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PythonFZ
/
SimTech_2022_04
connected to https://github.com/PythonFZ/SimTech_2022_04.git

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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   download_kaggle:
    4. 

  4.     cmd: 'python -c "from src.download import download_kaggle; download_kaggle(exec_func=True)" '
    5. 

  5.     params:
    6. 

  6.       params.yaml:
    7. 

  7.         download_kaggle:
    8. 

  8.           dataset: datamunge/sign-language-mnist
    9. 

  9.     outs:
    10. 

  10.     - path: dataset
    11. 

  11.       md5: dce5ff47d2f83a726e773d58bc663eee.dir
    12. 

  12.       size: 210857086
    13. 

  13.       nfiles: 7
    14. 

  14.   DataPreprocessor:
    15. 

  15.     cmd: "python -c \"from src.process import DataPreprocessor; DataPreprocessor.load(name='DataPreprocessor').run_and_save()\"\
    16. 

  16.       \ "
    17. 

  17.     deps:
    18. 

  18.     - path: dataset
    19. 

  19.       md5: dce5ff47d2f83a726e773d58bc663eee.dir
    20. 

  20.       size: 210857086
    21. 

  21.       nfiles: 7
    22. 

  22.     params:
    23. 

  23.       params.yaml:
    24. 

  24.         DataPreprocessor:
    25. 

  25.           dataset: sign_mnist_train
    26. 

  26.     outs:
    27. 

  27.     - path: nodes/DataPreprocessor/outs.json
    28. 

  28.       md5: 91bf7e1e8916a86ada5cccd6cfe0acf1
    29. 

  29.       size: 233258189
    30. 

  30.   data_preprocess_test:
    31. 

  31.     cmd: "python3 -c \"from src.DataPreprocessor import DataPreprocessor; DataPreprocessor.load(name='data_preprocess_test').run_and_save()\"\
    32. 

  32.       \ "
    33. 

  33.     deps:
    34. 

  34.     - path: dataset
    35. 

  35.       md5: dce5ff47d2f83a726e773d58bc663eee.dir
    36. 

  36.       size: 210857086
    37. 

  37.       nfiles: 7
    38. 

  38.     - path: src/DataPreprocessor.py
    39. 

  39.       md5: 2d68eeed3da20f673103b5e45b217607
    40. 

  40.       size: 1610
    41. 

  41.     params:
    42. 

  42.       params.yaml:
    43. 

  43.         data_preprocess_test:
    44. 

  44.           dataset: sign_mnist_test
    45. 

  45.     outs:
    46. 

  46.     - path: nodes/data_preprocess_test/outs.json
    47. 

  47.       md5: 5eb9c135aeb36ebe84979901c29d648f
    48. 

  48.       size: 60933812
    49. 

  49.   MLModel:
    50. 

  50.     cmd: "python -c \"from src.train import MLModel; MLModel.load(name='MLModel').run_and_save()\"\
    51. 

  51.       \ "
    52. 

  52.     deps:
    53. 

  53.     - path: nodes/DataPreprocessor/outs.json
    54. 

  54.       md5: 91bf7e1e8916a86ada5cccd6cfe0acf1
    55. 

  55.       size: 233258180
    56. 

  56.     params:
    57. 

  57.       params.yaml:
    58. 

  58.         MLModel:
    59. 

  59.           dense:
    60. 

  60.           - 4
    61. 

  61.           epochs: 10
    62. 

  62.           filters:
    63. 

  63.           - 4
    64. 

  64.           optimizer: adam
    65. 

  65.     outs:
    66. 

  66.     - path: nodes/MLModel/metrics_no_cache.json
    67. 

  67.       md5: db620041cf0b8cf175a95a2341c5be45
    68. 

  68.       size: 194
    69. 

  69.     - path: nodes/MLModel/model
    70. 

  70.       md5: ae83907bb4ee913483077949371063d7.dir
    71. 

  71.       size: 158676
    72. 

  72.       nfiles: 4
    73. 

  73.     - path: nodes/MLModel/training_history.csv
    74. 

  74.       md5: 862bfa1f3d8e20dd6925e6e15716e59c
    75. 

  75.       size: 844
    76. 

  76.   EvaluateModel:
    77. 

  77.     cmd: "python -c \"from src.evaluate import EvaluateModel; EvaluateModel.load(name='EvaluateModel').run_and_save()\"\
    78. 

  78.       \ "
    79. 

  79.     deps:
    80. 

  80.     - path: nodes/MLModel/metrics_no_cache.json
    81. 

  81.       md5: db620041cf0b8cf175a95a2341c5be45
    82. 

  82.       size: 194
    83. 

  83.     - path: nodes/MLModel/model
    84. 

  84.       md5: ae83907bb4ee913483077949371063d7.dir
    85. 

  85.       size: 158676
    86. 

  86.       nfiles: 4
    87. 

  87.     - path: nodes/MLModel/training_history.csv
    88. 

  88.       md5: 862bfa1f3d8e20dd6925e6e15716e59c
    89. 

  89.       size: 844
    90. 

  90.     - path: nodes/test_data/outs.json
    91. 

  91.       md5: 5eb9c135aeb36ebe84979901c29d648f
    92. 

  92.       size: 60933821
    93. 

  93.     outs:
    94. 

  94.     - path: nodes/EvaluateModel/confusion_matrix.csv
    95. 

  95.       md5: 534650b027951608be75ae9aa99a9dde
    96. 

  96.       size: 79881
    97. 

  97.     - path: nodes/EvaluateModel/metrics_no_cache.json
    98. 

  98.       md5: 79e89c3d13faeb68ec615ae22cb91eab
    99. 

  99.       size: 107
    100. 

  100.   test_data:
    101. 

  101.     cmd: "python -c \"from src.process import DataPreprocessor; DataPreprocessor.load(name='test_data').run_and_save()\"\
    102. 

  102.       \ "
    103. 

  103.     deps:
    104. 

  104.     - path: dataset
    105. 

  105.       md5: dce5ff47d2f83a726e773d58bc663eee.dir
    106. 

  106.       size: 210857086
    107. 

  107.       nfiles: 7
    108. 

  108.     params:
    109. 

  109.       params.yaml:
    110. 

  110.         test_data:
    111. 

  111.           dataset: sign_mnist_test
    112. 

  112.     outs:
    113. 

  113.     - path: nodes/test_data/outs.json
    114. 

  114.       md5: 5eb9c135aeb36ebe84979901c29d648f
    115. 

  115.       size: 60933821
    116.
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