your pixi_ environment:: diff --git a/docs/advanced_installation/advanced_installation_spack.rst b/docs/advanced_installation/advanced_installation_spack.rst index 3fe412377a..c2abd410fb 100644 --- a/docs/advanced_installation/advanced_installation_spack.rst +++ b/docs/advanced_installation/advanced_installation_spack.rst @@ -1,7 +1,7 @@ Spack ===== -`Advanced Installation `__ \|\| `pip `__ \|\| `uv `__ \|\| `pixi `__ \|\| `conda `__ \|\| **Spack** +:doc:`Advanced Installation ` || :doc:`pip ` || :doc:`uv ` || :doc:`pixi ` || :doc:`conda ` || **Spack** Install libEnsemble using the Spack_ distribution:: diff --git a/docs/advanced_installation/advanced_installation_uv.rst b/docs/advanced_installation/advanced_installation_uv.rst index b10b64bfa5..e47dcaa92a 100644 --- a/docs/advanced_installation/advanced_installation_uv.rst +++ b/docs/advanced_installation/advanced_installation_uv.rst @@ -1,7 +1,7 @@ uv == -`Advanced Installation `__ \|\| `pip `__ \|\| **uv** \|\| `pixi `__ \|\| `conda `__ \|\| `Spack `__ +:doc:`Advanced Installation ` || :doc:`pip ` || **uv** || :doc:`pixi ` || :doc:`conda ` || :doc:`Spack ` To install the latest PyPI_ release via uv_:: diff --git a/docs/conf.py b/docs/conf.py index 2d227780e1..062eddf988 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -118,6 +118,16 @@ class AxParameterWarning(Warning): # Ensure it's a real warning subclass "community": ("https://libensemble.readthedocs.io/projects/libe-community-examples/en/latest/", None) } +# These hosts reject automated requests from Sphinx linkcheck with HTTP 403. +linkcheck_ignore = [ + r"https://(docs|www)\.(alcf|lcrc)\.anl\.gov/.*", + r"https://www\.mcs\.anl\.gov/.*", + r"https://link\.aps\.org/.*", + r"https://libensemble\.slack\.com(?:/.*)?$", + r"https://software\.intel\.com/.*", + r"https://stackoverflow\.com/.*", +] + autodoc_pydantic_model_show_json = False extlinks = { diff --git a/docs/data_structures/libE_specs/libE_specs.rst b/docs/data_structures/libE_specs/libE_specs.rst index a219109851..45a6e0f117 100644 --- a/docs/data_structures/libE_specs/libE_specs.rst +++ b/docs/data_structures/libE_specs/libE_specs.rst @@ -1,6 +1,6 @@ .. _datastruct-libe-specs: -**Introduction** \|\| `General `__ \|\| `Directories `__ \|\| `Profiling `__ \|\| `TCP `__ \|\| `History `__ \|\| `Resources `__ +**Introduction** || :doc:`General ` || :doc:`Directories ` || :doc:`Profiling ` || :doc:`History ` || :doc:`Resources ` LibE Specs ========== @@ -19,7 +19,6 @@ libEnsemble is primarily customized by setting options within a ``LibeSpecs`` in libE_specs_general libE_specs_directories libE_specs_profiling - libE_specs_tcp libE_specs_history libE_specs_resources diff --git a/docs/data_structures/libE_specs/libE_specs_directories.rst b/docs/data_structures/libE_specs/libE_specs_directories.rst index 76c848da05..4c8ae8661b 100644 --- a/docs/data_structures/libE_specs/libE_specs_directories.rst +++ b/docs/data_structures/libE_specs/libE_specs_directories.rst @@ -1,7 +1,7 @@ Directories =========== -`Introduction `__ \|\| `General `__ \|\| **Directories** \|\| `Profiling `__ \|\| `TCP `__ \|\| `History `__ \|\| `Resources `__ +:doc:`Introduction ` || :doc:`General ` || **Directories** || :doc:`Profiling ` || :doc:`History ` || :doc:`Resources ` .. tab-set:: diff --git a/docs/data_structures/libE_specs/libE_specs_general.rst b/docs/data_structures/libE_specs/libE_specs_general.rst index f7f07f75fa..1701b41b12 100644 --- a/docs/data_structures/libE_specs/libE_specs_general.rst +++ b/docs/data_structures/libE_specs/libE_specs_general.rst @@ -1,15 +1,15 @@ General ======= -`Introduction `__ \|\| **General** \|\| `Directories `__ \|\| `Profiling `__ \|\| `TCP `__ \|\| `History `__ \|\| `Resources `__ +:doc:`Introduction ` || **General** || :doc:`Directories ` || :doc:`Profiling ` || :doc:`History ` || :doc:`Resources ` **comms** [str] = ``"mpi"``: - Manager/Worker communications mode: ``'mpi'``, ``'local'``, ``'threads'``, or ``'tcp'``. + Manager/Worker communications mode: ``'mpi'``, ``'local'``, or ``'threads'``. If ``nworkers`` is specified, then ``local`` comms will be used unless a parallel MPI environment is detected. **nworkers** [int]: - Number of worker processes in ``"local"``, ``"threads"``, or ``"tcp"``. + Number of worker processes in ``"local"`` or ``"threads"``. **gen_on_worker** [bool] = False Instructs Worker process to run generator instead of Manager. diff --git a/docs/data_structures/libE_specs/libE_specs_history.rst b/docs/data_structures/libE_specs/libE_specs_history.rst index 55e9089696..20a4ece21e 100644 --- a/docs/data_structures/libE_specs/libE_specs_history.rst +++ b/docs/data_structures/libE_specs/libE_specs_history.rst @@ -1,7 +1,7 @@ History ======= -`Introduction `__ \|\| `General `__ \|\| `Directories `__ \|\| `Profiling `__ \|\| `TCP `__ \|\| **History** \|\| `Resources `__ +:doc:`Introduction ` || :doc:`General ` || :doc:`Directories ` || :doc:`Profiling ` || **History** || :doc:`Resources ` **save_every_k_sims** [int]: Save history array to file after every k simulated points. diff --git a/docs/data_structures/libE_specs/libE_specs_profiling.rst b/docs/data_structures/libE_specs/libE_specs_profiling.rst index 6a855c8ce6..f377352005 100644 --- a/docs/data_structures/libE_specs/libE_specs_profiling.rst +++ b/docs/data_structures/libE_specs/libE_specs_profiling.rst @@ -1,7 +1,7 @@ Profiling ========= -`Introduction `__ \|\| `General `__ \|\| `Directories `__ \|\| **Profiling** \|\| `TCP `__ \|\| `History `__ \|\| `Resources `__ +:doc:`Introduction ` || :doc:`General ` || :doc:`Directories ` || **Profiling** || :doc:`History ` || :doc:`Resources ` **profile** [bool] = ``False``: Profile manager and worker logic using ``cProfile``. diff --git a/docs/data_structures/libE_specs/libE_specs_resources.rst b/docs/data_structures/libE_specs/libE_specs_resources.rst index 6b6118d663..b7016a906f 100644 --- a/docs/data_structures/libE_specs/libE_specs_resources.rst +++ b/docs/data_structures/libE_specs/libE_specs_resources.rst @@ -1,7 +1,7 @@ Resources ========= -`Introduction `__ \|\| `General `__ \|\| `Directories `__ \|\| `Profiling `__ \|\| `TCP `__ \|\| `History `__ \|\| **Resources** +:doc:`Introduction ` || :doc:`General ` || :doc:`Directories ` || :doc:`Profiling ` || :doc:`History ` || **Resources** **disable_resource_manager** [bool] = ``False``: Disable the built-in resource manager, including automatic resource detection diff --git a/docs/data_structures/libE_specs/libE_specs_tcp.rst b/docs/data_structures/libE_specs/libE_specs_tcp.rst deleted file mode 100644 index d0d2a05655..0000000000 --- a/docs/data_structures/libE_specs/libE_specs_tcp.rst +++ /dev/null @@ -1,24 +0,0 @@ -TCP -=== - -`Introduction `__ \|\| `General `__ \|\| `Directories `__ \|\| `Profiling `__ \|\| **TCP** \|\| `History `__ \|\| `Resources `__ - -**workers** [list]: - TCP Only: A list of worker hostnames. - -**ip** [str]: - TCP Only: IP address for Manager's system. - -**port** [int]: - TCP Only: Port number for Manager's system. - -**authkey** [str]: - TCP Only: Authkey for Manager's system. - -**workerID** [int]: - TCP Only: Worker ID number assigned to the new process. - -**worker_cmd** [list]: - TCP Only: Split string corresponding to worker/client Python process invocation. Contains - a local Python path, calling script, and manager/server format-fields for ``manager_ip``, - ``manager_port``, ``authkey``, and ``workerID``. ``nworkers`` is specified normally. diff --git a/docs/data_structures/platform_specs.rst b/docs/data_structures/platform_specs.rst index e6d7014300..5d3d1dfc29 100644 --- a/docs/data_structures/platform_specs.rst +++ b/docs/data_structures/platform_specs.rst @@ -102,6 +102,15 @@ E.g., in the command line or batch submission script: Known Platforms List -------------------- +.. autopydantic_model:: libensemble.resources.platforms.FluxAllocation + :model-show-validator-members: False + :model-show-validator-summary: False + :model-show-field-summary: False + :field-list-validators: False + :field-show-required: False + :field-show-default: False + :field-show-alias: False + .. dropdown:: ``Known_platforms`` :open: diff --git a/docs/examples/calling_scripts.rst b/docs/examples/calling_scripts.rst index 7a58ad05e4..cb435df62d 100644 --- a/docs/examples/calling_scripts.rst +++ b/docs/examples/calling_scripts.rst @@ -43,10 +43,10 @@ This example from the regression tests demonstrates the gest-api interface with standardized ``APOSMM`` generator class parameterized by a ``VOCS`` object, and paired with a gest-api ``simulator`` callable. -.. literalinclude:: ../../libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py +.. literalinclude:: ../../libensemble/tests/regression_tests/test_aposmm_nlopt.py :language: python - :caption: tests/regression_tests/test_asktell_aposmm_nlopt.py + :caption: tests/regression_tests/test_aposmm_nlopt.py :linenos: - :end-at: workflow.exit_criteria = ExitCriteria(sim_max=2000, wallclock_max=600) + :end-before: # Perform the run .. _regression tests: https://github.com/Libensemble/libensemble/tree/develop/libensemble/tests/regression_tests diff --git a/docs/examples/gen_funcs.rst b/docs/examples/gen_funcs.rst index 6347d8bce6..04df058756 100644 --- a/docs/examples/gen_funcs.rst +++ b/docs/examples/gen_funcs.rst @@ -41,7 +41,6 @@ Optimization aposmm uniform_or_localopt - ax_multitask VTMOP ytopt consensus @@ -51,10 +50,6 @@ Optimization Asynchronously Parallel Optimization Solver for finding Multiple Minima (APOSMM_). -- :doc:`Ax Multitask` - - Bayesian optimization with a Gaussian process driven by an Ax_ multi-task algorithm. - - :ref:`DEAP-NSGA-II` Distributed evolutionary algorithms (*community example*) diff --git a/docs/examples/gest_api/aposmm.rst b/docs/examples/gest_api/aposmm.rst index dbbd4f7ad1..def88b3d96 100644 --- a/docs/examples/gest_api/aposmm.rst +++ b/docs/examples/gest_api/aposmm.rst @@ -10,7 +10,7 @@ APOSMM APOSMM with libEnsemble ^^^^^^^^^^^^^^^^^^^^^^^ -.. literalinclude:: ../../../libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py +.. literalinclude:: ../../../libensemble/tests/regression_tests/test_aposmm_nlopt.py :linenos: :start-at: workflow = Ensemble(parse_args=True) :end-before: # Perform the run diff --git a/docs/executor/ex_base.rst b/docs/executor/ex_base.rst index ee3dd3269a..1d8a5d6bfd 100644 --- a/docs/executor/ex_base.rst +++ b/docs/executor/ex_base.rst @@ -1,13 +1,15 @@ Base Executor ============= -`Overview `__ \|\| **Base Executor** \|\| `MPI Executor `__ \|\| `Flux Executor `__ +:doc:`Overview ` || **Base Executor** || :doc:`MPI Executor ` || :doc:`Flux Executor ` .. automodule:: executor :no-undoc-members: +.. autoexception:: libensemble.executors.executor.ExecutorException + Only for running local serial-launched applications. -To run MPI applications and use detected resources, use the `MPI Executor `__ tab. +To run MPI applications and use detected resources, use the :doc:`MPI Executor ` tab. .. tab-set:: diff --git a/docs/executor/ex_flux.rst b/docs/executor/ex_flux.rst index 01509c074c..c32f2d2f36 100644 --- a/docs/executor/ex_flux.rst +++ b/docs/executor/ex_flux.rst @@ -1,7 +1,7 @@ Flux Executor ============== -`Overview `__ \|\| `Base Executor `__ \|\| `MPI Executor `__ \|\| **Flux Executor** +:doc:`Overview ` || :doc:`Base Executor ` || :doc:`MPI Executor ` || **Flux Executor** .. automodule:: flux_executor :no-undoc-members: diff --git a/docs/executor/ex_globus_compute.rst b/docs/executor/ex_globus_compute.rst index 56047cf266..ba5ab1bb3d 100644 --- a/docs/executor/ex_globus_compute.rst +++ b/docs/executor/ex_globus_compute.rst @@ -1,7 +1,7 @@ Globus Compute Executor ======================= -`Overview `__ || `Base Executor `__ || `MPI Executor `__ || **Globus Compute Executor** +:doc:`Overview ` || :doc:`Base Executor ` || :doc:`MPI Executor ` || **Globus Compute Executor** The :class:`GlobusComputeExecutor` submits Python callables to a remote `Globus Compute`_ endpoint instead of diff --git a/docs/executor/ex_index.rst b/docs/executor/ex_index.rst index 7d9e3a522c..af0f207811 100644 --- a/docs/executor/ex_index.rst +++ b/docs/executor/ex_index.rst @@ -1,6 +1,6 @@ .. _executor_index: -**Overview** || `Base Executor `__ || `MPI Executor `__ || `Flux Executor `__ || `Globus Compute Executor `__ +**Overview** || :doc:`Base Executor ` || :doc:`MPI Executor ` || :doc:`Flux Executor ` || :doc:`Globus Compute Executor ` Executors ========= diff --git a/docs/executor/ex_mpi.rst b/docs/executor/ex_mpi.rst index bddd2caa17..33a69fdd5b 100644 --- a/docs/executor/ex_mpi.rst +++ b/docs/executor/ex_mpi.rst @@ -1,7 +1,7 @@ MPI Executor ============ -`Overview `__ \|\| `Base Executor `__ \|\| **MPI Executor** \|\| `Flux Executor `__ +:doc:`Overview ` || :doc:`Base Executor ` || **MPI Executor** || :doc:`Flux Executor ` .. automodule:: mpi_executor :no-undoc-members: diff --git a/docs/executor/ex_overview.rst b/docs/executor/ex_overview.rst index 7054faedc5..c8903fee88 100644 --- a/docs/executor/ex_overview.rst +++ b/docs/executor/ex_overview.rst @@ -1,7 +1,7 @@ Overview ======== -**Overview** || `Base Executor `__ || `MPI Executor `__ || `Flux Executor `__ || `Globus Compute Executor `__ +**Overview** || :doc:`Base Executor ` || :doc:`MPI Executor ` || :doc:`Flux Executor ` || :doc:`Globus Compute Executor ` The **Executor** provides a portable interface for running applications on any system and any number of compute resources. diff --git a/docs/function_guides/generator.rst b/docs/function_guides/generator.rst index c560ce3934..3d928a6d61 100644 --- a/docs/function_guides/generator.rst +++ b/docs/function_guides/generator.rst @@ -3,7 +3,7 @@ Generators ========== -**Introduction** \|\| `Standardized Generator (gest-api) `__ \|\| `Legacy Generator Function `__ +**Introduction** || :doc:`Standardized Generator (gest-api) ` || :doc:`Legacy Generator Function ` Writing a Generator ------------------- diff --git a/docs/function_guides/generator_legacy.rst b/docs/function_guides/generator_legacy.rst index c8c155a363..ac05946413 100644 --- a/docs/function_guides/generator_legacy.rst +++ b/docs/function_guides/generator_legacy.rst @@ -1,7 +1,7 @@ Legacy Generator Function ========================= -`Introduction `__ \|\| `Standardized Generator (gest-api) `__ \|\| **Legacy Generator Function** +:doc:`Introduction ` || :doc:`Standardized Generator (gest-api) ` || **Legacy Generator Function** .. code-block:: python diff --git a/docs/function_guides/generator_standardized.rst b/docs/function_guides/generator_standardized.rst index d02c0619f7..04c614e69a 100644 --- a/docs/function_guides/generator_standardized.rst +++ b/docs/function_guides/generator_standardized.rst @@ -1,7 +1,7 @@ Standardized Generator (gest-api) ================================= -`Introduction `__ \|\| **Standardized Generator (gest-api)** \|\| `Legacy Generator Function `__ +:doc:`Introduction ` || **Standardized Generator (gest-api)** || :doc:`Legacy Generator Function ` Standardized generators are classes that inherit from ``gest_api.Generator``. They adhere to the ``gest-api`` standard and are parameterized by a ``VOCS`` diff --git a/docs/function_guides/simulator.rst b/docs/function_guides/simulator.rst index 5d69a4f79b..1918e64ea3 100644 --- a/docs/function_guides/simulator.rst +++ b/docs/function_guides/simulator.rst @@ -3,7 +3,7 @@ Simulator Functions =================== -**Introduction** \|\| `Standardized Simulator (gest-api) `__ \|\| `Legacy Simulator Function `__ +**Introduction** || :doc:`Standardized Simulator (gest-api) ` || :doc:`Legacy Simulator Function ` Simulator and :ref:`Generator functions` have relatively similar interfaces. diff --git a/docs/function_guides/simulator_legacy.rst b/docs/function_guides/simulator_legacy.rst index 3f65096abc..b4ec35edc7 100644 --- a/docs/function_guides/simulator_legacy.rst +++ b/docs/function_guides/simulator_legacy.rst @@ -1,7 +1,7 @@ Legacy Simulator Function ========================= -`Introduction `__ \|\| `Standardized Simulator (gest-api) `__ \|\| **Legacy Simulator Function** +:doc:`Introduction ` || :doc:`Standardized Simulator (gest-api) ` || **Legacy Simulator Function** .. code-block:: python diff --git a/docs/function_guides/simulator_standardized.rst b/docs/function_guides/simulator_standardized.rst index 27b72deb5f..2dcc828e70 100644 --- a/docs/function_guides/simulator_standardized.rst +++ b/docs/function_guides/simulator_standardized.rst @@ -1,7 +1,7 @@ Standardized Simulator (gest-api) ================================= -`Introduction `__ \|\| **Standardized Simulator (gest-api)** \|\| `Legacy Simulator Function `__ +:doc:`Introduction ` || **Standardized Simulator (gest-api)** || :doc:`Legacy Simulator Function ` Standardized simulators are plain callables — no base class required — with the signature:: diff --git a/docs/images/diagram_xml/balsam2.xml b/docs/images/diagram_xml/balsam2.xml deleted file mode 100644 index 4bb97c3b77..0000000000 --- a/docs/images/diagram_xml/balsam2.xml +++ /dev/null @@ -1 +0,0 @@ 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 \ No newline at end of file diff --git a/docs/latex_index.rst b/docs/latex_index.rst index e2fd0ffb90..42964ea08d 100644 --- a/docs/latex_index.rst +++ b/docs/latex_index.rst @@ -1,5 +1,7 @@ .. libEnsemble documentation master file for the latex build +:orphan: + ===== Dummy ===== diff --git a/docs/running_libE.rst b/docs/running_libE.rst index 2677eb8d25..58fe1650b8 100644 --- a/docs/running_libE.rst +++ b/docs/running_libE.rst @@ -71,30 +71,6 @@ This nesting does work with MPICH_ and its derivative MPI implementations. It is also unsuitable to use this mode when running on the **launch** nodes of three-tier systems. In that case ``local`` mode is recommended. -TCP Comms ---------- - -Run the Manager on one system and launch workers to remote -systems or nodes over TCP. Configure through -:class:`libE_specs`, or on the command line -if using an :class:`Ensemble` object with -``Ensemble(parse_args=True)``, - -**Reverse-ssh interface** - -Set ``comms`` to ``ssh`` to launch workers on remote ssh-accessible systems. This -co-locates workers, functions, and any applications. Simulator functions can be -persistent, unlike those submitted to :ref:`Globus Compute`, -which must be non-persistent. - -The remote working directory and Python need to be specified. This may resemble:: - - python myscript.py --comms ssh --workers machine1 machine2 --worker_pwd /home/workers --worker_python /home/.conda/.../python - -**Limitations of TCP mode** - -- There cannot be two calls to ``Ensemble.run()`` or ``libE()`` in the same script. - Further Command Line Options ---------------------------- diff --git a/docs/tutorials/local_sine_tutorial/local_sine_tutorial.rst b/docs/tutorials/local_sine_tutorial/local_sine_tutorial.rst index f1e392a0d0..d84004a175 100644 --- a/docs/tutorials/local_sine_tutorial/local_sine_tutorial.rst +++ b/docs/tutorials/local_sine_tutorial/local_sine_tutorial.rst @@ -2,7 +2,7 @@ Simple Introduction =================== -**Introduction** \|\| `1. Getting started `__ \|\| `2. Generator `__ \|\| `3. Simulator `__ \|\| `4. Script `__ \|\| `5. Next steps `__ +**Introduction** || :doc:`1. Getting started ` || :doc:`2. Generator ` || :doc:`3. Simulator ` || :doc:`4. Script ` || :doc:`5. Next steps ` This tutorial demonstrates the capability to perform ensembles of calculations in parallel using :doc:`libEnsemble<../../introduction>`. diff --git a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_1.rst b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_1.rst index 9523ada0f4..7ce99f315a 100644 --- a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_1.rst +++ b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_1.rst @@ -1,7 +1,7 @@ 1. Getting started ================== -`Introduction `__ \|\| **1. Getting started** \|\| `2. Generator `__ \|\| `3. Simulator `__ \|\| `4. Script `__ \|\| `5. Next steps `__ +:doc:`Introduction ` || **1. Getting started** || :doc:`2. Generator ` || :doc:`3. Simulator ` || :doc:`4. Script ` || :doc:`5. Next steps ` libEnsemble is written entirely in Python_. Let's make sure the correct version is installed. diff --git a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_2.rst b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_2.rst index 024bb52d14..adfb95c603 100644 --- a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_2.rst +++ b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_2.rst @@ -1,7 +1,7 @@ 2. Generator ============ -`Introduction `__ \|\| `1. Getting started `__ \|\| **2. Generator** \|\| `3. Simulator `__ \|\| `4. Script `__ \|\| `5. Next steps `__ +:doc:`Introduction ` || :doc:`1. Getting started ` || **2. Generator** || :doc:`3. Simulator ` || :doc:`4. Script ` || :doc:`5. Next steps ` Let's begin the coding portion of this tutorial by writing our generator. diff --git a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_3.rst b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_3.rst index 05836abf32..a1a358d420 100644 --- a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_3.rst +++ b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_3.rst @@ -1,7 +1,7 @@ 3. Simulator ============ -`Introduction `__ \|\| `1. Getting started `__ \|\| `2. Generator `__ \|\| **3. Simulator** \|\| `4. Script `__ \|\| `5. Next steps `__ +:doc:`Introduction ` || :doc:`1. Getting started ` || :doc:`2. Generator ` || **3. Simulator** || :doc:`4. Script ` || :doc:`5. Next steps ` Next, we'll write our simulator function or :ref:`sim_f`. Simulator functions perform calculations based on values from the generator. diff --git a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_4.rst b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_4.rst index 92a5c8536b..eb285c367f 100644 --- a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_4.rst +++ b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_4.rst @@ -1,7 +1,7 @@ 4. Script ========= -`Introduction `__ \|\| `1. Getting started `__ \|\| `2. Generator `__ \|\| `3. Simulator `__ \|\| **4. Script** \|\| `5. Next steps `__ +:doc:`Introduction ` || :doc:`1. Getting started ` || :doc:`2. Generator ` || :doc:`3. Simulator ` || **4. Script** || :doc:`5. Next steps ` Now lets write the script that configures our generator and simulator functions and starts libEnsemble. diff --git a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_5.rst b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_5.rst index e5045cf0ec..be660c9af0 100644 --- a/docs/tutorials/local_sine_tutorial/local_sine_tutorial_5.rst +++ b/docs/tutorials/local_sine_tutorial/local_sine_tutorial_5.rst @@ -1,7 +1,7 @@ 5. Next steps ============= -`Introduction `__ \|\| `1. Getting started `__ \|\| `2. Generator `__ \|\| `3. Simulator `__ \|\| `4. Script `__ \|\| **5. Next steps** +:doc:`Introduction ` || :doc:`1. Getting started ` || :doc:`2. Generator ` || :doc:`3. Simulator ` || :doc:`4. Script ` || **5. Next steps** **libEnsemble with MPI** diff --git a/libensemble/comms/tcp_mgr.py b/libensemble/comms/tcp_mgr.py deleted file mode 100644 index 9956896e57..0000000000 --- a/libensemble/comms/tcp_mgr.py +++ /dev/null @@ -1,126 +0,0 @@ -""" -TCP-based bidirectional communicator ------------------------------------- - -""" - -from multiprocessing import Queue -from multiprocessing.managers import BaseManager - -from libensemble.comms.comms import QComm - -queues = {} - - -def get_queue(name): - if name not in queues: - queues[name] = Queue() - return queues[name] - - -class ServerQueueManager(BaseManager): - pass - - -class ServerQCommManager: - """Set up a QComm manager server. - - The QComm manager server provides shared (networked) access to message - queues for communication between the libensemble manager and workers. - """ - - def __init__(self, port, authkey): - """Initialize the server on localhost at an indicated TCP port and key.""" - - ServerQueueManager.register("get_queue", callable=get_queue) - self.manager = ServerQueueManager(address=("", port), authkey=authkey) - self.manager.start() - - def shutdown(self): - """Shutdown the manager""" - self.manager.shutdown() - - @property - def address(self): - """Get IP address for socket.""" - return self.manager.address - - def get_queue(self, name): - """Get a queue from the shared manager""" - return self.manager.get_queue(name) - - def get_inbox(self, workerID): - """Get a worker inbox queue.""" - return self.get_queue(f"inbox{workerID}") - - def get_outbox(self, workerID): - """Get a worker outbox queue.""" - return self.get_queue(f"outbox{workerID}") - - def get_shared(self): - """Get a shared queue for worker subscription.""" - return self.get_queue("shared") - - def await_workers(self, nworkers): - """Wait for a pool of workers to join.""" - sharedq = self.get_shared() - wqueues = [] - for _ in range(nworkers): - workerID = sharedq.get() - inbox = self.get_outbox(workerID) - outbox = self.get_inbox(workerID) - wqueues.append(QComm(inbox, outbox)) - return wqueues - - def __enter__(self): - """Context enter.""" - return self - - def __exit__(self, etype, value, traceback): - """Context exit.""" - self.shutdown() - - -class ClientQCommManager: - """Set up a client to the QComm server. - - The client runs at the worker and mediates access to the shared queues - provided by the server. - """ - - def __init__(self, ip, port, authkey, workerID): - """Attach by TCP to (ip, port) with a uniquely given workerID""" - self.workerID = workerID - - class ClientQueueManager(BaseManager): - pass - - ClientQueueManager.register("get_queue") - self.manager = ClientQueueManager(address=(ip, port), authkey=authkey) - self.manager.connect() - sharedq = self.get_shared() - sharedq.put(workerID) - - def get_queue(self, name): - """Get a queue from the server.""" - return self.manager.get_queue(name) - - def get_inbox(self): - """Get this worker's inbox.""" - return self.get_queue(f"inbox{self.workerID}") - - def get_outbox(self): - """Get this worker's outbox.""" - return self.get_queue(f"outbox{self.workerID}") - - def get_shared(self): - """Get the shared queue for worker sign-up.""" - return self.get_queue("shared") - - def __enter__(self): - """Enter the context.""" - return QComm(self.get_inbox(), self.get_outbox()) - - def __exit__(self, etype, value, traceback): - """Exit the context.""" - pass diff --git a/libensemble/ensemble.py b/libensemble/ensemble.py index dc2ac806c3..d072fe1804 100644 --- a/libensemble/ensemble.py +++ b/libensemble/ensemble.py @@ -5,9 +5,9 @@ from libensemble.executors import Executor from libensemble.libE import libE from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs -from libensemble.tools import parse_args as parse_args_f from libensemble.tools import save_libE_output from libensemble.tools.parse_args import mpi_init +from libensemble.tools.parse_args import parse_args as parse_args_f from libensemble.utils.misc import specs_dump ATTR_ERR_MSG = 'Unable to load "{}". Is the function or submodule correctly named?' @@ -216,7 +216,7 @@ def ready(self) -> tuple[bool, list[str]]: - A simulation callable (``sim_f`` or ``simulator``) is set on ``sim_specs``. - At least one exit condition is configured on ``exit_criteria``. - - Workers are available (``nworkers > 0`` for local/threads/tcp comms, + - Workers are available (``nworkers > 0`` for local/threads comms, or MPI comms is set, which infers workers from the MPI communicator). - If both ``gen_specs`` and ``sim_specs`` use the classic field-name interface, the generator output field names are a superset of the simulator input field names. @@ -259,7 +259,7 @@ def ready(self) -> tuple[bool, list[str]]: # --- workers: must be determinable --- comms = getattr(self._libE_specs, "comms", "mpi") - if comms in ("local", "threads", "tcp"): + if comms in ("local", "threads"): if not self.nworkers: issues.append( f"libE_specs.comms is '{comms}' but 'nworkers' is not set. " diff --git a/libensemble/gen_classes/sampling.py b/libensemble/gen_classes/sampling.py index 0b06624480..ff097105ae 100644 --- a/libensemble/gen_classes/sampling.py +++ b/libensemble/gen_classes/sampling.py @@ -156,9 +156,7 @@ class UniformSampleWithVariableResources(LibensembleGenerator): path was tested with the default alloc. """ - def __init__( - self, vocs: VOCS, max_resource_sets: int, random_seed: int = 1, *args, **kwargs - ): + def __init__(self, vocs: VOCS, max_resource_sets: int, random_seed: int = 1, *args, **kwargs): super().__init__(vocs, *args, **kwargs) self.rng = np.random.default_rng(random_seed) self.max_rsets = max_resource_sets diff --git a/libensemble/libE.py b/libensemble/libE.py index 4a68526662..51395b467a 100644 --- a/libensemble/libE.py +++ b/libensemble/libE.py @@ -4,8 +4,7 @@ This module sets up the manager and the team of workers, configured according to the contents of :ref:`libE_specs`. The manager/worker communications scheme used in libEnsemble is parsed from the ``comms`` key if -present, with valid values being ``mpi``, ``local`` (for multiprocessing), or -``tcp``. +present, with valid values being ``mpi`` or ``local`` (for multiprocessing). MPI is the default if ``nworkers`` is not given. However, if ``libE_specs["nworkers"]`` is specified, then ``local`` comms will be used unless a parallel MPI environment @@ -109,7 +108,6 @@ __all__ = ["libE"] import logging -import os import pickle # Only used when saving output on error import socket import sys @@ -126,7 +124,6 @@ from libensemble.comms.comms import QCommProcess, QCommThread, Timeout from libensemble.comms.logs import manager_logging_config -from libensemble.comms.tcp_mgr import ClientQCommManager, ServerQCommManager from libensemble.executors.executor import Executor from libensemble.executors.mpi_executor import MPIExecutor from libensemble.history import History @@ -136,9 +133,7 @@ from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs, _EnsembleSpecs from libensemble.tools.alloc_support import AllocSupport from libensemble.tools.tools import _USER_SIM_ID_WARNING -from libensemble.utils import launcher from libensemble.utils.misc import specs_dump -from libensemble.utils.timer import Timer from libensemble.version import __version__ from libensemble.worker import worker_main @@ -260,7 +255,7 @@ def libE( logger.manager_warning("Dry run. All libE() inputs validated. Exiting.") # type: ignore[attr-defined] sys.exit() - libE_funcs = {"mpi": libE_mpi, "tcp": libE_tcp, "local": libE_local, "threads": libE_local} + libE_funcs = {"mpi": libE_mpi, "local": libE_local, "threads": libE_local} if sim_specs.get("globus_compute_endpoint"): libE_specs["_gc_only"] = True @@ -535,131 +530,6 @@ def cleanup(): ) -# ==================== TCP version ================================= - - -def get_ip(): - """Get the IP address of the current host""" - try: - return socket.gethostbyname(socket.gethostname()) - except socket.gaierror: - return "localhost" - - -def libE_tcp_default_ID(): - """Assign a (we hope unique) worker ID if not assigned by manager.""" - return f"{get_ip()}_pid{os.getpid()}" - - -def libE_tcp(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs, H0): - """Main routine for TCP multiprocessing launch of libE.""" - - is_worker = libE_specs.get("workerID") is not None - - exctr = Executor.executor - if exctr is not None: - # TCP does not currently support resource_management but when does, assume - # each TCP worker is in a different resource pool (only knowing local_host) - if not is_worker: - exctr.serial_setup() - - if is_worker: - libE_tcp_worker(sim_specs, gen_specs, libE_specs) - return [], persis_info, [] - - return libE_tcp_mgr(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs, H0) - - -def libE_tcp_worker_launcher(libE_specs): - """Get a launch function from libE_specs.""" - if "worker_launcher" in libE_specs: - worker_launcher = libE_specs["worker_launcher"] - else: - worker_cmd = libE_specs["worker_cmd"] - - def worker_launcher(specs): - """Basic worker launch function.""" - return launcher.launch(worker_cmd, specs) - - return worker_launcher - - -def libE_tcp_start_team(manager, nworkers, workers, ip, port, authkey, launchf): - """Launch nworkers workers that attach back to a managers server.""" - worker_procs = [] - specs = {"manager_ip": ip, "manager_port": port, "authkey": authkey} - with Timer() as timer: - for w in range(1, nworkers + 1): - logger.info(f"Manager is launching worker {w}") - if workers is not None: - specs["worker_ip"] = workers[w - 1] - specs["tunnel_port"] = 0x71BE - specs["workerID"] = w - worker_procs.append(launchf(specs)) - logger.info(f"Manager is awaiting {nworkers} workers") - wcomms = manager.await_workers(nworkers) - logger.info(f"Manager connected to {nworkers} workers ({timer.elapsed} s)") - return worker_procs, wcomms - - -def libE_tcp_mgr(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs, H0): - """Main routine for TCP multiprocessing launch of libE at manager.""" - hist = History(alloc_specs, sim_specs, gen_specs, exit_criteria, H0) - - # Set up a worker launcher - launchf = libE_tcp_worker_launcher(libE_specs) - - # Get worker launch parameters and fill in defaults for TCP/IP conn - if libE_specs.get("nworkers"): - workers = None - nworkers = libE_specs["nworkers"] - elif libE_specs.get("workers"): - workers = libE_specs["workers"] - nworkers = len(workers) - ip = libE_specs["ip"] or get_ip() - port = libE_specs["port"] - authkey = libE_specs["authkey"] - - with ServerQCommManager(port, authkey.encode("utf-8")) as tcp_manager: - # Get port if needed because of auto-assignment - if port == 0: - _, port = tcp_manager.address - - if not libE_specs["disable_log_files"]: - exit_logger = manager_logging_config(specs=libE_specs) - else: - exit_logger = None - - logger.info(f"Launched server at ({ip}, {port})") - - # Launch worker team and set up logger - worker_procs, wcomms = libE_tcp_start_team(tcp_manager, nworkers, workers, ip, port, authkey, launchf) - - def cleanup(): - """Handler to clean up launched team.""" - for wp in worker_procs: - launcher.cancel(wp, timeout=libE_specs["worker_timeout"]) - if exit_logger is not None: - exit_logger() - - # Run generic manager - return manager( - wcomms, sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs, hist, on_cleanup=cleanup - ) - - -def libE_tcp_worker(sim_specs, gen_specs, libE_specs): - """Main routine for TCP worker launched by libE.""" - ip = libE_specs["ip"] - port = libE_specs["port"] - authkey = libE_specs["authkey"] - workerID = libE_specs["workerID"] - - with ClientQCommManager(ip, port, authkey.encode("utf-8"), workerID) as comm: - worker_main(comm, sim_specs, gen_specs, libE_specs, workerID=workerID, log_comm=True) - logger.debug(f"Worker {workerID} exiting") - - # ==================== Additional Internal Functions =========================== diff --git a/libensemble/resources/platforms.py b/libensemble/resources/platforms.py index 07989cb05e..56e151f744 100644 --- a/libensemble/resources/platforms.py +++ b/libensemble/resources/platforms.py @@ -90,7 +90,7 @@ def check_logical_cores(self): - ``"option_gpus_per_node"``: Expresses GPUs per node on MPI runner command line. - ``"option_gpus_per_task"``: Expresses GPUs per task on MPI runner command line. - With the exception of "runner_default", the :attr:`gpu_setting_name` + With the exception of "runner_default", the :attr:`Platform.gpu_setting_name` attribute is also required when this attribute is set. If "gpu_setting_type" is not provided (same as ``runner_default``) and the diff --git a/libensemble/specs.py b/libensemble/specs.py index c95bdd8f87..4dadb786b9 100644 --- a/libensemble/specs.py +++ b/libensemble/specs.py @@ -1,4 +1,3 @@ -import random import warnings from pathlib import Path @@ -8,7 +7,6 @@ from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens from libensemble.utils.validators import ( - check_any_workers_and_disable_rm_if_tcp, check_exit_criteria, check_H0, check_input_dir_exists, @@ -445,13 +443,13 @@ class LibeSpecs(BaseModel): comms: str | None = "mpi" """ - Manager/Worker communications mode. ``'mpi'``, ``'local'``, ``'threads'``, or ``'tcp'`` + Manager/Worker communications mode. ``'mpi'``, ``'local'``, or ``'threads'``. If ``nworkers`` is specified, then ``local`` comms will be used unless a parallel MPI environment is detected. """ nworkers: int | None = 0 - """ Number of worker processes in ``"local"``, ``"threads"``, or ``"tcp"``.""" + """ Number of worker processes in ``"local"`` or ``"threads"``.""" gen_on_worker: bool = False """ Instructs libEnsemble to run generator functions on a worker rank. @@ -605,10 +603,6 @@ def check_inputs_exist(cls, value): def set_default_comms(cls, values): return set_default_comms(cls, values) - @model_validator(mode="after") - def check_any_workers_and_disable_rm_if_tcp(self): - return check_any_workers_and_disable_rm_if_tcp(self) - @model_validator(mode="after") def enable_save_H_when_every_K(self): return enable_save_H_when_every_K(self) @@ -691,28 +685,6 @@ def set_calc_dirs_on_input_dir(self): live_data: object | None = None """ Add a live data capture object (e.g., for plotting). """ - workers: list[str] | None = [] - """ TCP Only: A list of worker hostnames. """ - - ip: str | None = None - """ TCP Only: IP address for Manager's system. """ - - port: int | None = 0 - """ TCP Only: Port number for Manager's system. """ - - authkey: str | None = f"libE_auth_{random.randrange(99999)}" - """ TCP Only: Authkey for Manager's system.""" - - workerID: int | None = None - """ TCP Only: Worker ID number assigned to the new process. """ - - worker_cmd: list[str] | None = [] - """ - TCP Only: Split string corresponding to worker/client Python process invocation. Contains - a local Python path, user script, and manager/server format-fields for ``manager_ip``, - ``manager_port``, ``authkey``, and ``workerID``. ``nworkers`` is specified normally. - """ - final_gen_send: bool | None = False """ Send final simulation results to persistent generators before shutdown. diff --git a/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py b/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py index 1e59cc91cd..976e1dd035 100644 --- a/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py +++ b/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_1d_sampling_with_profile.py python test_1d_sampling_with_profile.py --nworkers 3 - python test_1d_sampling_with_profile.py --nworkers 3 --comms tcp + python test_1d_sampling_with_profile.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_1d_splitcomm.py b/libensemble/tests/functionality_tests/test_1d_splitcomm.py index c66ed569ef..27ff374e62 100644 --- a/libensemble/tests/functionality_tests/test_1d_splitcomm.py +++ b/libensemble/tests/functionality_tests/test_1d_splitcomm.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_1d_sampling.py python test_1d_sampling.py --nworkers 3 - python test_1d_sampling.py --nworkers 3 --comms tcp + python test_1d_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_1d_subcomm.py b/libensemble/tests/functionality_tests/test_1d_subcomm.py index aa0f34d0a0..cbd2bb16e0 100644 --- a/libensemble/tests/functionality_tests/test_1d_subcomm.py +++ b/libensemble/tests/functionality_tests/test_1d_subcomm.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_1d_sampling.py python test_1d_sampling.py --nworkers 3 - python test_1d_sampling.py --nworkers 3 --comms tcp + python test_1d_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_1d_super_simple.py b/libensemble/tests/functionality_tests/test_1d_super_simple.py index 04265e9ee7..6f79aab159 100644 --- a/libensemble/tests/functionality_tests/test_1d_super_simple.py +++ b/libensemble/tests/functionality_tests/test_1d_super_simple.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_1d_sampling.py python test_1d_sampling.py --nworkers 3 - python test_1d_sampling.py --nworkers 3 --comms tcp + python test_1d_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_GPU_gen_resources.py b/libensemble/tests/functionality_tests/test_GPU_gen_resources.py index eca3db0ac8..6e121d2307 100644 --- a/libensemble/tests/functionality_tests/test_GPU_gen_resources.py +++ b/libensemble/tests/functionality_tests/test_GPU_gen_resources.py @@ -28,8 +28,6 @@ # TESTSUITE_COMMS: mpi local # TESTSUITE_NPROCS: 5 -import sys - import numpy as np from libensemble.executors.mpi_executor import MPIExecutor @@ -58,9 +56,6 @@ libE_specs["reuse_output_dir"] = True dry_run = True - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run six_hump_camel_app = six_hump_camel.__file__ exctr = MPIExecutor() diff --git a/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py b/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py index 60d3401fe9..842c8b2f0e 100644 --- a/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py +++ b/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_6-hump_camel_active_persistent_worker_abort.py python test_6-hump_camel_active_persistent_worker_abort.py --nworkers 3 - python test_6-hump_camel_active_persistent_worker_abort.py --nworkers 3 --comms tcp + python test_6-hump_camel_active_persistent_worker_abort.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -12,7 +12,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/functionality_tests/test_asktell_sampling.py b/libensemble/tests/functionality_tests/test_asktell_sampling.py index 300109aa1a..7ecf0d30a7 100644 --- a/libensemble/tests/functionality_tests/test_asktell_sampling.py +++ b/libensemble/tests/functionality_tests/test_asktell_sampling.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sampling_asktell_gen.py python test_sampling_asktell_gen.py --nworkers 3 --comms local - python test_sampling_asktell_gen.py --nworkers 3 --comms tcp + python test_sampling_asktell_gen.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py b/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py index f6b703b581..81417442ba 100644 --- a/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py +++ b/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py @@ -6,7 +6,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_asktell_sampling_external_gen.py python test_asktell_sampling_external_gen.py --nworkers 3 --comms local - python test_asktell_sampling_external_gen.py --nworkers 3 --comms tcp + python test_asktell_sampling_external_gen.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 3. """ diff --git a/libensemble/tests/functionality_tests/test_calc_exception.py b/libensemble/tests/functionality_tests/test_calc_exception.py index 11a5fc52ce..5121bc0746 100644 --- a/libensemble/tests/functionality_tests/test_calc_exception.py +++ b/libensemble/tests/functionality_tests/test_calc_exception.py @@ -4,11 +4,11 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_calc_exception.py python test_calc_exception.py --nworkers 3 - python test_calc_exception.py --nworkers 3 --comms tcp + python test_calc_exception.py --nworkers 3 --comms threads """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 from gest_api.vocs import VOCS diff --git a/libensemble/tests/functionality_tests/test_cancel_in_alloc.py b/libensemble/tests/functionality_tests/test_cancel_in_alloc.py index 45e5f8ad28..8a991a1e39 100644 --- a/libensemble/tests/functionality_tests/test_cancel_in_alloc.py +++ b/libensemble/tests/functionality_tests/test_cancel_in_alloc.py @@ -8,13 +8,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_cancel_in_alloc.py python test_cancel_in_alloc.py --nworkers 3 - python test_cancel_in_alloc.py --nworkers 3 --comms tcp + python test_cancel_in_alloc.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/functionality_tests/test_comms.py b/libensemble/tests/functionality_tests/test_comms.py index de61cda5dd..2adbae1029 100644 --- a/libensemble/tests/functionality_tests/test_comms.py +++ b/libensemble/tests/functionality_tests/test_comms.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_comms.py python test_comms.py --nworkers 3 - python test_comms.py --nworkers 3 --comms tcp + python test_comms.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be N-1. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/functionality_tests/test_elapsed_time_abort.py b/libensemble/tests/functionality_tests/test_elapsed_time_abort.py index b09d94717b..abe3e1d145 100644 --- a/libensemble/tests/functionality_tests/test_elapsed_time_abort.py +++ b/libensemble/tests/functionality_tests/test_elapsed_time_abort.py @@ -4,13 +4,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_6-hump_camel_elapsed_time_abort.py python test_6-hump_camel_elapsed_time_abort.py --nworkers 3 - python test_6-hump_camel_elapsed_time_abort.py --nworkers 3 --comms tcp + python test_6-hump_camel_elapsed_time_abort.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 from gest_api.vocs import VOCS diff --git a/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py b/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py index 32785fd12d..3059af830a 100644 --- a/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py +++ b/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_evaluate_existing_sample.py python test_evaluate_existing_sample.py --nworkers 3 - python test_evaluate_existing_sample.py --nworkers 3 --comms tcp + python test_evaluate_existing_sample.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py b/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py index 83a9cbc9a2..7191c80b06 100644 --- a/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py +++ b/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_executor_hworld.py python test_executor_hworld.py --nworkers 3 - python test_executor_hworld.py --nworkers 3 --comms tcp + python test_executor_hworld.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ @@ -33,7 +33,7 @@ from libensemble.tools import parse_args # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_OS_SKIP: OSX WIN # TESTSUITE_NPROCS: 3 4 # TESTSUITE_OMPI_SKIP: true @@ -52,9 +52,6 @@ if cores_all_tasks > logical_cores: disable_resource_manager = True mess_resources = "Oversubscribing - Resource manager disabled" - elif libE_specs.get("comms", False) == "tcp": - disable_resource_manager = True - mess_resources = "TCP comms does not support resource management. Resource manager disabled" else: disable_resource_manager = False mess_resources = "Resource manager enabled" diff --git a/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py b/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py index 002d8cf113..4d233a8a4b 100644 --- a/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py +++ b/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_executor_hworld.py python test_executor_hworld.py --nworkers 3 - python test_executor_hworld.py --nworkers 3 --comms tcp + python test_executor_hworld.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ @@ -27,7 +27,7 @@ from libensemble.tools import parse_args # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 3 4 # TESTSUITE_OMPI_SKIP: true # TESTSUITE_OS_SKIP: OSX WIN @@ -46,9 +46,6 @@ if cores_all_tasks > logical_cores: disable_resource_manager = True mess_resources = "Oversubscribing - Resource manager disabled" - elif libE_specs.get("comms", False) == "tcp": - disable_resource_manager = True - mess_resources = "TCP comms does not support resource management. Resource manager disabled" else: disable_resource_manager = False mess_resources = "Resource manager enabled" @@ -92,11 +89,7 @@ exit_criteria = {"wallclock_max": 10, "sim_max": nworkers} - # TCP does not support multiple libE calls - if libE_specs["comms"] == "tcp": - iterations = 1 - else: - iterations = 2 + iterations = 2 for i in range(iterations): # Perform the run diff --git a/libensemble/tests/functionality_tests/test_executor_simple.py b/libensemble/tests/functionality_tests/test_executor_simple.py index e6d1c7468e..2f8496f187 100644 --- a/libensemble/tests/functionality_tests/test_executor_simple.py +++ b/libensemble/tests/functionality_tests/test_executor_simple.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_executor_hworld.py python test_executor_hworld.py --nworkers 3 - python test_executor_hworld.py --nworkers 3 --comms tcp + python test_executor_hworld.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_fast_alloc.py b/libensemble/tests/functionality_tests/test_fast_alloc.py index 6d49162dad..b4fb87e044 100644 --- a/libensemble/tests/functionality_tests/test_fast_alloc.py +++ b/libensemble/tests/functionality_tests/test_fast_alloc.py @@ -13,7 +13,6 @@ # TESTSUITE_NPROCS: 4 import gc -import sys import numpy as np @@ -52,12 +51,6 @@ exit_criteria = {"sim_max": 2 * num_pts, "wallclock_max": 300} - if libE_specs["comms"] == "tcp": - # Can't use the same interface for manager and worker if we want - # repeated calls to libE -- the manager sets up a different server - # each time, and the worker will not know what port to connect to. - sys.exit("Cannot run with tcp when repeated calls to libE -- aborting...") - for time in np.append([0], np.logspace(-5, -1, 2)): if is_manager: print("Starting for time: ", time, flush=True) diff --git a/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py b/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py index d83e7a13cd..00fd8f9fe9 100644 --- a/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py +++ b/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py @@ -42,7 +42,6 @@ # TESTSUITE_NPROCS: 4 7 import os -import sys import warnings import numpy as np @@ -68,9 +67,6 @@ libE_specs["num_resource_sets"] = nworkers # Persistent gen does not need resources libE_specs["use_workflow_dir"] = True # Only a place for Open MPI machinefiles - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run six_hump_camel_app = six_hump_camel.__file__ diff --git a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py index a32afe128e..f0ae3e98d0 100644 --- a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py +++ b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py @@ -22,7 +22,6 @@ # TESTSUITE_NPROCS: 3 6 import os -import sys import numpy as np @@ -48,9 +47,6 @@ # Optional for organization of output scripts libE_specs["sim_dirs_make"] = True - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run six_hump_camel_app = six_hump_camel.__file__ diff --git a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py index b29e27fe70..5a3ae681e2 100644 --- a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py +++ b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py @@ -24,7 +24,6 @@ # TESTSUITE_NPROCS: 3 6 12 import os -import sys import numpy as np @@ -49,9 +48,6 @@ libE_specs["num_resource_sets"] = nsim_workers # Persistent gen does not need resources libE_specs["use_workflow_dir"] = True # Only a place for Open MPI machinefiles - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run six_hump_camel_app = six_hump_camel.__file__ diff --git a/libensemble/tests/functionality_tests/test_mpi_runners.py b/libensemble/tests/functionality_tests/test_mpi_runners.py index da141f5681..a5bc363d64 100644 --- a/libensemble/tests/functionality_tests/test_mpi_runners.py +++ b/libensemble/tests/functionality_tests/test_mpi_runners.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_mpi_runners.py python test_mpi_runners.py --nworkers 3 - python test_mpi_runners.py --nworkers 3 --comms tcp + python test_mpi_runners.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py b/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py index c5211f33e5..da0ef675f4 100644 --- a/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py +++ b/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py @@ -6,7 +6,7 @@ Execute via one of the following commands (e.g. 4 workers): mpiexec -np 5 python test_mpi_runners_subnode.py python test_mpi_runners_subnode.py --nworkers 4 - python test_mpi_runners_subnode.py --nworkers 4 --comms tcp + python test_mpi_runners_subnode.py --nworkers 4 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py b/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py index 643a415637..2f4494fe45 100644 --- a/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py +++ b/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py @@ -6,7 +6,7 @@ Execute via one of the following commands (e.g. 5 workers): mpiexec -np 6 python test_mpi_runners_subnode_uneven.py python test_mpi_runners_subnode_uneven.py --nworkers 5 - python test_mpi_runners_subnode_uneven.py --nworkers 5 --comms tcp + python test_mpi_runners_subnode_uneven.py --nworkers 5 --comms threads """ import sys diff --git a/libensemble/tests/functionality_tests/test_new_field.py b/libensemble/tests/functionality_tests/test_new_field.py index 158edd60bf..dd5ae68ae7 100644 --- a/libensemble/tests/functionality_tests/test_new_field.py +++ b/libensemble/tests/functionality_tests/test_new_field.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_1d_sampling.py python test_1d_sampling.py --nworkers 3 - python test_1d_sampling.py --nworkers 3 --comms tcp + python test_1d_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py b/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py index 584049de61..907ea8ab29 100644 --- a/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py +++ b/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py @@ -13,8 +13,6 @@ # TESTSUITE_COMMS: mpi local # TESTSUITE_NPROCS: 4 -import sys - import numpy as np from libensemble.executors.mpi_executor import MPIExecutor @@ -39,9 +37,6 @@ libE_specs["sim_dir_copy_files"] = [".gitignore"] libE_specs["reuse_output_dir"] = True - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run six_hump_camel_app = six_hump_camel.__file__ exctr = MPIExecutor() diff --git a/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py b/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py index 7314f42fc5..2a697c91ff 100644 --- a/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py +++ b/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_sim_uniform_sampling.py python test_persistent_sim_uniform_sampling.py --nworkers 3 - python test_persistent_sim_uniform_sampling.py --nworkers 3 --comms tcp + python test_persistent_sim_uniform_sampling.py --nworkers 3 --comms threads When running with the above command, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -13,7 +13,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 # TESTSUITE_OS_SKIP: WIN diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py b/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py index 4d0e7a5eb7..ad0113edb3 100644 --- a/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py +++ b/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 5 python test_persistent_uniform_gen_decides_stop.py python test_persistent_uniform_gen_decides_stop.py --nworkers 4 - python test_persistent_uniform_gen_decides_stop.py --nworkers 4 --comms tcp + python test_persistent_uniform_gen_decides_stop.py --nworkers 4 --comms threads The number of concurrent evaluations of the objective function with 2 gens will be 2: 5 - 1 manager - 2 persistent gens = 2. diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py index e9a4c75b2b..a7e67a77ca 100644 --- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py +++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_uniform_sampling.py python test_persistent_uniform_sampling.py --nworkers 3 - python test_persistent_uniform_sampling.py --nworkers 3 --comms tcp + python test_persistent_uniform_sampling.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py index 4b36678bc3..05f97b3c98 100644 --- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py +++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_uniform_sampling_async.py python test_persistent_uniform_sampling_async.py --nworkers 3 - python test_persistent_uniform_sampling_async.py --nworkers 3 --comms tcp + python test_persistent_uniform_sampling_async.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -13,7 +13,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import sys diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py index c8e0090124..f510c27f42 100644 --- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py +++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_uniform_sampling_cancel.py python test_persistent_uniform_sampling_cancel.py --nworkers 3 - python test_persistent_uniform_sampling_cancel.py --nworkers 3 --comms tcp + python test_persistent_uniform_sampling_cancel.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py index 989222594c..691e0e0bce 100644 --- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py +++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_uniform_sampling_nonblocking.py python test_persistent_uniform_sampling_nonblocking.py --nworkers 3 - python test_persistent_uniform_sampling_nonblocking.py --nworkers 3 --comms tcp + python test_persistent_uniform_sampling_nonblocking.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -13,7 +13,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import sys diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py index c6be008da7..b66d954c13 100644 --- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py +++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g., 3 workers): mpiexec -np 4 python test_persistent_uniform_sampling_adv.py python test_persistent_uniform_sampling_running_mean.py --nworkers 3 - python test_persistent_uniform_sampling_running_mean.py --nworkers 3 --comms tcp + python test_persistent_uniform_sampling_running_mean.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the diff --git a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py index 5033339e71..36968d5913 100644 --- a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py +++ b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py @@ -70,8 +70,6 @@ }, } - # comms = libE_specs["disable_resource_manager"] = True # SH TCP testing - comms = libE_specs["comms"] node_file = "nodelist_adaptive_workers_persistent_ovsub_rsets_comms_" + str(comms) + "_wrks_" + str(nworkers) if is_manager: diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py b/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py index de91ad6158..de47d62a48 100644 --- a/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py +++ b/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sim_dirs_per_calc.py python test_sim_dirs_per_calc.py --nworkers 3 - python test_sim_dirs_per_calc.py --nworkers 3 --comms tcp + python test_sim_dirs_per_calc.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import os diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py b/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py index 751531a3bb..4f2eb22448 100644 --- a/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py +++ b/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sim_dirs_per_worker.py python test_sim_dirs_per_worker.py --nworkers 3 - python test_sim_dirs_per_worker.py --nworkers 3 --comms tcp + python test_sim_dirs_per_worker.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import os diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py b/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py index df1dc1d1fe..c4182d2dcf 100644 --- a/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py +++ b/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sim_dirs_with_exception.py python test_sim_dirs_with_exception.py --nworkers 3 - python test_sim_dirs_with_exception.py --nworkers 3 --comms tcp + python test_sim_dirs_with_exception.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import os diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py b/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py index c99a078992..d3614a0a3d 100644 --- a/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py +++ b/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sim_dirs_with_gen_dirs.py python test_sim_dirs_with_gen_dirs.py --nworkers 3 - python test_sim_dirs_with_gen_dirs.py --nworkers 3 --comms tcp + python test_sim_dirs_with_gen_dirs.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import os diff --git a/libensemble/tests/functionality_tests/test_sim_input_dir_option.py b/libensemble/tests/functionality_tests/test_sim_input_dir_option.py index f121237818..9e765b560a 100644 --- a/libensemble/tests/functionality_tests/test_sim_input_dir_option.py +++ b/libensemble/tests/functionality_tests/test_sim_input_dir_option.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sim_input_dir_option.py python test_sim_input_dir_option.py --nworkers 3 - python test_sim_input_dir_option.py --nworkers 3 --comms tcp + python test_sim_input_dir_option.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import os diff --git a/libensemble/tests/functionality_tests/test_stats_output.py b/libensemble/tests/functionality_tests/test_stats_output.py index 0f9bf7e1ae..0ee39f05da 100644 --- a/libensemble/tests/functionality_tests/test_stats_output.py +++ b/libensemble/tests/functionality_tests/test_stats_output.py @@ -15,7 +15,6 @@ # TESTSUITE_COMMS: mpi local # TESTSUITE_NPROCS: 4 -import sys import warnings import numpy as np @@ -41,9 +40,6 @@ libE_specs["sim_dirs_make"] = True - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run hello_world_app = helloworld.__file__ six_hump_camel_app = six_hump_camel.__file__ diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling.py b/libensemble/tests/functionality_tests/test_uniform_sampling.py index cffc84a25d..eaf718db3d 100644 --- a/libensemble/tests/functionality_tests/test_uniform_sampling.py +++ b/libensemble/tests/functionality_tests/test_uniform_sampling.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_uniform_sampling.py python test_uniform_sampling.py --nworkers 3 - python test_uniform_sampling.py --nworkers 3 --comms tcp + python test_uniform_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import datetime diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py b/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py index 98e2b7814d..d5cf39492e 100644 --- a/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py +++ b/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_uniform_sampling_cancel.py python test_uniform_sampling_cancel.py --nworkers 3 - python test_uniform_sampling_cancel.py --nworkers 3 --comms tcp + python test_uniform_sampling_cancel.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py b/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py index 68364a3ead..290923e20b 100644 --- a/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py +++ b/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py @@ -17,7 +17,6 @@ # TESTSUITE_COMMS: mpi # TESTSUITE_NPROCS: 4 -import sys from copy import deepcopy import numpy as np @@ -34,11 +33,6 @@ # Main block is necessary only when using local comms with spawn start method (default on macOS and Windows). if __name__ == "__main__": nworkers, is_manager, libE_specs, _ = parse_args() - if libE_specs["comms"] == "tcp": - # Can't use the same interface for manager and worker if we want - # repeated calls to libE -- the manager sets up a different server - # each time, and the worker will not know what port to connect to. - sys.exit("Cannot run with tcp when repeated calls to libE -- aborting...") # Declare the run parameters/functions m = 214 diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py b/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py index ae8b8b4f87..4c9e662dbc 100644 --- a/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py +++ b/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_uniform_sampling_then_persistent_localopt_runs.py python test_uniform_sampling_then_persistent_localopt_runs.py --nworkers 3 - python test_uniform_sampling_then_persistent_localopt_runs.py --nworkers 3 --comms tcp + python test_uniform_sampling_then_persistent_localopt_runs.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -13,7 +13,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py b/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py index cf6eda18aa..f0b3fb2dee 100644 --- a/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py +++ b/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py @@ -16,7 +16,6 @@ # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true -import sys from multiprocessing import set_start_method import numpy as np @@ -38,9 +37,6 @@ en_suffix = str(nworkers) + "_" + libE_specs.get("comms") libE_specs["ensemble_dir_path"] = "./ensemble_diff_nodes_w" + en_suffix - if libE_specs["comms"] == "tcp": - sys.exit("This test only runs with MPI or local -- aborting...") - # Get paths for applications to run hello_world_app = helloworld.__file__ six_hump_camel_app = six_hump_camel.__file__ diff --git a/libensemble/tests/functionality_tests/test_worker_exceptions.py b/libensemble/tests/functionality_tests/test_worker_exceptions.py index 72c7ca98b0..2da9857558 100644 --- a/libensemble/tests/functionality_tests/test_worker_exceptions.py +++ b/libensemble/tests/functionality_tests/test_worker_exceptions.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_worker_exceptions.py python test_worker_exceptions.py --nworkers 3 - python test_worker_exceptions.py --nworkers 3 --comms tcp + python test_worker_exceptions.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 from gest_api.vocs import VOCS diff --git a/libensemble/tests/functionality_tests/test_workflow_dir.py b/libensemble/tests/functionality_tests/test_workflow_dir.py index 4a51c31f96..597674f849 100644 --- a/libensemble/tests/functionality_tests/test_workflow_dir.py +++ b/libensemble/tests/functionality_tests/test_workflow_dir.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_sim_input_dir_option.py python test_sim_input_dir_option.py --nworkers 3 - python test_sim_input_dir_option.py --nworkers 3 --comms tcp + python test_sim_input_dir_option.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import os diff --git a/libensemble/tests/regression_tests/test_1d_sampling.py b/libensemble/tests/regression_tests/test_1d_sampling.py index efa3572cbd..61a4b3b166 100644 --- a/libensemble/tests/regression_tests/test_1d_sampling.py +++ b/libensemble/tests/regression_tests/test_1d_sampling.py @@ -4,13 +4,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_1d_sampling.py python test_1d_sampling.py --nworkers 3 - python test_1d_sampling.py --nworkers 3 --comms tcp + python test_1d_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local threads tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 from gest_api.vocs import VOCS diff --git a/libensemble/tests/regression_tests/test_2d_sampling.py b/libensemble/tests/regression_tests/test_2d_sampling.py index bf5c63efcd..a4155826e6 100644 --- a/libensemble/tests/regression_tests/test_2d_sampling.py +++ b/libensemble/tests/regression_tests/test_2d_sampling.py @@ -4,13 +4,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_2d_sampling.py python test_2d_sampling.py --nworkers 3 - python test_2d_sampling.py --nworkers 3 --comms tcp + python test_2d_sampling.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local threads tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/regression_tests/test_2d_sampling_vocs.py b/libensemble/tests/regression_tests/test_2d_sampling_vocs.py index 92382680b6..4585e2c375 100644 --- a/libensemble/tests/regression_tests/test_2d_sampling_vocs.py +++ b/libensemble/tests/regression_tests/test_2d_sampling_vocs.py @@ -5,11 +5,11 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_2d_sampling_vocs.py python test_2d_sampling_vocs.py --nworkers 3 - python test_2d_sampling_vocs.py --nworkers 3 --comms tcp + python test_2d_sampling_vocs.py --nworkers 3 --comms threads """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local threads tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/regression_tests/test_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_aposmm_nlopt.py index 40ebcc4978..9ddc2f2775 100644 --- a/libensemble/tests/regression_tests/test_aposmm_nlopt.py +++ b/libensemble/tests/regression_tests/test_aposmm_nlopt.py @@ -4,14 +4,14 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_aposmm_nlopt.py python test_aposmm_nlopt.py --nworkers 3 --comms local - python test_aposmm_nlopt.py --nworkers 3 --comms tcp + python test_aposmm_nlopt.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 3, as the generator runs on the manager. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 from math import gamma, pi, sqrt diff --git a/libensemble/tests/regression_tests/test_aposmm_scipy.py b/libensemble/tests/regression_tests/test_aposmm_scipy.py index 7a24588d2c..ffb3963aa3 100644 --- a/libensemble/tests/regression_tests/test_aposmm_scipy.py +++ b/libensemble/tests/regression_tests/test_aposmm_scipy.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_aposmm_scipy.py python test_aposmm_scipy.py --nworkers 3 --comms local - python test_aposmm_scipy.py --nworkers 3 --comms tcp + python test_aposmm_scipy.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 3, as the generator runs on the manager. diff --git a/libensemble/tests/regression_tests/test_aposmm_timeout.py b/libensemble/tests/regression_tests/test_aposmm_timeout.py index 3ece7bbb3d..8646b93890 100644 --- a/libensemble/tests/regression_tests/test_aposmm_timeout.py +++ b/libensemble/tests/regression_tests/test_aposmm_timeout.py @@ -4,14 +4,14 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_aposmm_timeout.py python test_aposmm_timeout.py --nworkers 3 --comms local - python test_aposmm_timeout.py --nworkers 3 --comms tcp + python test_aposmm_timeout.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 3, as the generator runs on the manager. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_evaluate_existing_sample.py b/libensemble/tests/regression_tests/test_evaluate_existing_sample.py index 3aac366e7e..c4adcfd0f7 100644 --- a/libensemble/tests/regression_tests/test_evaluate_existing_sample.py +++ b/libensemble/tests/regression_tests/test_evaluate_existing_sample.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_evaluate_existing_sample.py python test_evaluate_existing_sample.py --nworkers 3 - python test_evaluate_existing_sample.py --nworkers 3 --comms tcp + python test_evaluate_existing_sample.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/regression_tests/test_evaluate_mixed_sample.py b/libensemble/tests/regression_tests/test_evaluate_mixed_sample.py index 38f9566fed..5f607e4153 100644 --- a/libensemble/tests/regression_tests/test_evaluate_mixed_sample.py +++ b/libensemble/tests/regression_tests/test_evaluate_mixed_sample.py @@ -5,13 +5,13 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_evaluate_mixed_sample.py python test_evaluate_mixed_sample.py --nworkers 3 - python test_evaluate_mixed_sample.py --nworkers 3 --comms tcp + python test_evaluate_mixed_sample.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import warnings diff --git a/libensemble/tests/regression_tests/test_inverse_bayes_example.py b/libensemble/tests/regression_tests/test_inverse_bayes_example.py index 7676dd8079..abd5fb9761 100644 --- a/libensemble/tests/regression_tests/test_inverse_bayes_example.py +++ b/libensemble/tests/regression_tests/test_inverse_bayes_example.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_inverse_bayes_example.py python test_inverse_bayes_example.py --nworkers 3 - python test_inverse_bayes_example.py --nworkers 3 --comms tcp + python test_inverse_bayes_example.py --nworkers 3 --comms threads Debugging: mpiexec -np 4 xterm -e "python inverse_bayes_example.py" @@ -15,7 +15,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 import numpy as np diff --git a/libensemble/tests/regression_tests/test_mfkg_branin.py b/libensemble/tests/regression_tests/test_mfkg_branin.py index d28dc0bc1b..9184b534a7 100644 --- a/libensemble/tests/regression_tests/test_mfkg_branin.py +++ b/libensemble/tests/regression_tests/test_mfkg_branin.py @@ -18,7 +18,7 @@ Execute via one of the following commands: mpiexec -np 5 python run_botorch_mfkg_branin.py python run_botorch_mfkg_branin.py --nworkers 4 - python run_botorch_mfkg_branin.py --nworkers 4 --comms tcp + python run_botorch_mfkg_branin.py --nworkers 4 --comms threads With ``--nworkers 4`` one worker is the generator and three concurrently evaluate the objective. diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py b/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py index f73f7e6939..223f647087 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py @@ -6,7 +6,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_aposmm_dfols.py python test_persistent_aposmm_dfols.py --nworkers 3 - python test_persistent_aposmm_dfols.py --nworkers 3 --comms tcp + python test_persistent_aposmm_dfols.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -14,7 +14,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py b/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py index 1d8eefb854..7e0ed1d503 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py @@ -17,7 +17,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_OS_SKIP: OSX WIN # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py index 28da42d53a..052134d909 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_aposmm_nlopt.py python test_persistent_aposmm_nlopt.py --nworkers 3 - python test_persistent_aposmm_nlopt.py --nworkers 3 --comms tcp + python test_persistent_aposmm_nlopt.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -12,7 +12,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 3 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py b/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py index 9a74249952..fb5ce75a33 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py @@ -6,7 +6,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_aposmm_pounders.py python test_persistent_aposmm_pounders.py --nworkers 3 - python test_persistent_aposmm_pounders.py --nworkers 3 --comms tcp + python test_persistent_aposmm_pounders.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -14,7 +14,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py index 8e057f80ad..d4747c52d8 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_aposmm_tao_blmvm.py python test_persistent_aposmm_tao_blmvm.py --nworkers 3 - python test_persistent_aposmm_tao_blmvm.py --nworkers 3 --comms tcp + python test_persistent_aposmm_tao_blmvm.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -12,7 +12,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py index 3dfe488fa5..3fa4bf0662 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_aposmm_tao_nm.py python test_persistent_aposmm_tao_nm.py --nworkers 3 - python test_persistent_aposmm_tao_nm.py --nworkers 3 --comms tcp + python test_persistent_aposmm_tao_nm.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -12,7 +12,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py b/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py index 79cc04afc7..5bedd2b18d 100644 --- a/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py +++ b/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_aposmm_with_grad.py python test_persistent_aposmm_with_grad.py --nworkers 3 - python test_persistent_aposmm_with_grad.py --nworkers 3 --comms tcp + python test_persistent_aposmm_with_grad.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -13,7 +13,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: local mpi tcp +# TESTSUITE_COMMS: local mpi threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true diff --git a/libensemble/tests/regression_tests/test_persistent_surmise_calib.py b/libensemble/tests/regression_tests/test_persistent_surmise_calib.py index 3820bfdec8..978ce2b323 100644 --- a/libensemble/tests/regression_tests/test_persistent_surmise_calib.py +++ b/libensemble/tests/regression_tests/test_persistent_surmise_calib.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_surmise_calib.py python test_persistent_surmise_calib.py --nworkers 3 - python test_persistent_surmise_calib.py --nworkers 3 --comms tcp + python test_persistent_surmise_calib.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -22,7 +22,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true # TESTSUITE_OS_SKIP: OSX diff --git a/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py b/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py index d3f79de1c0..0904cf26a5 100644 --- a/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py +++ b/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py @@ -4,7 +4,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_persistent_surmise_killsims.py python test_persistent_surmise_killsims.py --nworkers 3 - python test_persistent_surmise_killsims.py --nworkers 3 --comms tcp + python test_persistent_surmise_killsims.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, as one of the three workers will be the @@ -22,7 +22,7 @@ """ # Do not change these lines - they are parsed by run-tests.sh -# TESTSUITE_COMMS: mpi local tcp +# TESTSUITE_COMMS: mpi local threads # TESTSUITE_NPROCS: 4 # TESTSUITE_EXTRA: true # TESTSUITE_OS_SKIP: OSX diff --git a/libensemble/tests/regression_tests/test_proxystore_integration.py b/libensemble/tests/regression_tests/test_proxystore_integration.py index 22e4472868..04f5c6d274 100644 --- a/libensemble/tests/regression_tests/test_proxystore_integration.py +++ b/libensemble/tests/regression_tests/test_proxystore_integration.py @@ -5,7 +5,7 @@ Execute via one of the following commands (e.g. 3 workers): mpiexec -np 4 python test_evaluate_existing_sample.py python test_evaluate_existing_sample.py --nworkers 3 - python test_evaluate_existing_sample.py --nworkers 3 --comms tcp + python test_evaluate_existing_sample.py --nworkers 3 --comms threads The number of concurrent evaluations of the objective function will be 4-1=3. """ diff --git a/libensemble/tests/regression_tests/test_with_app_persistent_aposmm_tao_nm.py b/libensemble/tests/regression_tests/test_with_app_persistent_aposmm_tao_nm.py index 77f200aaf4..44559f7f35 100644 --- a/libensemble/tests/regression_tests/test_with_app_persistent_aposmm_tao_nm.py +++ b/libensemble/tests/regression_tests/test_with_app_persistent_aposmm_tao_nm.py @@ -8,7 +8,7 @@ Execute via one of the following commands (e.g., 3 workers): mpiexec -np 4 python test_persistent_aposmm_tao_nm.py python test_with_app_persistent_aposmm_tao_nm.py --nworkers 3 - python test_with_app_persistent_aposmm_tao_nm.py --nworkers 3 --comms tcp + python test_with_app_persistent_aposmm_tao_nm.py --nworkers 3 --comms threads When running with the above commands, the number of concurrent evaluations of the objective function will be 2, since one of the three workers will be the diff --git a/libensemble/tests/run_tests.py b/libensemble/tests/run_tests.py index e566d451f5..5dfe2ff521 100755 --- a/libensemble/tests/run_tests.py +++ b/libensemble/tests/run_tests.py @@ -335,7 +335,6 @@ def parse_arguments(): parser.add_argument("-r", action="store_true", help="Run only the regression tests") parser.add_argument("-m", action="store_true", help="Run the regression tests using MPI comms") parser.add_argument("-l", action="store_true", help="Run the regression tests using Local comms") - parser.add_argument("-t", action="store_true", help="Run the regression tests using TCP comms") parser.add_argument("-e", action="store_true", help="Run extra unit and regression tests") parser.add_argument("-A", metavar="", help="Supply arguments to python") parser.add_argument("-a", metavar="", help="Supply a string of args to add to mpiexec line") @@ -367,10 +366,8 @@ def run_regression_tests(root_dir, python_exec, args, current_os): user_comms_list.append("mpi") if args.l: user_comms_list.append("local") - if args.t: - user_comms_list.append("tcp") if not user_comms_list: - user_comms_list = ["mpi", "local", "tcp"] + user_comms_list = ["mpi", "local"] print_heading(f"Running regression tests (comms: {', '.join(user_comms_list)})") if not REG_LIST_TESTS_ONLY: diff --git a/libensemble/tests/unit_tests/test_models.py b/libensemble/tests/unit_tests/test_models.py index 01341ed94b..3dd3ba3cda 100644 --- a/libensemble/tests/unit_tests/test_models.py +++ b/libensemble/tests/unit_tests/test_models.py @@ -78,19 +78,11 @@ def test_sim_gen_alloc_exit_specs_invalid(): def test_libe_specs(): sim_specs, gen_specs, exit_criteria = setup.make_criteria_and_specs_0() libE_specs = {"mpi_comm": Fake_MPI(), "comms": "mpi"} - ls = LibeSpecs.model_validate(libE_specs) + LibeSpecs.model_validate(libE_specs) libE_specs["sim_input_dir"] = "." libE_specs["sim_dir_copy_files"] = ["."] - ls = LibeSpecs.model_validate(libE_specs) - - libE_specs = {"comms": "tcp", "nworkers": 4} - - ls = LibeSpecs.model_validate(libE_specs) - assert ls.disable_resource_manager, "resource manager should be disabled when using tcp comms" - - libE_specs = {"comms": "tcp", "workers": ["hello.host"]} - ls = LibeSpecs.model_validate(libE_specs) + LibeSpecs.model_validate(libE_specs) def test_libe_specs_invalid(): diff --git a/libensemble/tools/parse_args.py b/libensemble/tools/parse_args.py index 9f52129d9b..377120f111 100644 --- a/libensemble/tools/parse_args.py +++ b/libensemble/tools/parse_args.py @@ -1,7 +1,6 @@ import argparse import os import sys -from pathlib import Path # ==================== Command-line argument parsing =========================== @@ -11,7 +10,7 @@ "--comms", type=str, nargs="?", - choices=["local", "threads", "tcp", "ssh", "client", "mpi"], + choices=["local", "threads", "mpi"], help="Type of communicator", ) parser.add_argument("-n", "--nworkers", type=int, nargs="?", help="Number of local forked processes") @@ -83,70 +82,6 @@ def _local_parse_args(args): return nworkers, True, libE_specs, args.tester_args -def _tcp_parse_args(args): - """Parses arguments for local TCP connections""" - nworkers = args.nworkers or 4 - cmd = [ - sys.executable, - sys.argv[0], - "--comms", - "client", - "--server", - "{manager_ip}", - "{manager_port}", - "{authkey}", - "--workerID", - "{workerID}", - "--nworkers", - str(nworkers), - ] - libE_specs = {"nworkers": nworkers, "worker_cmd": cmd, "comms": "tcp"} - return nworkers, True, libE_specs, args.tester_args - - -def _ssh_parse_args(args): - """Parses arguments for SSH with reverse tunnel.""" - nworkers = len(args.workers) - worker_pwd = Path(args.worker_pwd) if args.worker_pwd else Path.cwd() - script_dir, script_name = os.path.split(sys.argv[0]) - worker_script_name = worker_pwd / script_name - ssh = ["ssh", "-R", "{tunnel_port}:localhost:{manager_port}", "{worker_ip}"] - cmd = [ - args.worker_python, - worker_script_name, - "--comms", - "client", - "--server", - "localhost", - "{tunnel_port}", - "{authkey}", - "--workerID", - "{workerID}", - "--nworkers", - str(nworkers), - ] - cmd = " ".join(cmd) - cmd = f"( cd {worker_pwd} ; {cmd} )" - ssh.append(cmd) - libE_specs = {"workers": args.workers, "worker_cmd": ssh, "ip": "localhost", "comms": "tcp"} - return nworkers, True, libE_specs, args.tester_args - - -def _client_parse_args(args): - """Parses arguments for a TCP client.""" - nworkers = args.nworkers or 4 - ip, port, authkey = args.server - libE_specs = { - "ip": ip, - "port": int(port), - "authkey": authkey, - "workerID": args.workerID, - "nworkers": nworkers, - "comms": "tcp", - } - return nworkers, False, libE_specs, args.tester_args - - def parse_args(): """ Parses command-line arguments. @@ -171,7 +106,7 @@ def parse_args(): Usage:: - usage: test_... [-h] [--comms [{local, tcp, ssh, client, mpi}]] + usage: test_... [-h] [--comms [{local, threads, mpi}]] [--nworkers [NWORKERS]] [--workers WORKERS [WORKERS ...]] [--nsim_workers [NSIM_WORKERS]] [--nresource_sets [NRESOURCE_SETS]] @@ -186,7 +121,7 @@ def parse_args(): --comms, Communications medium for manager and workers. Default is 'local' if --nworkers is provided, otherwise 'mpi'. - --nworkers/-n, (For 'local' or 'tcp' comms) Set number of workers. + --nworkers/-n, (For 'local' or 'threads' comms) Set number of workers. --nresource_sets, Explicitly set the number of resource sets. This sets libE_specs["num_resource_sets"]. By default, resources will be divided by workers. @@ -240,9 +175,6 @@ def parse_args(): "mpi": _mpi_parse_args, "local": _local_parse_args, "threads": _local_parse_args, - "tcp": _tcp_parse_args, - "ssh": _ssh_parse_args, - "client": _client_parse_args, } if args.pwd is not None: os.chdir(args.pwd) diff --git a/libensemble/tools/test_support.py b/libensemble/tools/test_support.py index bad9c2a789..7e07271253 100644 --- a/libensemble/tools/test_support.py +++ b/libensemble/tools/test_support.py @@ -244,9 +244,9 @@ def check_gpu_setting(task, assert_setting=True, print_setting=False, resources= if assert_setting: if isinstance(expected, dict): for key, value in expected.items(): - assert key in gpu_setting, ( - f"Worker {task.workerID}: Expected env key '{key}' not found in GPU setting: {gpu_setting}" - ) + assert ( + key in gpu_setting + ), f"Worker {task.workerID}: Expected env key '{key}' not found in GPU setting: {gpu_setting}" assert gpu_setting[key] == value, ( f"Worker {task.workerID}: GPU setting key '{key}' has value '{gpu_setting[key]}', " f"expected '{value}'" diff --git a/libensemble/utils/validators.py b/libensemble/utils/validators.py index c1fee67ac8..f3ef50efc6 100644 --- a/libensemble/utils/validators.py +++ b/libensemble/utils/validators.py @@ -57,7 +57,7 @@ def check_valid_in(cls, v): def check_valid_comms_type(cls, value): - assert value in ["mpi", "local", "threads", "tcp"], "Invalid comms type" + assert value in ["mpi", "local", "threads"], "Invalid comms type" return value @@ -109,19 +109,6 @@ def check_mpi_runner_type(cls, value): return value -def check_any_workers_and_disable_rm_if_tcp(values): - comms_type = scg(values, "comms") - if comms_type in ["local", "tcp"]: - if scg(values, "nworkers"): - assert scg(values, "nworkers") >= 1, "Must specify at least one worker" - else: - if comms_type == "tcp": - assert scg(values, "workers"), "Without nworkers, must specify worker hosts on TCP" - if comms_type == "tcp": - scs(values, "disable_resource_manager", True) # Resource management not supported with TCP - return values - - def set_default_comms(cls, values): return default_comms(values) diff --git a/pyproject.toml b/pyproject.toml index fa82ba28d4..85fba92fce 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -141,9 +141,6 @@ latexmk = ">=4.88,<5" fonts-conda-forge = ">=1,<2" imagemagick = ">=7.1.2_16,<8" -[tool.pixi.tasks.build-docs] -cmd = "cd docs && make html" - [tool.pixi.tasks.build-pdf] cmd = "cd docs && make latexpdf"