https://github.com/cloudmercato/sudoku-ml-benchmark

Tensorflow Sudoku solver benchmark
https://github.com/cloudmercato/sudoku-ml-benchmark

Last synced: 8 months ago
JSON representation

Tensorflow Sudoku solver benchmark

• Host: GitHub
• URL: https://github.com/cloudmercato/sudoku-ml-benchmark
• Owner: cloudmercato
• Created: 2022-01-19T02:34:40.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-03-01T23:48:57.000Z (over 4 years ago)
• Last Synced: 2025-01-22T15:47:54.762Z (over 1 year ago)
• Language: Python
• Size: 15.6 KB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst

Awesome Lists containing this project

README

          
Tensorflow Sudoku Solver Benchmark

==================================

Benchmark tool evaluating training and inference from `sudoku-ml `_.

Install

-------

::

  pip install https://github.com/cloudmercato/sudoku-game/archive/refs/heads/master.zip

  pip install https://github.com/cloudmercato/sudoku-ml/archive/refs/heads/master.zip

  pip install https://github.com/cloudmercato/sudoku-ml-benchmark/archive/refs/heads/master.zip

  

Usage

-----

::

  usage: sudoku-ml-bench [-h] [--batch-size BATCH_SIZE] [--epochs EPOCHS]

                         [--train-dataset-size TRAIN_DATASET_SIZE]

                         [--train-removed TRAIN_REMOVED]

                         [--infer-dataset-size INFER_DATASET_SIZE]

                         [--infer-removed INFER_REMOVED]

                         [--generator-processes GENERATOR_PROCESSES]

                         [--model-path MODEL_PATH]

                         [--model-load-file MODEL_LOAD_FILE]

                         [--model-save-file MODEL_SAVE_FILE] [--log-dir LOG_DIR]

                         [--tf-log-device] [--tf-dump-debug-info]

                         [--tf-profiler-port TF_PROFILER_PORT]

                         [--verbose VERBOSE] [--tf-verbose TF_VERBOSE]

  optional arguments:

    -h, --help            show this help message and exit

    --batch-size BATCH_SIZE

    --epochs EPOCHS

    --train-dataset-size TRAIN_DATASET_SIZE

    --train-removed TRAIN_REMOVED

    --infer-dataset-size INFER_DATASET_SIZE

    --infer-removed INFER_REMOVED

    --generator-processes GENERATOR_PROCESSES

    --model-path MODEL_PATH

                          Python path to the model to compile

    --model-load-file MODEL_LOAD_FILE

                          Model load file path (h5)

    --model-save-file MODEL_SAVE_FILE

                          Model save file path (h5)

    --log-dir LOG_DIR     Tensorboard log directory

    --tf-log-device       Determines whether TF compute device info is

                          displayed.

    --tf-dump-debug-info

    --tf-profiler-port TF_PROFILER_PORT

    --verbose VERBOSE, -v VERBOSE

    --tf-verbose TF_VERBOSE, -tfv TF_VERBOSE

    

Docker support

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

Dockerfile for classic Tensorflow and the GPU version are available: ::

  # For CPU

  docker build -f Dockerfile -t sudoku-ml-bench .

  docker run -it sudoku-ml-bench

  

  # For GPU

  docker build -f Dockerfile-gpu -t sudoku-ml-bench-gpu .

  docker run --gpus all --ipc=host -it sudoku-ml-bench-gpu

  # Add -e TF_CPP_MIN_LOG_LEVEL=3 to catch only the JSON output

  

The 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.