{"id":21343537,"url":"https://github.com/cloudmercato/sudoku-ml-benchmark","last_synced_at":"2025-10-13T05:13:58.735Z","repository":{"id":44691265,"uuid":"449521326","full_name":"cloudmercato/sudoku-ml-benchmark","owner":"cloudmercato","description":"Tensorflow Sudoku solver 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Sudoku Solver Benchmark\r\n==================================\r\n\r\nBenchmark tool evaluating training and inference from `sudoku-ml \u003chttps://github.com/cloudmercato/sudoku-ml\u003e`_.\r\n\r\n\r\nInstall\r\n-------\r\n\r\n::\r\n\r\n  pip install https://github.com/cloudmercato/sudoku-game/archive/refs/heads/master.zip\r\n  pip install https://github.com/cloudmercato/sudoku-ml/archive/refs/heads/master.zip\r\n  pip install https://github.com/cloudmercato/sudoku-ml-benchmark/archive/refs/heads/master.zip\r\n  \r\nUsage\r\n-----\r\n\r\n::\r\n\r\n  usage: sudoku-ml-bench [-h] [--batch-size BATCH_SIZE] [--epochs EPOCHS]\r\n                         [--train-dataset-size TRAIN_DATASET_SIZE]\r\n                         [--train-removed TRAIN_REMOVED]\r\n                         [--infer-dataset-size INFER_DATASET_SIZE]\r\n                         [--infer-removed INFER_REMOVED]\r\n                         [--generator-processes GENERATOR_PROCESSES]\r\n                         [--model-path MODEL_PATH]\r\n                         [--model-load-file MODEL_LOAD_FILE]\r\n                         [--model-save-file MODEL_SAVE_FILE] [--log-dir LOG_DIR]\r\n                         [--tf-log-device] [--tf-dump-debug-info]\r\n                         [--tf-profiler-port TF_PROFILER_PORT]\r\n                         [--verbose VERBOSE] [--tf-verbose TF_VERBOSE]\r\n\r\n  optional arguments:\r\n    -h, --help            show this help message and exit\r\n    --batch-size BATCH_SIZE\r\n    --epochs EPOCHS\r\n    --train-dataset-size TRAIN_DATASET_SIZE\r\n    --train-removed TRAIN_REMOVED\r\n    --infer-dataset-size INFER_DATASET_SIZE\r\n    --infer-removed INFER_REMOVED\r\n    --generator-processes GENERATOR_PROCESSES\r\n    --model-path MODEL_PATH\r\n                          Python path to the model to compile\r\n    --model-load-file MODEL_LOAD_FILE\r\n                          Model load file path (h5)\r\n    --model-save-file MODEL_SAVE_FILE\r\n                          Model save file path (h5)\r\n    --log-dir LOG_DIR     Tensorboard log directory\r\n    --tf-log-device       Determines whether TF compute device info is\r\n                          displayed.\r\n    --tf-dump-debug-info\r\n    --tf-profiler-port TF_PROFILER_PORT\r\n    --verbose VERBOSE, -v VERBOSE\r\n    --tf-verbose TF_VERBOSE, -tfv TF_VERBOSE\r\n    \r\nDocker support\r\n--------------\r\n\r\nDockerfile for classic Tensorflow and the GPU version are available: ::\r\n\r\n  # For CPU\r\n  docker build -f Dockerfile -t sudoku-ml-bench .\r\n  docker run -it sudoku-ml-bench\r\n  \r\n  # For GPU\r\n  docker build -f Dockerfile-gpu -t sudoku-ml-bench-gpu .\r\n  docker run --gpus all --ipc=host -it sudoku-ml-bench-gpu\r\n  # Add -e TF_CPP_MIN_LOG_LEVEL=3 to catch only the JSON output\r\n  \r\nThe commands above will run a training, then save an inference. You can mount a volume on `/models/` to keep it. In the same idea you can mount a volume on `/log_dir/`, to retrive the Tensorboard data.\r\n  \r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcloudmercato%2Fsudoku-ml-benchmark","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcloudmercato%2Fsudoku-ml-benchmark","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcloudmercato%2Fsudoku-ml-benchmark/lists"}