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turacam2014
/
DVC3
mirror of https://github.com/Turaca444/DVC3.git

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dvc.lock 2.1 KB
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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   prepare:
    4. 

  4.     cmd: python src/prepare.py data/data.xml
    5. 

  5.     deps:
    6. 

  6.     - path: data/data.xml
    7. 

  7.       md5: a304afb96060aad90176268345e10355
    8. 

  8.       size: 37891850
    9. 

  9.     - path: src/prepare.py
    10. 

  10.       md5: 51549a1c87b182ebdd785704f56ffaf1
    11. 

  11.       size: 1581
    12. 

  12.     params:
    13. 

  13.       params.yaml:
    14. 

  14.         prepare.seed: 20170428
    15. 

  15.         prepare.split: 0.25
    16. 

  16.     outs:
    17. 

  17.     - path: data/prepared
    18. 

  18.       md5: f1588b397483387838adbface43c3911.dir
    19. 

  19.       size: 23861319
    20. 

  20.       nfiles: 2
    21. 

  21.   featurize:
    22. 

  22.     cmd: python src/featurization.py data/prepared data/features
    23. 

  23.     deps:
    24. 

  24.     - path: data/prepared
    25. 

  25.       md5: f1588b397483387838adbface43c3911.dir
    26. 

  26.       size: 23861319
    27. 

  27.       nfiles: 2
    28. 

  28.     - path: src/featurization.py
    29. 

  29.       md5: 61c592707fd1b33e27819c87cf93f80a
    30. 

  30.       size: 2391
    31. 

  31.     params:
    32. 

  32.       params.yaml:
    33. 

  33.         featurize.max_features: 250
    34. 

  34.         featurize.ngrams: 1
    35. 

  35.     outs:
    36. 

  36.     - path: data/features
    37. 

  37.       md5: 5dc26e5822f7aa06fbf918fc727c8fda.dir
    38. 

  38.       size: 5599725
    39. 

  39.       nfiles: 2
    40. 

  40.   train:
    41. 

  41.     cmd: python src/train.py data/features model.pkl
    42. 

  42.     deps:
    43. 

  43.     - path: data/features
    44. 

  44.       md5: 5dc26e5822f7aa06fbf918fc727c8fda.dir
    45. 

  45.       size: 5599725
    46. 

  46.       nfiles: 2
    47. 

  47.     - path: src/train.py
    48. 

  48.       md5: 9ab95496b29b6ea3418bbf20b9fe3473
    49. 

  49.       size: 964
    50. 

  50.     params:
    51. 

  51.       params.yaml:
    52. 

  52.         train.min_split: 2
    53. 

  53.         train.n_est: 25
    54. 

  54.         train.seed: 20170428
    55. 

  55.     outs:
    56. 

  56.     - path: model.pkl
    57. 

  57.       md5: 160794bad1ba592f9228aadf82e0f7f9
    58. 

  58.       size: 1329222
    59. 

  59.   evaluate:
    60. 

  60.     cmd: python src/evaluate.py model.pkl data/features scores.json prc.json roc.json
    61. 

  61.     deps:
    62. 

  62.     - path: data/features
    63. 

  63.       md5: 5dc26e5822f7aa06fbf918fc727c8fda.dir
    64. 

  64.       size: 5599725
    65. 

  65.       nfiles: 2
    66. 

  66.     - path: model.pkl
    67. 

  67.       md5: 160794bad1ba592f9228aadf82e0f7f9
    68. 

  68.       size: 1329222
    69. 

  69.     - path: src/evaluate.py
    70. 

  70.       md5: fb7b5209c9237ea6cf63550e5fe9b817
    71. 

  71.       size: 1943
    72. 

  72.     outs:
    73. 

  73.     - path: prc.json
    74. 

  74.       md5: 5e29997c6de75339ee1df02515efe591
    75. 

  75.       size: 2261
    76. 

  76.     - path: roc.json
    77. 

  77.       md5: 27201999171df9877a3fa4f3969ad963
    78. 

  78.       size: 2169
    79. 

  79.     - path: scores.json
    80. 

  80.       md5: f2067423acf8648e95c498ecd87673bd
    81. 

  81.       size: 73
    82.
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Integrate Google Cloud Storage
Use Google Storage
Select bucket
Upload key
Finish

Use Google Cloud Storage!

Browsing data directories saved to Google Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Google Storage bucket

Service Account Key

Congratulations!

DVC3 is now integrated with Google Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate AWS S3
Use S3 remote
Select bucket
Access key
Finish

Use AWS S3 as storage!

Browsing data directories saved to S3 is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Access key (If needed)

Congratulations!

DVC3 is now integrated with AWS S3!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate S3 compatible storage
Use S3 like remote
Select bucket
Access key
Finish

Use any S3 compatible storage!

Browsing data directories saved to S3 compatible storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Access key (If needed)

Congratulations!

DVC3 is now integrated with your S3 compatible storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate Azure Cloud Storage
Use Azure Storage
Select bucket
Set key
Finish

Use Azure Cloud Storage!

Browsing data directories saved to Azure Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Azure Storage bucket

Access key (If needed)

Congratulations!

DVC3 is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes