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jan-janssen merged 2 commits into from
Dec 20, 2024
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Update Documentation #531

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30fa4f5
Update __init__.py
jan-janssen Dec 20, 2024
fe31cb9
Update trouble_shooting.md
jan-janssen Dec 20, 2024
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6 changes: 3 additions & 3 deletions docs/trouble_shooting.md
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Expand Up @@ -31,9 +31,9 @@ performance computing installations Python 3.12 is the recommended Python verion

## Resource Dictionary
The resource dictionary parameter `resource_dict` can contain one or more of the following options:
* `cores_per_worker` (int): number of MPI cores to be used for each function call
* `cores` (int): number of MPI cores to be used for each function call
* `threads_per_core` (int): number of OpenMP threads to be used for each function call
* `gpus_per_worker` (int): number of GPUs per worker - defaults to 0
* `gpus_per_core` (int): number of GPUs per worker - defaults to 0
* `cwd` (str/None): current working directory where the parallel python task is executed
* `openmpi_oversubscribe` (bool): adds the `--oversubscribe` command line flag (OpenMPI and SLURM only) - default False
* `slurm_cmd_args` (list): Additional command line arguments for the srun call (SLURM only)
Expand All @@ -54,4 +54,4 @@ high performance computing (HPC) clusters via SSH, this functionality is not sup
is the use of [cloudpickle](https://github.com/cloudpipe/cloudpickle) for serialization inside executorlib, this requires
the same Python version and dependencies on both computer connected via SSH. As tracking those parameters is rather
complicated the SSH connection functionality of [pysqa](https://pysqa.readthedocs.io) is not officially supported in
executorlib.
executorlib.
4 changes: 2 additions & 2 deletions executorlib/__init__.py
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Expand Up @@ -35,9 +35,9 @@ class Executor:
cache_directory (str, optional): The directory to store cache files. Defaults to "cache".
max_cores (int): defines the number cores which can be used in parallel
resource_dict (dict): A dictionary of resources required by the task. With the following keys:
- cores_per_worker (int): number of MPI cores to be used for each function call
- cores (int): number of MPI cores to be used for each function call
- threads_per_core (int): number of OpenMP threads to be used for each function call
- gpus_per_worker (int): number of GPUs per worker - defaults to 0
- gpus_per_core (int): number of GPUs per worker - defaults to 0
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💡 Codebase verification

Parameter naming inconsistency detected across codebase

The verification reveals inconsistent parameter naming between the docstring and actual implementation:

  • The docstring uses cores, threads_per_core, and gpus_per_core
  • The codebase still uses old parameter names like cores_per_worker and gpus_per_worker in multiple files:
    • executorlib/standalone/inputcheck.py
    • executorlib/interactive/executor.py
    • executorlib/standalone/serialize.py
    • tests/test_shared_input_check.py

This inconsistency needs to be addressed to maintain code clarity and prevent potential bugs.

🔗 Analysis chain

Verify complete parameter renaming across codebase

Let's ensure there are no remaining occurrences of the old parameter names to maintain consistency.

🏁 Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Search for any remaining instances of old parameter names
echo "Checking for old parameter names..."
rg -i "cores_per_worker|gpus_per_worker" --type py --type md

# Search for new parameter names to verify consistent usage
echo -e "\nVerifying new parameter names..."
rg -i "cores.*=|gpus_per_core" --type py --type md

Length of output: 14477

- cwd (str/None): current working directory where the parallel python task is executed
- openmpi_oversubscribe (bool): adds the `--oversubscribe` command line flag (OpenMPI and
SLURM only) - default False
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