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olga-gorun
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mnist_dagshub

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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   load_mnist:
    4. 

  4.     cmd: PYTHONPATH=../code/ python code/load_mnist_mlp.py
    5. 

  5.     deps:
    6. 

  6.     - path: code/load_mnist_mlp.py
    7. 

  7.       md5: f771d61df1b421d94c059129084976fe
    8. 

  8.       size: 1751
    9. 

  9.     params:
    10. 

  10.       params.yaml:
    11. 

  11.         load_mnist:
    12. 

  12.           test_ratio: 0.2
    13. 

  13.           seed: 42
    14. 

  14.     outs:
    15. 

  15.     - path: data/X_test_plain.npy
    16. 

  16.       md5: 2c738fd1407af62cbb2e797118c94857
    17. 

  17.       size: 62720128
    18. 

  18.     - path: data/X_train_plain.npy
    19. 

  19.       md5: bf2841792eeaf938eb9ea9bef8b53dc5
    20. 

  20.       size: 301056128
    21. 

  21.     - path: data/X_val_plain.npy
    22. 

  22.       md5: 2568856f7af4df832d97296c236b4575
    23. 

  23.       size: 75264128
    24. 

  24.     - path: data/Y_test_plain.npy
    25. 

  25.       md5: 620d51f67460fb75179aa02c24cc19c8
    26. 

  26.       size: 400128
    27. 

  27.     - path: data/Y_train_plain.npy
    28. 

  28.       md5: ce3f10bfcecb587f7032629c7745ab24
    29. 

  29.       size: 1920128
    30. 

  30.     - path: data/Y_val_plain.npy
    31. 

  31.       md5: 3ffd8c7cbf70515f1bcf6c212808795b
    32. 

  32.       size: 480128
    33. 

  33.   train:
    34. 

  34.     cmd: PYTHONPATH=../code/ python code/model_train_mlp.py
    35. 

  35.     deps:
    36. 

  36.     - path: code/common.py
    37. 

  37.       md5: 88618942f56c1c8aa042a061b718e05e
    38. 

  38.       size: 1287
    39. 

  39.     - path: code/model_train_mlp.py
    40. 

  40.       md5: 0b4d704d4e54b86b04ddb1596890574a
    41. 

  41.       size: 2285
    42. 

  42.     - path: data/X_train_plain.npy
    43. 

  43.       md5: bf2841792eeaf938eb9ea9bef8b53dc5
    44. 

  44.       size: 301056128
    45. 

  45.     - path: data/X_val_plain.npy
    46. 

  46.       md5: 2568856f7af4df832d97296c236b4575
    47. 

  47.       size: 75264128
    48. 

  48.     - path: data/Y_train_plain.npy
    49. 

  49.       md5: ce3f10bfcecb587f7032629c7745ab24
    50. 

  50.       size: 1920128
    51. 

  51.     - path: data/Y_val_plain.npy
    52. 

  52.       md5: 3ffd8c7cbf70515f1bcf6c212808795b
    53. 

  53.       size: 480128
    54. 

  54.     params:
    55. 

  55.       params.yaml:
    56. 

  56.         train:
    57. 

  57.           epochs: 11
    58. 

  58.           batch_size: 32
    59. 

  59.           lr: 0.5
    60. 

  60.     outs:
    61. 

  61.     - path: data/model/model.h5
    62. 

  62.       md5: 3b2db5a8628bfd1634230d34ba09d4e6
    63. 

  63.       size: 2290304
    64. 

  64.     - path: data/model/model.json
    65. 

  65.       md5: 6b417b03c605d5115d0b4e68f5c5005e
    66. 

  66.       size: 2526
    67. 

  67.     - path: training_metrics
    68. 

  68.       md5: 0e1f1688964c9b9ad712b77cf2b3355c.dir
    69. 

  69.       size: 1712
    70. 

  70.       nfiles: 4
    71. 

  71.   test:
    72. 

  72.     cmd: PYTHONPATH=../code/ python code/model_test_mlp.py
    73. 

  73.     deps:
    74. 

  74.     - path: code/model_test_mlp.py
    75. 

  75.       md5: defd7a9871e11c038bba68e048d02e0b
    76. 

  76.       size: 1260
    77. 

  77.     - path: data/X_test_plain.npy
    78. 

  78.       md5: 2c738fd1407af62cbb2e797118c94857
    79. 

  79.       size: 62720128
    80. 

  80.     - path: data/Y_test_plain.npy
    81. 

  81.       md5: 620d51f67460fb75179aa02c24cc19c8
    82. 

  82.       size: 400128
    83. 

  83.     - path: data/model/model.h5
    84. 

  84.       md5: 3b2db5a8628bfd1634230d34ba09d4e6
    85. 

  85.       size: 2290304
    86. 

  86.     - path: data/model/model.json
    87. 

  87.       md5: 6b417b03c605d5115d0b4e68f5c5005e
    88. 

  88.       size: 2526
    89. 

  89.     outs:
    90. 

  90.     - path: metrics.yaml
    91. 

  91.       md5: 3b55cd153a3bb1fa981dce6d61f3894e
    92. 

  92.       size: 65
    93.
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Integrate Google Cloud Storage
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Integrate Azure Cloud Storage
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Specify your Azure Storage bucket

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Congratulations!

mnist_dagshub is now integrated with Azure Cloud Storage!

Delete Storage Key

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