5621 lines
232 KiB
Plaintext
5621 lines
232 KiB
Plaintext
{
|
||
"nbformat": 4,
|
||
"nbformat_minor": 0,
|
||
"metadata": {
|
||
"colab": {
|
||
"provenance": []
|
||
},
|
||
"kernelspec": {
|
||
"name": "python3",
|
||
"display_name": "Python 3"
|
||
},
|
||
"language_info": {
|
||
"name": "python"
|
||
},
|
||
"accelerator": "GPU",
|
||
"gpuClass": "standard",
|
||
"widgets": {
|
||
"application/vnd.jupyter.widget-state+json": {
|
||
"fbc74a6e57c94d66bfb493c150bbbf47": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_3de5f4aaad314b04a6d326ed75473deb",
|
||
"IPY_MODEL_48669319a40449a6ac8bfc850e3888a0",
|
||
"IPY_MODEL_a1f2f849dec54b8298749baf353fa084"
|
||
],
|
||
"layout": "IPY_MODEL_b114219520ba4477b8c14e0ab6f77d4b"
|
||
}
|
||
},
|
||
"3de5f4aaad314b04a6d326ed75473deb": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_08ae246277b64dfda696edc1ba2c0b81",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_6ead2c9114054c449c074d21b4f50431",
|
||
"value": "Downloading builder script: 100%"
|
||
}
|
||
},
|
||
"48669319a40449a6ac8bfc850e3888a0": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_db84fa270ba64af7b0e4f49e9fd84b41",
|
||
"max": 3968,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_4b3e7ced2e024d8c8afd1a1cd070034a",
|
||
"value": 3968
|
||
}
|
||
},
|
||
"a1f2f849dec54b8298749baf353fa084": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_1550a85ee3874857b2b77febfb9e2525",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_f12e174f9c5a4057a295c2b0f4c894ba",
|
||
"value": " 3.97k/3.97k [00:00<00:00, 139kB/s]"
|
||
}
|
||
},
|
||
"b114219520ba4477b8c14e0ab6f77d4b": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"08ae246277b64dfda696edc1ba2c0b81": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"6ead2c9114054c449c074d21b4f50431": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"db84fa270ba64af7b0e4f49e9fd84b41": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"4b3e7ced2e024d8c8afd1a1cd070034a": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"1550a85ee3874857b2b77febfb9e2525": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"f12e174f9c5a4057a295c2b0f4c894ba": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"0d14dee025724d3097b80fe729ae3532": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_7589959458ae451bb0fc46d7e4193bcf",
|
||
"IPY_MODEL_015cae145720498cba1c65a4ac877052",
|
||
"IPY_MODEL_9e8fc689767b45b79771c6a5efca10b3"
|
||
],
|
||
"layout": "IPY_MODEL_4cf50a0ecdaf4191a36e8dddfeaa8b36"
|
||
}
|
||
},
|
||
"7589959458ae451bb0fc46d7e4193bcf": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_30db2acbf995414fb3e47c9d12ee8697",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_b3aebbd1bcf241c68ef4d01f244e38c0",
|
||
"value": "Downloading metadata: 100%"
|
||
}
|
||
},
|
||
"015cae145720498cba1c65a4ac877052": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_8b2c386292954944bf004dab5a6ef8d8",
|
||
"max": 3280,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_1dd09c89af8448ed9673238c4a3ebb8e",
|
||
"value": 3280
|
||
}
|
||
},
|
||
"9e8fc689767b45b79771c6a5efca10b3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_fc2503b36be542e5a3512b8196c30e2b",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_8eb569059fa74218a9f47c78e3db8436",
|
||
"value": " 3.28k/3.28k [00:00<00:00, 119kB/s]"
|
||
}
|
||
},
|
||
"4cf50a0ecdaf4191a36e8dddfeaa8b36": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"30db2acbf995414fb3e47c9d12ee8697": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"b3aebbd1bcf241c68ef4d01f244e38c0": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"8b2c386292954944bf004dab5a6ef8d8": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"1dd09c89af8448ed9673238c4a3ebb8e": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"fc2503b36be542e5a3512b8196c30e2b": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8eb569059fa74218a9f47c78e3db8436": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"24abb274aee648eaa308802754b96b7a": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_aab5cad3e7d94ae981eac90756bf8d41",
|
||
"IPY_MODEL_fc353140430841929ff5a94e09a4143e",
|
||
"IPY_MODEL_f23d67fd143844a393b1a08ee3d48969"
|
||
],
|
||
"layout": "IPY_MODEL_f7be3e08cb514922b0f67913216005dc"
|
||
}
|
||
},
|
||
"aab5cad3e7d94ae981eac90756bf8d41": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_32a2ce7715a941b0bec06e5676252446",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_c9faf32b655f4fa992d641768a558220",
|
||
"value": "Downloading readme: 100%"
|
||
}
|
||
},
|
||
"fc353140430841929ff5a94e09a4143e": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_17b604cbc8da43898eca3f1527e3b125",
|
||
"max": 8777,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_d30de94f30ce4da1a516c087074aee96",
|
||
"value": 8777
|
||
}
|
||
},
|
||
"f23d67fd143844a393b1a08ee3d48969": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_adcced2b10f046d0bb31d20e4ec46708",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_bb8ce706f3644b13a5a6982b052fec84",
|
||
"value": " 8.78k/8.78k [00:00<00:00, 288kB/s]"
|
||
}
|
||
},
|
||
"f7be3e08cb514922b0f67913216005dc": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"32a2ce7715a941b0bec06e5676252446": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"c9faf32b655f4fa992d641768a558220": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"17b604cbc8da43898eca3f1527e3b125": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d30de94f30ce4da1a516c087074aee96": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"adcced2b10f046d0bb31d20e4ec46708": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"bb8ce706f3644b13a5a6982b052fec84": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"2a8fa16116094071970fac4c8de210e7": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_2b766b35ab0944bca286e1a7dea163a4",
|
||
"IPY_MODEL_f1395abbe0c14c2b925caef7b3630a94",
|
||
"IPY_MODEL_866570d7610f4843b3ff943809239197"
|
||
],
|
||
"layout": "IPY_MODEL_b5d63d011ffb484d969b3a1db52837a0"
|
||
}
|
||
},
|
||
"2b766b35ab0944bca286e1a7dea163a4": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_d0e5d5dedb7f48c4b8467f75a374b1ee",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_133b2906561441ceb62aaf52ef73e237",
|
||
"value": "Downloading data files: 100%"
|
||
}
|
||
},
|
||
"f1395abbe0c14c2b925caef7b3630a94": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_c1f9e1738aad45a3918eb0ee7fe7e1b9",
|
||
"max": 3,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_b0897d82b3d1409880d4739ebc924ec1",
|
||
"value": 3
|
||
}
|
||
},
|
||
"866570d7610f4843b3ff943809239197": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_fd502663b2bf4538845cc4ba89605dce",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_8d3c98af85474a68b5a11836909446f2",
|
||
"value": " 3/3 [00:00<00:00, 5.87it/s]"
|
||
}
|
||
},
|
||
"b5d63d011ffb484d969b3a1db52837a0": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d0e5d5dedb7f48c4b8467f75a374b1ee": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"133b2906561441ceb62aaf52ef73e237": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"c1f9e1738aad45a3918eb0ee7fe7e1b9": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"b0897d82b3d1409880d4739ebc924ec1": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"fd502663b2bf4538845cc4ba89605dce": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"8d3c98af85474a68b5a11836909446f2": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"e58e692e115b44469ec23491d22001f9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_70662fe04f374bc1a4f977526bc7b91e",
|
||
"IPY_MODEL_f77bc5ec0a1a43028497d888b399e8ef",
|
||
"IPY_MODEL_5db3f48937274eb9bc8823956bde1f0b"
|
||
],
|
||
"layout": "IPY_MODEL_829fcb51001c4c92b9dfc7d037125075"
|
||
}
|
||
},
|
||
"70662fe04f374bc1a4f977526bc7b91e": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_fddfc33676b64b9d90429a5339bbeedb",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_c569f575d48e49c68e02c148bede9f70",
|
||
"value": "Downloading data: 100%"
|
||
}
|
||
},
|
||
"f77bc5ec0a1a43028497d888b399e8ef": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_9fb790cca3334d3b8e8b9c7c02a35cf6",
|
||
"max": 591930,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_7edfe8f0b73641a1bfa576aae0703728",
|
||
"value": 591930
|
||
}
|
||
},
|
||
"5db3f48937274eb9bc8823956bde1f0b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_86cfd09655f14aba8efcb98b5933865a",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_55969ecc0f2e4a599a5da24b97d856b2",
|
||
"value": " 592k/592k [00:00<00:00, 12.5MB/s]"
|
||
}
|
||
},
|
||
"829fcb51001c4c92b9dfc7d037125075": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"fddfc33676b64b9d90429a5339bbeedb": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"c569f575d48e49c68e02c148bede9f70": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"9fb790cca3334d3b8e8b9c7c02a35cf6": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"7edfe8f0b73641a1bfa576aae0703728": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"86cfd09655f14aba8efcb98b5933865a": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"55969ecc0f2e4a599a5da24b97d856b2": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"35b7eb5a427046358c978089ecb9d550": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_a0032c1faac44445bec67c334390980e",
|
||
"IPY_MODEL_ec01cb7f32f5448ca866647e3ebedbfb",
|
||
"IPY_MODEL_f1ee9050cee845f88e9baf513535785b"
|
||
],
|
||
"layout": "IPY_MODEL_5f4b7a51deb94d4dbae86148225c19b5"
|
||
}
|
||
},
|
||
"a0032c1faac44445bec67c334390980e": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_81081eff27b242e8b96f8b17348f5fb2",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_a970d1c066994b95835ff14d47d201cc",
|
||
"value": "Downloading data: 100%"
|
||
}
|
||
},
|
||
"ec01cb7f32f5448ca866647e3ebedbfb": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_5659feb2b0924d9f9e9324cd4c05777d",
|
||
"max": 74018,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_eb21821900034762885653d6b54f5461",
|
||
"value": 74018
|
||
}
|
||
},
|
||
"f1ee9050cee845f88e9baf513535785b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_7455c4b1c5ac4977b678845a5ba2ea78",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_5f6799d3ddbc4c369e1aae2b95b3904c",
|
||
"value": " 74.0k/74.0k [00:00<00:00, 1.97MB/s]"
|
||
}
|
||
},
|
||
"5f4b7a51deb94d4dbae86148225c19b5": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"81081eff27b242e8b96f8b17348f5fb2": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"a970d1c066994b95835ff14d47d201cc": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"5659feb2b0924d9f9e9324cd4c05777d": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"eb21821900034762885653d6b54f5461": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"7455c4b1c5ac4977b678845a5ba2ea78": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"5f6799d3ddbc4c369e1aae2b95b3904c": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"11286368590748a295186146162297ce": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_8aab56f7ede942eda07d132777e5c1a6",
|
||
"IPY_MODEL_74e2c6e41731406ba201594f9e3de0be",
|
||
"IPY_MODEL_d48c6048e8af487aaf92327e8ed4fb7f"
|
||
],
|
||
"layout": "IPY_MODEL_17cb59373eef4e27b6fd58a29303ecc6"
|
||
}
|
||
},
|
||
"8aab56f7ede942eda07d132777e5c1a6": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_fef878d871614253836af7f166e40010",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_6f2162b33b2b4af4af632a9b1f20e291",
|
||
"value": "Downloading data: 100%"
|
||
}
|
||
},
|
||
"74e2c6e41731406ba201594f9e3de0be": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_fc729efb3eed4f80900f2d110e1e6d4e",
|
||
"max": 74935,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_23038bfafd9b4be9ae46bbfabbc5b624",
|
||
"value": 74935
|
||
}
|
||
},
|
||
"d48c6048e8af487aaf92327e8ed4fb7f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_59d9f15287c1497b82bf7ee540118ac6",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_d58b6979f60e42c2a5a79b789e790a03",
|
||
"value": " 74.9k/74.9k [00:00<00:00, 3.13MB/s]"
|
||
}
|
||
},
|
||
"17cb59373eef4e27b6fd58a29303ecc6": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"fef878d871614253836af7f166e40010": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"6f2162b33b2b4af4af632a9b1f20e291": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"fc729efb3eed4f80900f2d110e1e6d4e": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"23038bfafd9b4be9ae46bbfabbc5b624": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"59d9f15287c1497b82bf7ee540118ac6": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d58b6979f60e42c2a5a79b789e790a03": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"e7b1d27f3aa64d4f8d09127e36037731": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_374c74aa844f4b13b089bb70d377d698",
|
||
"IPY_MODEL_82caada33e2640d69f520b524a4456f6",
|
||
"IPY_MODEL_5efeb3a9060d4448b874a8872f3f165c"
|
||
],
|
||
"layout": "IPY_MODEL_6ae20e8136884830825b5c49c37f867a"
|
||
}
|
||
},
|
||
"374c74aa844f4b13b089bb70d377d698": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_700d432dafd3460288bc63ac9d20a598",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_803645353525428ea3ca1cd17197350b",
|
||
"value": "Extracting data files: 100%"
|
||
}
|
||
},
|
||
"82caada33e2640d69f520b524a4456f6": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_d6041f8ba8b346838088d2582dbbb95c",
|
||
"max": 3,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_df3f52353df04a088de30577074117f9",
|
||
"value": 3
|
||
}
|
||
},
|
||
"5efeb3a9060d4448b874a8872f3f165c": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_0ef75435cae04344a2eb8a52565e74c8",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_201049abbcfa4c03a3ce4a66042c6f09",
|
||
"value": " 3/3 [00:00<00:00, 60.43it/s]"
|
||
}
|
||
},
|
||
"6ae20e8136884830825b5c49c37f867a": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"700d432dafd3460288bc63ac9d20a598": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"803645353525428ea3ca1cd17197350b": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"d6041f8ba8b346838088d2582dbbb95c": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"df3f52353df04a088de30577074117f9": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"0ef75435cae04344a2eb8a52565e74c8": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"201049abbcfa4c03a3ce4a66042c6f09": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"9422ac8de56949968f6dd0aac6c82e90": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_a4477dd1876f4a9d99408ea568ebdf0c",
|
||
"IPY_MODEL_62132fd350844e9487633e66692c0c51",
|
||
"IPY_MODEL_4b3af99603cd4614a32a7dd0f0cf69a7"
|
||
],
|
||
"layout": "IPY_MODEL_d20552706e624d81be477cf53c70de48"
|
||
}
|
||
},
|
||
"a4477dd1876f4a9d99408ea568ebdf0c": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_1ace1068c2a74419822f05b01382b66c",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_92862060d6b3404395b9d26b762673e0",
|
||
"value": "Generating train split: 100%"
|
||
}
|
||
},
|
||
"62132fd350844e9487633e66692c0c51": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_2d7de6a858c54f2792e4d38e1b2a57fc",
|
||
"max": 16000,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_f4fac1abd5d54adf8e25bca6791daf7f",
|
||
"value": 16000
|
||
}
|
||
},
|
||
"4b3af99603cd4614a32a7dd0f0cf69a7": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_6198eafef9d8467d9a63a5329cd6feac",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_00164598fdbe4062910ad66f0201d9c3",
|
||
"value": " 16000/16000 [00:18<00:00, 27337.21 examples/s]"
|
||
}
|
||
},
|
||
"d20552706e624d81be477cf53c70de48": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"1ace1068c2a74419822f05b01382b66c": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"92862060d6b3404395b9d26b762673e0": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"2d7de6a858c54f2792e4d38e1b2a57fc": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"f4fac1abd5d54adf8e25bca6791daf7f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"6198eafef9d8467d9a63a5329cd6feac": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"00164598fdbe4062910ad66f0201d9c3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"766d69ba63734c8e9dea95623c060c18": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_20fbbcc1d6c7459fafd988d41438eb80",
|
||
"IPY_MODEL_e503fe4702d440d58db6c8ebcef5ca8d",
|
||
"IPY_MODEL_1bd87756be65458da1130d62b4d61c5a"
|
||
],
|
||
"layout": "IPY_MODEL_9776edf5da834fa887b501e385c8977a"
|
||
}
|
||
},
|
||
"20fbbcc1d6c7459fafd988d41438eb80": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_1b73671e115f4d5f93e0cf3ace65edf0",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_b36db9ac6eba433a985087fb6ac7f88f",
|
||
"value": "Generating validation split: 0%"
|
||
}
|
||
},
|
||
"e503fe4702d440d58db6c8ebcef5ca8d": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_f2f98c2d73f24d7f973a578f90255a76",
|
||
"max": 2000,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_49277a7a3089460fa77ce74f54f263a3",
|
||
"value": 2000
|
||
}
|
||
},
|
||
"1bd87756be65458da1130d62b4d61c5a": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_0f0d8cccdf3f4ec68caad47d432c2e6b",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_e849e2fbaa054d4394bd0d081fa919c5",
|
||
"value": " 0/2000 [00:00<?, ? examples/s]"
|
||
}
|
||
},
|
||
"9776edf5da834fa887b501e385c8977a": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": "hidden",
|
||
"width": null
|
||
}
|
||
},
|
||
"1b73671e115f4d5f93e0cf3ace65edf0": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"b36db9ac6eba433a985087fb6ac7f88f": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"f2f98c2d73f24d7f973a578f90255a76": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"49277a7a3089460fa77ce74f54f263a3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"0f0d8cccdf3f4ec68caad47d432c2e6b": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"e849e2fbaa054d4394bd0d081fa919c5": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"fdf218b36eda42aa9ed2dd633d240f9d": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_d7f5fafaa9b8473996724860957e053c",
|
||
"IPY_MODEL_d91686aad27f4c39b9dc2952bb175074",
|
||
"IPY_MODEL_4cb2ab536a6a48869357dcdb85aa07e3"
|
||
],
|
||
"layout": "IPY_MODEL_7d5196e467db44409a244cf73bc61fdc"
|
||
}
|
||
},
|
||
"d7f5fafaa9b8473996724860957e053c": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_9c4cc76511744dd0b2502135aa9b26ad",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_2d5274420c074ca1bcbcc1c1414421be",
|
||
"value": "Generating test split: 0%"
|
||
}
|
||
},
|
||
"d91686aad27f4c39b9dc2952bb175074": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_653f135e75d64a4886fc8aaf9efe2e8e",
|
||
"max": 2000,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_5f48da1818b54f148e9c6e9b61dda7f4",
|
||
"value": 0
|
||
}
|
||
},
|
||
"4cb2ab536a6a48869357dcdb85aa07e3": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_a3a139b1683745958cfd65f4d5855071",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_072dbd1ad830460fb1609deb6a4a3daf",
|
||
"value": " 0/2000 [00:00<?, ? examples/s]"
|
||
}
|
||
},
|
||
"7d5196e467db44409a244cf73bc61fdc": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"9c4cc76511744dd0b2502135aa9b26ad": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"2d5274420c074ca1bcbcc1c1414421be": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"653f135e75d64a4886fc8aaf9efe2e8e": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"5f48da1818b54f148e9c6e9b61dda7f4": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"a3a139b1683745958cfd65f4d5855071": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"072dbd1ad830460fb1609deb6a4a3daf": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"f78c464090be4742be047cadf84cd5d7": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HBoxModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HBoxModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HBoxView",
|
||
"box_style": "",
|
||
"children": [
|
||
"IPY_MODEL_bae635ed7cd54c64aeb618619a5b4207",
|
||
"IPY_MODEL_bf0c6a864ed946738528c16e1ce7ca3e",
|
||
"IPY_MODEL_0effabe282f7485f9a41ec518499b376"
|
||
],
|
||
"layout": "IPY_MODEL_cab3e18cde1e40898df29f80af4c049f"
|
||
}
|
||
},
|
||
"bae635ed7cd54c64aeb618619a5b4207": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_3371bf2f419447c6977db12f3bc8a0ac",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_55fcdf435e754088b572ac4cf61ae2e0",
|
||
"value": "100%"
|
||
}
|
||
},
|
||
"bf0c6a864ed946738528c16e1ce7ca3e": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "FloatProgressModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "FloatProgressModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "ProgressView",
|
||
"bar_style": "success",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_bd74fe36a9c54c5dac5bcda51afee7cf",
|
||
"max": 3,
|
||
"min": 0,
|
||
"orientation": "horizontal",
|
||
"style": "IPY_MODEL_d723a2df495a442dabebd2e59797435a",
|
||
"value": 3
|
||
}
|
||
},
|
||
"0effabe282f7485f9a41ec518499b376": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "HTMLModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_dom_classes": [],
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "HTMLModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/controls",
|
||
"_view_module_version": "1.5.0",
|
||
"_view_name": "HTMLView",
|
||
"description": "",
|
||
"description_tooltip": null,
|
||
"layout": "IPY_MODEL_bac0681cfc8143daa8276eeea99e13ab",
|
||
"placeholder": "",
|
||
"style": "IPY_MODEL_fe5c4bc05b2548e2bd5efac843351c69",
|
||
"value": " 3/3 [00:00<00:00, 133.11it/s]"
|
||
}
|
||
},
|
||
"cab3e18cde1e40898df29f80af4c049f": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"3371bf2f419447c6977db12f3bc8a0ac": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"55fcdf435e754088b572ac4cf61ae2e0": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"bd74fe36a9c54c5dac5bcda51afee7cf": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"d723a2df495a442dabebd2e59797435a": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "ProgressStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "ProgressStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"bar_color": null,
|
||
"description_width": ""
|
||
}
|
||
},
|
||
"bac0681cfc8143daa8276eeea99e13ab": {
|
||
"model_module": "@jupyter-widgets/base",
|
||
"model_name": "LayoutModel",
|
||
"model_module_version": "1.2.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/base",
|
||
"_model_module_version": "1.2.0",
|
||
"_model_name": "LayoutModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "LayoutView",
|
||
"align_content": null,
|
||
"align_items": null,
|
||
"align_self": null,
|
||
"border": null,
|
||
"bottom": null,
|
||
"display": null,
|
||
"flex": null,
|
||
"flex_flow": null,
|
||
"grid_area": null,
|
||
"grid_auto_columns": null,
|
||
"grid_auto_flow": null,
|
||
"grid_auto_rows": null,
|
||
"grid_column": null,
|
||
"grid_gap": null,
|
||
"grid_row": null,
|
||
"grid_template_areas": null,
|
||
"grid_template_columns": null,
|
||
"grid_template_rows": null,
|
||
"height": null,
|
||
"justify_content": null,
|
||
"justify_items": null,
|
||
"left": null,
|
||
"margin": null,
|
||
"max_height": null,
|
||
"max_width": null,
|
||
"min_height": null,
|
||
"min_width": null,
|
||
"object_fit": null,
|
||
"object_position": null,
|
||
"order": null,
|
||
"overflow": null,
|
||
"overflow_x": null,
|
||
"overflow_y": null,
|
||
"padding": null,
|
||
"right": null,
|
||
"top": null,
|
||
"visibility": null,
|
||
"width": null
|
||
}
|
||
},
|
||
"fe5c4bc05b2548e2bd5efac843351c69": {
|
||
"model_module": "@jupyter-widgets/controls",
|
||
"model_name": "DescriptionStyleModel",
|
||
"model_module_version": "1.5.0",
|
||
"state": {
|
||
"_model_module": "@jupyter-widgets/controls",
|
||
"_model_module_version": "1.5.0",
|
||
"_model_name": "DescriptionStyleModel",
|
||
"_view_count": null,
|
||
"_view_module": "@jupyter-widgets/base",
|
||
"_view_module_version": "1.2.0",
|
||
"_view_name": "StyleView",
|
||
"description_width": ""
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"cells": [
|
||
{
|
||
"cell_type": "code",
|
||
"source": [],
|
||
"metadata": {
|
||
"id": "JErLYXsaYy8-"
|
||
},
|
||
"execution_count": null,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"! pip install datasets transformers torch scikit-learn evaluate"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "u29i-U30zRjY",
|
||
"outputId": "2ecd3ab8-fcf8-436f-90bc-73b804194095"
|
||
},
|
||
"execution_count": 1,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
|
||
"Collecting datasets\n",
|
||
" Downloading datasets-2.9.0-py3-none-any.whl (462 kB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m462.8/462.8 KB\u001b[0m \u001b[31m19.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hCollecting transformers\n",
|
||
" Downloading transformers-4.26.1-py3-none-any.whl (6.3 MB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m33.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hRequirement already satisfied: torch in /usr/local/lib/python3.8/dist-packages (1.13.1+cu116)\n",
|
||
"Requirement already satisfied: scikit-learn in /usr/local/lib/python3.8/dist-packages (1.0.2)\n",
|
||
"Collecting evaluate\n",
|
||
" Downloading evaluate-0.4.0-py3-none-any.whl (81 kB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m81.4/81.4 KB\u001b[0m \u001b[31m6.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hRequirement already satisfied: pyarrow>=6.0.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (9.0.0)\n",
|
||
"Collecting responses<0.19\n",
|
||
" Downloading responses-0.18.0-py3-none-any.whl (38 kB)\n",
|
||
"Collecting multiprocess\n",
|
||
" Downloading multiprocess-0.70.14-py38-none-any.whl (132 kB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m132.0/132.0 KB\u001b[0m \u001b[31m12.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hRequirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (2.25.1)\n",
|
||
"Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (2023.1.0)\n",
|
||
"Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (4.64.1)\n",
|
||
"Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from datasets) (23.0)\n",
|
||
"Requirement already satisfied: aiohttp in /usr/local/lib/python3.8/dist-packages (from datasets) (3.8.3)\n",
|
||
"Requirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (from datasets) (1.3.5)\n",
|
||
"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (6.0)\n",
|
||
"Requirement already satisfied: dill<0.3.7 in /usr/local/lib/python3.8/dist-packages (from datasets) (0.3.6)\n",
|
||
"Collecting xxhash\n",
|
||
" Downloading xxhash-3.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (213 kB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m213.0/213.0 KB\u001b[0m \u001b[31m10.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from datasets) (1.21.6)\n",
|
||
"Collecting huggingface-hub<1.0.0,>=0.2.0\n",
|
||
" Downloading huggingface_hub-0.12.0-py3-none-any.whl (190 kB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.3/190.3 KB\u001b[0m \u001b[31m10.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hCollecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
|
||
" Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m25.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers) (3.9.0)\n",
|
||
"Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n",
|
||
"Requirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch) (4.4.0)\n",
|
||
"Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.2.0)\n",
|
||
"Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.7.3)\n",
|
||
"Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (3.1.0)\n",
|
||
"Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (22.2.0)\n",
|
||
"Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (2.1.1)\n",
|
||
"Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (6.0.4)\n",
|
||
"Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.8.2)\n",
|
||
"Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.3)\n",
|
||
"Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.1)\n",
|
||
"Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (4.0.2)\n",
|
||
"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (2.10)\n",
|
||
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (1.24.3)\n",
|
||
"Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (4.0.0)\n",
|
||
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (2022.12.7)\n",
|
||
"Collecting urllib3<1.27,>=1.21.1\n",
|
||
" Downloading urllib3-1.26.14-py2.py3-none-any.whl (140 kB)\n",
|
||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m140.6/140.6 KB\u001b[0m \u001b[31m11.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||
"\u001b[?25hRequirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2022.7.1)\n",
|
||
"Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2.8.2)\n",
|
||
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n",
|
||
"Installing collected packages: tokenizers, xxhash, urllib3, multiprocess, responses, huggingface-hub, transformers, datasets, evaluate\n",
|
||
" Attempting uninstall: urllib3\n",
|
||
" Found existing installation: urllib3 1.24.3\n",
|
||
" Uninstalling urllib3-1.24.3:\n",
|
||
" Successfully uninstalled urllib3-1.24.3\n",
|
||
"Successfully installed datasets-2.9.0 evaluate-0.4.0 huggingface-hub-0.12.0 multiprocess-0.70.14 responses-0.18.0 tokenizers-0.13.2 transformers-4.26.1 urllib3-1.26.14 xxhash-3.2.0\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [],
|
||
"metadata": {
|
||
"id": "a_f-yno_zity"
|
||
}
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"!wget 'https://git.wmi.amu.edu.pl/s444465/projekt-glebokie/raw/branch/master/run_glue.py' -O 'run_glue.py'\n",
|
||
"!wget 'https://git.wmi.amu.edu.pl/s444465/projekt-glebokie/raw/branch/master/roberta.py' -O 'roberta.py'\n",
|
||
"!wget 'https://git.wmi.amu.edu.pl/s444465/projekt-glebokie/raw/branch/master/gpt2.py' -O 'gpt2.py'"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "V_HmRNcmzhsw",
|
||
"outputId": "4e1f2362-305f-4af3-f125-32ccadb484a2"
|
||
},
|
||
"execution_count": 2,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"--2023-02-12 18:47:51-- https://git.wmi.amu.edu.pl/s444465/projekt-glebokie/raw/branch/master/run_glue.py\n",
|
||
"Resolving git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)... 150.254.78.40\n",
|
||
"Connecting to git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)|150.254.78.40|:443... connected.\n",
|
||
"HTTP request sent, awaiting response... 200 OK\n",
|
||
"Length: 30650 (30K) [text/plain]\n",
|
||
"Saving to: ‘run_glue.py’\n",
|
||
"\n",
|
||
"run_glue.py 100%[===================>] 29.93K --.-KB/s in 0.1s \n",
|
||
"\n",
|
||
"2023-02-12 18:47:52 (271 KB/s) - ‘run_glue.py’ saved [30650/30650]\n",
|
||
"\n",
|
||
"--2023-02-12 18:47:53-- https://git.wmi.amu.edu.pl/s444465/projekt-glebokie/raw/branch/master/roberta.py\n",
|
||
"Resolving git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)... 150.254.78.40\n",
|
||
"Connecting to git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)|150.254.78.40|:443... connected.\n",
|
||
"HTTP request sent, awaiting response... 200 OK\n",
|
||
"Length: 18577 (18K) [text/plain]\n",
|
||
"Saving to: ‘roberta.py’\n",
|
||
"\n",
|
||
"roberta.py 100%[===================>] 18.14K --.-KB/s in 0.1s \n",
|
||
"\n",
|
||
"2023-02-12 18:47:53 (164 KB/s) - ‘roberta.py’ saved [18577/18577]\n",
|
||
"\n",
|
||
"--2023-02-12 18:47:53-- https://git.wmi.amu.edu.pl/s444465/projekt-glebokie/raw/branch/master/gpt2.py\n",
|
||
"Resolving git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)... 150.254.78.40\n",
|
||
"Connecting to git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)|150.254.78.40|:443... connected.\n",
|
||
"HTTP request sent, awaiting response... 200 OK\n",
|
||
"Length: 7976 (7.8K) [text/plain]\n",
|
||
"Saving to: ‘gpt2.py’\n",
|
||
"\n",
|
||
"gpt2.py 100%[===================>] 7.79K --.-KB/s in 0s \n",
|
||
"\n",
|
||
"2023-02-12 18:47:54 (1.59 GB/s) - ‘gpt2.py’ saved [7976/7976]\n",
|
||
"\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"import json\n",
|
||
"from pathlib import Path\n",
|
||
"from typing import Dict, List\n",
|
||
"from datasets import load_dataset\n",
|
||
"\n",
|
||
"loaded_data = load_dataset('emotion')\n",
|
||
"\n",
|
||
"!mkdir -v -p data\n",
|
||
"\n",
|
||
"train_path = Path('data/train.json')\n",
|
||
"valid_path = Path('data/valid.json')\n",
|
||
"test_path = Path('data/test.json')\n",
|
||
"data_train, data_valid, data_test = [], [], []\n",
|
||
"\n",
|
||
"for source_data, dataset, max_size in [\n",
|
||
" (loaded_data['train'], data_train, None),\n",
|
||
" (loaded_data['test'], data_valid, None),\n",
|
||
"]:\n",
|
||
" for i, data in enumerate(source_data):\n",
|
||
" if max_size is not None and i >= max_size:\n",
|
||
" break\n",
|
||
" data_line = {\n",
|
||
" 'label': int(data['label']),\n",
|
||
" 'text': data['text'],\n",
|
||
" }\n",
|
||
" dataset.append(data_line)\n",
|
||
"\n",
|
||
"print(f'Train: {len(data_train):6d}')\n",
|
||
"print(f'Valid: {len(data_valid):6d}')\n",
|
||
"\n",
|
||
"data_class_1, data_class_2 = [], []\n",
|
||
"\n",
|
||
"for data in data_valid:\n",
|
||
" label = data['label']\n",
|
||
" if label == 0:\n",
|
||
" data_class_1.append(data)\n",
|
||
" elif label == 1:\n",
|
||
" data_class_2.append(data)\n",
|
||
"\n",
|
||
"print(f'Label 1: {len(data_class_1):6d}')\n",
|
||
"print(f'Label 2: {len(data_class_2):6d}')\n",
|
||
"\n",
|
||
"size_half_class_1 = int(len(data_class_1) / 2)\n",
|
||
"size_half_class_2 = int(len(data_class_2) / 2)\n",
|
||
"\n",
|
||
"data_valid = data_class_1[:size_half_class_1] + data_class_2[:size_half_class_2]\n",
|
||
"data_test = data_class_1[size_half_class_1:] + data_class_2[size_half_class_2:]\n",
|
||
"\n",
|
||
"print(f'Valid: {len(data_valid):6d}')\n",
|
||
"print(f'Test : {len(data_test):6d}')\n",
|
||
"\n",
|
||
"MAP_LABEL_TRANSLATION = {\n",
|
||
" 0: 'sadness',\n",
|
||
" 1: 'joy',\n",
|
||
" 2: 'love',\n",
|
||
" 3: 'anger',\n",
|
||
" 4: 'fear',\n",
|
||
" 5: 'surprise',\n",
|
||
"}\n",
|
||
"\n",
|
||
"def save_as_translations(original_save_path: Path, data_to_save: List[Dict]) -> None:\n",
|
||
" file_name = 's2s-' + original_save_path.name\n",
|
||
" file_path = original_save_path.parent / file_name\n",
|
||
"\n",
|
||
" print(f'Saving into: {file_path}')\n",
|
||
" with open(file_path, 'wt') as f_write:\n",
|
||
" for data_line in data_to_save:\n",
|
||
" label = data_line['label']\n",
|
||
" new_label = MAP_LABEL_TRANSLATION[label]\n",
|
||
" data_line['label'] = new_label\n",
|
||
" data_line_str = json.dumps(data_line)\n",
|
||
" f_write.write(f'{data_line_str}\\n')\n",
|
||
"\n",
|
||
"for file_path, data_to_save in [(train_path, data_train), (valid_path, data_valid), (test_path, data_test)]:\n",
|
||
" print(f'Saving into: {file_path}')\n",
|
||
" with open(file_path, 'wt') as f_write:\n",
|
||
" for data_line in data_to_save:\n",
|
||
" data_line_str = json.dumps(data_line)\n",
|
||
" f_write.write(f'{data_line_str}\\n')\n",
|
||
" \n",
|
||
" save_as_translations(file_path, data_to_save)\n",
|
||
"\n"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 667,
|
||
"referenced_widgets": [
|
||
"fbc74a6e57c94d66bfb493c150bbbf47",
|
||
"3de5f4aaad314b04a6d326ed75473deb",
|
||
"48669319a40449a6ac8bfc850e3888a0",
|
||
"a1f2f849dec54b8298749baf353fa084",
|
||
"b114219520ba4477b8c14e0ab6f77d4b",
|
||
"08ae246277b64dfda696edc1ba2c0b81",
|
||
"6ead2c9114054c449c074d21b4f50431",
|
||
"db84fa270ba64af7b0e4f49e9fd84b41",
|
||
"4b3e7ced2e024d8c8afd1a1cd070034a",
|
||
"1550a85ee3874857b2b77febfb9e2525",
|
||
"f12e174f9c5a4057a295c2b0f4c894ba",
|
||
"0d14dee025724d3097b80fe729ae3532",
|
||
"7589959458ae451bb0fc46d7e4193bcf",
|
||
"015cae145720498cba1c65a4ac877052",
|
||
"9e8fc689767b45b79771c6a5efca10b3",
|
||
"4cf50a0ecdaf4191a36e8dddfeaa8b36",
|
||
"30db2acbf995414fb3e47c9d12ee8697",
|
||
"b3aebbd1bcf241c68ef4d01f244e38c0",
|
||
"8b2c386292954944bf004dab5a6ef8d8",
|
||
"1dd09c89af8448ed9673238c4a3ebb8e",
|
||
"fc2503b36be542e5a3512b8196c30e2b",
|
||
"8eb569059fa74218a9f47c78e3db8436",
|
||
"24abb274aee648eaa308802754b96b7a",
|
||
"aab5cad3e7d94ae981eac90756bf8d41",
|
||
"fc353140430841929ff5a94e09a4143e",
|
||
"f23d67fd143844a393b1a08ee3d48969",
|
||
"f7be3e08cb514922b0f67913216005dc",
|
||
"32a2ce7715a941b0bec06e5676252446",
|
||
"c9faf32b655f4fa992d641768a558220",
|
||
"17b604cbc8da43898eca3f1527e3b125",
|
||
"d30de94f30ce4da1a516c087074aee96",
|
||
"adcced2b10f046d0bb31d20e4ec46708",
|
||
"bb8ce706f3644b13a5a6982b052fec84",
|
||
"2a8fa16116094071970fac4c8de210e7",
|
||
"2b766b35ab0944bca286e1a7dea163a4",
|
||
"f1395abbe0c14c2b925caef7b3630a94",
|
||
"866570d7610f4843b3ff943809239197",
|
||
"b5d63d011ffb484d969b3a1db52837a0",
|
||
"d0e5d5dedb7f48c4b8467f75a374b1ee",
|
||
"133b2906561441ceb62aaf52ef73e237",
|
||
"c1f9e1738aad45a3918eb0ee7fe7e1b9",
|
||
"b0897d82b3d1409880d4739ebc924ec1",
|
||
"fd502663b2bf4538845cc4ba89605dce",
|
||
"8d3c98af85474a68b5a11836909446f2",
|
||
"e58e692e115b44469ec23491d22001f9",
|
||
"70662fe04f374bc1a4f977526bc7b91e",
|
||
"f77bc5ec0a1a43028497d888b399e8ef",
|
||
"5db3f48937274eb9bc8823956bde1f0b",
|
||
"829fcb51001c4c92b9dfc7d037125075",
|
||
"fddfc33676b64b9d90429a5339bbeedb",
|
||
"c569f575d48e49c68e02c148bede9f70",
|
||
"9fb790cca3334d3b8e8b9c7c02a35cf6",
|
||
"7edfe8f0b73641a1bfa576aae0703728",
|
||
"86cfd09655f14aba8efcb98b5933865a",
|
||
"55969ecc0f2e4a599a5da24b97d856b2",
|
||
"35b7eb5a427046358c978089ecb9d550",
|
||
"a0032c1faac44445bec67c334390980e",
|
||
"ec01cb7f32f5448ca866647e3ebedbfb",
|
||
"f1ee9050cee845f88e9baf513535785b",
|
||
"5f4b7a51deb94d4dbae86148225c19b5",
|
||
"81081eff27b242e8b96f8b17348f5fb2",
|
||
"a970d1c066994b95835ff14d47d201cc",
|
||
"5659feb2b0924d9f9e9324cd4c05777d",
|
||
"eb21821900034762885653d6b54f5461",
|
||
"7455c4b1c5ac4977b678845a5ba2ea78",
|
||
"5f6799d3ddbc4c369e1aae2b95b3904c",
|
||
"11286368590748a295186146162297ce",
|
||
"8aab56f7ede942eda07d132777e5c1a6",
|
||
"74e2c6e41731406ba201594f9e3de0be",
|
||
"d48c6048e8af487aaf92327e8ed4fb7f",
|
||
"17cb59373eef4e27b6fd58a29303ecc6",
|
||
"fef878d871614253836af7f166e40010",
|
||
"6f2162b33b2b4af4af632a9b1f20e291",
|
||
"fc729efb3eed4f80900f2d110e1e6d4e",
|
||
"23038bfafd9b4be9ae46bbfabbc5b624",
|
||
"59d9f15287c1497b82bf7ee540118ac6",
|
||
"d58b6979f60e42c2a5a79b789e790a03",
|
||
"e7b1d27f3aa64d4f8d09127e36037731",
|
||
"374c74aa844f4b13b089bb70d377d698",
|
||
"82caada33e2640d69f520b524a4456f6",
|
||
"5efeb3a9060d4448b874a8872f3f165c",
|
||
"6ae20e8136884830825b5c49c37f867a",
|
||
"700d432dafd3460288bc63ac9d20a598",
|
||
"803645353525428ea3ca1cd17197350b",
|
||
"d6041f8ba8b346838088d2582dbbb95c",
|
||
"df3f52353df04a088de30577074117f9",
|
||
"0ef75435cae04344a2eb8a52565e74c8",
|
||
"201049abbcfa4c03a3ce4a66042c6f09",
|
||
"9422ac8de56949968f6dd0aac6c82e90",
|
||
"a4477dd1876f4a9d99408ea568ebdf0c",
|
||
"62132fd350844e9487633e66692c0c51",
|
||
"4b3af99603cd4614a32a7dd0f0cf69a7",
|
||
"d20552706e624d81be477cf53c70de48",
|
||
"1ace1068c2a74419822f05b01382b66c",
|
||
"92862060d6b3404395b9d26b762673e0",
|
||
"2d7de6a858c54f2792e4d38e1b2a57fc",
|
||
"f4fac1abd5d54adf8e25bca6791daf7f",
|
||
"6198eafef9d8467d9a63a5329cd6feac",
|
||
"00164598fdbe4062910ad66f0201d9c3",
|
||
"766d69ba63734c8e9dea95623c060c18",
|
||
"20fbbcc1d6c7459fafd988d41438eb80",
|
||
"e503fe4702d440d58db6c8ebcef5ca8d",
|
||
"1bd87756be65458da1130d62b4d61c5a",
|
||
"9776edf5da834fa887b501e385c8977a",
|
||
"1b73671e115f4d5f93e0cf3ace65edf0",
|
||
"b36db9ac6eba433a985087fb6ac7f88f",
|
||
"f2f98c2d73f24d7f973a578f90255a76",
|
||
"49277a7a3089460fa77ce74f54f263a3",
|
||
"0f0d8cccdf3f4ec68caad47d432c2e6b",
|
||
"e849e2fbaa054d4394bd0d081fa919c5",
|
||
"fdf218b36eda42aa9ed2dd633d240f9d",
|
||
"d7f5fafaa9b8473996724860957e053c",
|
||
"d91686aad27f4c39b9dc2952bb175074",
|
||
"4cb2ab536a6a48869357dcdb85aa07e3",
|
||
"7d5196e467db44409a244cf73bc61fdc",
|
||
"9c4cc76511744dd0b2502135aa9b26ad",
|
||
"2d5274420c074ca1bcbcc1c1414421be",
|
||
"653f135e75d64a4886fc8aaf9efe2e8e",
|
||
"5f48da1818b54f148e9c6e9b61dda7f4",
|
||
"a3a139b1683745958cfd65f4d5855071",
|
||
"072dbd1ad830460fb1609deb6a4a3daf",
|
||
"f78c464090be4742be047cadf84cd5d7",
|
||
"bae635ed7cd54c64aeb618619a5b4207",
|
||
"bf0c6a864ed946738528c16e1ce7ca3e",
|
||
"0effabe282f7485f9a41ec518499b376",
|
||
"cab3e18cde1e40898df29f80af4c049f",
|
||
"3371bf2f419447c6977db12f3bc8a0ac",
|
||
"55fcdf435e754088b572ac4cf61ae2e0",
|
||
"bd74fe36a9c54c5dac5bcda51afee7cf",
|
||
"d723a2df495a442dabebd2e59797435a",
|
||
"bac0681cfc8143daa8276eeea99e13ab",
|
||
"fe5c4bc05b2548e2bd5efac843351c69"
|
||
]
|
||
},
|
||
"id": "bcR4tWQl0rqt",
|
||
"outputId": "a314ee1d-e9b4-4056-dd23-6466e5ccce5d"
|
||
},
|
||
"execution_count": 3,
|
||
"outputs": [
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading builder script: 0%| | 0.00/3.97k [00:00<?, ?B/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "fbc74a6e57c94d66bfb493c150bbbf47"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading metadata: 0%| | 0.00/3.28k [00:00<?, ?B/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "0d14dee025724d3097b80fe729ae3532"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading readme: 0%| | 0.00/8.78k [00:00<?, ?B/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "24abb274aee648eaa308802754b96b7a"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stderr",
|
||
"text": [
|
||
"WARNING:datasets.builder:No config specified, defaulting to: emotion/split\n"
|
||
]
|
||
},
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Downloading and preparing dataset emotion/split to /root/.cache/huggingface/datasets/emotion/split/1.0.0/cca5efe2dfeb58c1d098e0f9eeb200e9927d889b5a03c67097275dfb5fe463bd...\n"
|
||
]
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading data files: 0%| | 0/3 [00:00<?, ?it/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "2a8fa16116094071970fac4c8de210e7"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading data: 0%| | 0.00/592k [00:00<?, ?B/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "e58e692e115b44469ec23491d22001f9"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading data: 0%| | 0.00/74.0k [00:00<?, ?B/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "35b7eb5a427046358c978089ecb9d550"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Downloading data: 0%| | 0.00/74.9k [00:00<?, ?B/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "11286368590748a295186146162297ce"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Extracting data files: 0%| | 0/3 [00:00<?, ?it/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "e7b1d27f3aa64d4f8d09127e36037731"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Generating train split: 0%| | 0/16000 [00:00<?, ? examples/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "9422ac8de56949968f6dd0aac6c82e90"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Generating validation split: 0%| | 0/2000 [00:00<?, ? examples/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "766d69ba63734c8e9dea95623c060c18"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
"Generating test split: 0%| | 0/2000 [00:00<?, ? examples/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "fdf218b36eda42aa9ed2dd633d240f9d"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"Dataset emotion downloaded and prepared to /root/.cache/huggingface/datasets/emotion/split/1.0.0/cca5efe2dfeb58c1d098e0f9eeb200e9927d889b5a03c67097275dfb5fe463bd. Subsequent calls will reuse this data.\n"
|
||
]
|
||
},
|
||
{
|
||
"output_type": "display_data",
|
||
"data": {
|
||
"text/plain": [
|
||
" 0%| | 0/3 [00:00<?, ?it/s]"
|
||
],
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"version_major": 2,
|
||
"version_minor": 0,
|
||
"model_id": "f78c464090be4742be047cadf84cd5d7"
|
||
}
|
||
},
|
||
"metadata": {}
|
||
},
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"mkdir: created directory 'data'\n",
|
||
"Train: 16000\n",
|
||
"Valid: 2000\n",
|
||
"Label 1: 581\n",
|
||
"Label 2: 695\n",
|
||
"Valid: 637\n",
|
||
"Test : 639\n",
|
||
"Saving into: data/train.json\n",
|
||
"Saving into: data/s2s-train.json\n",
|
||
"Saving into: data/valid.json\n",
|
||
"Saving into: data/s2s-valid.json\n",
|
||
"Saving into: data/test.json\n",
|
||
"Saving into: data/s2s-test.json\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"\n",
|
||
"!head -n 2500 data/train.json > data/train-5k.json\n",
|
||
"!tail -n 2500 data/train.json >> data/train-5k.json\n",
|
||
"!wc -l data/train-5k.json"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "pRmHIvyB0fZe",
|
||
"outputId": "b3291697-b066-4acb-e9f8-d1aef3599dac"
|
||
},
|
||
"execution_count": 4,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"5000 data/train-5k.json\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"from pathlib import Path\n",
|
||
"\n",
|
||
"for file_name in [\"train\", \"valid\", \"test\", \"s2s-train\", \"s2s-valid\", \"s2s-test\"]:\n",
|
||
" print(f\"=== {file_name} ===\")\n",
|
||
" all_text = Path(f\"data/{file_name}.json\").read_text().split('\\n')\n",
|
||
" text = all_text[:2500] + all_text[-2500:]\n",
|
||
" Path(f\"data/{file_name}-5k.json\").write_text(\"\\n\".join(text))"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "rFa6ijdx2L28",
|
||
"outputId": "2dcdecf5-6240-40cb-c157-8548f17b920a"
|
||
},
|
||
"execution_count": 5,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"=== train ===\n",
|
||
"=== valid ===\n",
|
||
"=== test ===\n",
|
||
"=== s2s-train ===\n",
|
||
"=== s2s-valid ===\n",
|
||
"=== s2s-test ===\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"import os\n",
|
||
"\n",
|
||
"os.environ['TOKENIZERS_PARALLELISM'] = 'true'"
|
||
],
|
||
"metadata": {
|
||
"id": "8opbDvBv3ZlK"
|
||
},
|
||
"execution_count": 6,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [],
|
||
"metadata": {
|
||
"id": "pxuxjHt8P57X"
|
||
},
|
||
"execution_count": null,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"!python run_glue.py \\\n",
|
||
"--cache_dir .cache_training \\\n",
|
||
"--model_name_or_path gpt2 \\\n",
|
||
"--custom_model gpt2_hidden \\\n",
|
||
"--freeze_weights \\\n",
|
||
"--train_file data/train-5k.json \\\n",
|
||
"--validation_file data/valid-5k.json \\\n",
|
||
"--test_file data/test-5k.json \\\n",
|
||
"--per_device_train_batch_size 24 \\\n",
|
||
"--per_device_eval_batch_size 24 \\\n",
|
||
"--do_train \\\n",
|
||
"--do_eval \\\n",
|
||
"--do_predict \\\n",
|
||
"--max_seq_length 128 \\\n",
|
||
"--learning_rate 2e-5 \\\n",
|
||
"--num_train_epochs 5 \\\n",
|
||
"--output_dir out/imdb-5k/gpt2"
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 1000
|
||
},
|
||
"id": "XkkeRPG_z3Jc",
|
||
"outputId": "b0886744-a6a5-4472-dbc2-94a3928e6cdf"
|
||
},
|
||
"execution_count": 7,
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stdout",
|
||
"text": [
|
||
"2023-02-12 18:48:04.170632: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n",
|
||
"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
|
||
"2023-02-12 18:48:06.020374: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia\n",
|
||
"2023-02-12 18:48:06.020480: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia\n",
|
||
"2023-02-12 18:48:06.020498: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n",
|
||
"WARNING:__main__:Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n",
|
||
"INFO:__main__:Training/evaluation parameters TrainingArguments(\n",
|
||
"_n_gpu=1,\n",
|
||
"adafactor=False,\n",
|
||
"adam_beta1=0.9,\n",
|
||
"adam_beta2=0.999,\n",
|
||
"adam_epsilon=1e-08,\n",
|
||
"auto_find_batch_size=False,\n",
|
||
"bf16=False,\n",
|
||
"bf16_full_eval=False,\n",
|
||
"data_seed=None,\n",
|
||
"dataloader_drop_last=False,\n",
|
||
"dataloader_num_workers=0,\n",
|
||
"dataloader_pin_memory=True,\n",
|
||
"ddp_bucket_cap_mb=None,\n",
|
||
"ddp_find_unused_parameters=None,\n",
|
||
"ddp_timeout=1800,\n",
|
||
"debug=[],\n",
|
||
"deepspeed=None,\n",
|
||
"disable_tqdm=False,\n",
|
||
"do_eval=True,\n",
|
||
"do_predict=True,\n",
|
||
"do_train=True,\n",
|
||
"eval_accumulation_steps=None,\n",
|
||
"eval_delay=0,\n",
|
||
"eval_steps=None,\n",
|
||
"evaluation_strategy=no,\n",
|
||
"fp16=False,\n",
|
||
"fp16_backend=auto,\n",
|
||
"fp16_full_eval=False,\n",
|
||
"fp16_opt_level=O1,\n",
|
||
"fsdp=[],\n",
|
||
"fsdp_min_num_params=0,\n",
|
||
"fsdp_transformer_layer_cls_to_wrap=None,\n",
|
||
"full_determinism=False,\n",
|
||
"gradient_accumulation_steps=1,\n",
|
||
"gradient_checkpointing=False,\n",
|
||
"greater_is_better=None,\n",
|
||
"group_by_length=False,\n",
|
||
"half_precision_backend=auto,\n",
|
||
"hub_model_id=None,\n",
|
||
"hub_private_repo=False,\n",
|
||
"hub_strategy=every_save,\n",
|
||
"hub_token=<HUB_TOKEN>,\n",
|
||
"ignore_data_skip=False,\n",
|
||
"include_inputs_for_metrics=False,\n",
|
||
"jit_mode_eval=False,\n",
|
||
"label_names=None,\n",
|
||
"label_smoothing_factor=0.0,\n",
|
||
"learning_rate=2e-05,\n",
|
||
"length_column_name=length,\n",
|
||
"load_best_model_at_end=False,\n",
|
||
"local_rank=-1,\n",
|
||
"log_level=passive,\n",
|
||
"log_level_replica=passive,\n",
|
||
"log_on_each_node=True,\n",
|
||
"logging_dir=out/imdb-5k/gpt2/runs/Feb12_18-48-11_0a1839978b23,\n",
|
||
"logging_first_step=False,\n",
|
||
"logging_nan_inf_filter=True,\n",
|
||
"logging_steps=500,\n",
|
||
"logging_strategy=steps,\n",
|
||
"lr_scheduler_type=linear,\n",
|
||
"max_grad_norm=1.0,\n",
|
||
"max_steps=-1,\n",
|
||
"metric_for_best_model=None,\n",
|
||
"mp_parameters=,\n",
|
||
"no_cuda=False,\n",
|
||
"num_train_epochs=5.0,\n",
|
||
"optim=adamw_hf,\n",
|
||
"optim_args=None,\n",
|
||
"output_dir=out/imdb-5k/gpt2,\n",
|
||
"overwrite_output_dir=False,\n",
|
||
"past_index=-1,\n",
|
||
"per_device_eval_batch_size=24,\n",
|
||
"per_device_train_batch_size=24,\n",
|
||
"prediction_loss_only=False,\n",
|
||
"push_to_hub=False,\n",
|
||
"push_to_hub_model_id=None,\n",
|
||
"push_to_hub_organization=None,\n",
|
||
"push_to_hub_token=<PUSH_TO_HUB_TOKEN>,\n",
|
||
"ray_scope=last,\n",
|
||
"remove_unused_columns=True,\n",
|
||
"report_to=['tensorboard'],\n",
|
||
"resume_from_checkpoint=None,\n",
|
||
"run_name=out/imdb-5k/gpt2,\n",
|
||
"save_on_each_node=False,\n",
|
||
"save_steps=500,\n",
|
||
"save_strategy=steps,\n",
|
||
"save_total_limit=None,\n",
|
||
"seed=42,\n",
|
||
"sharded_ddp=[],\n",
|
||
"skip_memory_metrics=True,\n",
|
||
"tf32=None,\n",
|
||
"torch_compile=False,\n",
|
||
"torch_compile_backend=None,\n",
|
||
"torch_compile_mode=None,\n",
|
||
"torchdynamo=None,\n",
|
||
"tpu_metrics_debug=False,\n",
|
||
"tpu_num_cores=None,\n",
|
||
"use_ipex=False,\n",
|
||
"use_legacy_prediction_loop=False,\n",
|
||
"use_mps_device=False,\n",
|
||
"warmup_ratio=0.0,\n",
|
||
"warmup_steps=0,\n",
|
||
"weight_decay=0.0,\n",
|
||
"xpu_backend=None,\n",
|
||
")\n",
|
||
"INFO:__main__:load a local file for train: data/train-5k.json\n",
|
||
"INFO:__main__:load a local file for validation: data/valid-5k.json\n",
|
||
"INFO:__main__:load a local file for test: data/test-5k.json\n",
|
||
"WARNING:datasets.builder:Using custom data configuration default-eb684d402fe5af19\n",
|
||
"INFO:datasets.info:Loading Dataset Infos from /usr/local/lib/python3.8/dist-packages/datasets/packaged_modules/json\n",
|
||
"INFO:datasets.builder:Generating dataset json (/content/.cache_training/json/default-eb684d402fe5af19/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51)\n",
|
||
"Downloading and preparing dataset json/default to /content/.cache_training/json/default-eb684d402fe5af19/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51...\n",
|
||
"Downloading data files: 100% 3/3 [00:00<00:00, 8519.24it/s]\n",
|
||
"INFO:datasets.download.download_manager:Downloading took 0.0 min\n",
|
||
"INFO:datasets.download.download_manager:Checksum Computation took 0.0 min\n",
|
||
"Extracting data files: 100% 3/3 [00:00<00:00, 1477.73it/s]\n",
|
||
"INFO:datasets.utils.info_utils:Unable to verify checksums.\n",
|
||
"INFO:datasets.builder:Generating train split\n",
|
||
"INFO:datasets.builder:Generating validation split\n",
|
||
"INFO:datasets.builder:Generating test split\n",
|
||
"INFO:datasets.utils.info_utils:Unable to verify splits sizes.\n",
|
||
"Dataset json downloaded and prepared to /content/.cache_training/json/default-eb684d402fe5af19/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51. Subsequent calls will reuse this data.\n",
|
||
"100% 3/3 [00:00<00:00, 730.84it/s]\n",
|
||
"Downloading (…)lve/main/config.json: 100% 665/665 [00:00<00:00, 91.3kB/s]\n",
|
||
"[INFO|configuration_utils.py:660] 2023-02-12 18:48:12,394 >> loading configuration file config.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/config.json\n",
|
||
"[INFO|configuration_utils.py:712] 2023-02-12 18:48:12,395 >> Model config GPT2Config {\n",
|
||
" \"_name_or_path\": \"gpt2\",\n",
|
||
" \"activation_function\": \"gelu_new\",\n",
|
||
" \"architectures\": [\n",
|
||
" \"GPT2LMHeadModel\"\n",
|
||
" ],\n",
|
||
" \"attn_pdrop\": 0.1,\n",
|
||
" \"bos_token_id\": 50256,\n",
|
||
" \"embd_pdrop\": 0.1,\n",
|
||
" \"eos_token_id\": 50256,\n",
|
||
" \"id2label\": {\n",
|
||
" \"0\": \"LABEL_0\",\n",
|
||
" \"1\": \"LABEL_1\",\n",
|
||
" \"2\": \"LABEL_2\",\n",
|
||
" \"3\": \"LABEL_3\",\n",
|
||
" \"4\": \"LABEL_4\",\n",
|
||
" \"5\": \"LABEL_5\"\n",
|
||
" },\n",
|
||
" \"initializer_range\": 0.02,\n",
|
||
" \"label2id\": {\n",
|
||
" \"LABEL_0\": 0,\n",
|
||
" \"LABEL_1\": 1,\n",
|
||
" \"LABEL_2\": 2,\n",
|
||
" \"LABEL_3\": 3,\n",
|
||
" \"LABEL_4\": 4,\n",
|
||
" \"LABEL_5\": 5\n",
|
||
" },\n",
|
||
" \"layer_norm_epsilon\": 1e-05,\n",
|
||
" \"model_type\": \"gpt2\",\n",
|
||
" \"n_ctx\": 1024,\n",
|
||
" \"n_embd\": 768,\n",
|
||
" \"n_head\": 12,\n",
|
||
" \"n_inner\": null,\n",
|
||
" \"n_layer\": 12,\n",
|
||
" \"n_positions\": 1024,\n",
|
||
" \"reorder_and_upcast_attn\": false,\n",
|
||
" \"resid_pdrop\": 0.1,\n",
|
||
" \"scale_attn_by_inverse_layer_idx\": false,\n",
|
||
" \"scale_attn_weights\": true,\n",
|
||
" \"summary_activation\": null,\n",
|
||
" \"summary_first_dropout\": 0.1,\n",
|
||
" \"summary_proj_to_labels\": true,\n",
|
||
" \"summary_type\": \"cls_index\",\n",
|
||
" \"summary_use_proj\": true,\n",
|
||
" \"task_specific_params\": {\n",
|
||
" \"text-generation\": {\n",
|
||
" \"do_sample\": true,\n",
|
||
" \"max_length\": 50\n",
|
||
" }\n",
|
||
" },\n",
|
||
" \"transformers_version\": \"4.26.1\",\n",
|
||
" \"use_cache\": true,\n",
|
||
" \"vocab_size\": 50257\n",
|
||
"}\n",
|
||
"\n",
|
||
"[INFO|tokenization_auto.py:458] 2023-02-12 18:48:12,427 >> Could not locate the tokenizer configuration file, will try to use the model config instead.\n",
|
||
"[INFO|configuration_utils.py:660] 2023-02-12 18:48:12,460 >> loading configuration file config.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/config.json\n",
|
||
"[INFO|configuration_utils.py:712] 2023-02-12 18:48:12,461 >> Model config GPT2Config {\n",
|
||
" \"_name_or_path\": \"gpt2\",\n",
|
||
" \"activation_function\": \"gelu_new\",\n",
|
||
" \"architectures\": [\n",
|
||
" \"GPT2LMHeadModel\"\n",
|
||
" ],\n",
|
||
" \"attn_pdrop\": 0.1,\n",
|
||
" \"bos_token_id\": 50256,\n",
|
||
" \"embd_pdrop\": 0.1,\n",
|
||
" \"eos_token_id\": 50256,\n",
|
||
" \"initializer_range\": 0.02,\n",
|
||
" \"layer_norm_epsilon\": 1e-05,\n",
|
||
" \"model_type\": \"gpt2\",\n",
|
||
" \"n_ctx\": 1024,\n",
|
||
" \"n_embd\": 768,\n",
|
||
" \"n_head\": 12,\n",
|
||
" \"n_inner\": null,\n",
|
||
" \"n_layer\": 12,\n",
|
||
" \"n_positions\": 1024,\n",
|
||
" \"reorder_and_upcast_attn\": false,\n",
|
||
" \"resid_pdrop\": 0.1,\n",
|
||
" \"scale_attn_by_inverse_layer_idx\": false,\n",
|
||
" \"scale_attn_weights\": true,\n",
|
||
" \"summary_activation\": null,\n",
|
||
" \"summary_first_dropout\": 0.1,\n",
|
||
" \"summary_proj_to_labels\": true,\n",
|
||
" \"summary_type\": \"cls_index\",\n",
|
||
" \"summary_use_proj\": true,\n",
|
||
" \"task_specific_params\": {\n",
|
||
" \"text-generation\": {\n",
|
||
" \"do_sample\": true,\n",
|
||
" \"max_length\": 50\n",
|
||
" }\n",
|
||
" },\n",
|
||
" \"transformers_version\": \"4.26.1\",\n",
|
||
" \"use_cache\": true,\n",
|
||
" \"vocab_size\": 50257\n",
|
||
"}\n",
|
||
"\n",
|
||
"Downloading (…)olve/main/vocab.json: 100% 1.04M/1.04M [00:00<00:00, 68.6MB/s]\n",
|
||
"Downloading (…)olve/main/merges.txt: 100% 456k/456k [00:00<00:00, 36.6MB/s]\n",
|
||
"Downloading (…)/main/tokenizer.json: 100% 1.36M/1.36M [00:00<00:00, 61.1MB/s]\n",
|
||
"[INFO|tokenization_utils_base.py:1802] 2023-02-12 18:48:12,933 >> loading file vocab.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/vocab.json\n",
|
||
"[INFO|tokenization_utils_base.py:1802] 2023-02-12 18:48:12,933 >> loading file merges.txt from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/merges.txt\n",
|
||
"[INFO|tokenization_utils_base.py:1802] 2023-02-12 18:48:12,933 >> loading file tokenizer.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/tokenizer.json\n",
|
||
"[INFO|tokenization_utils_base.py:1802] 2023-02-12 18:48:12,933 >> loading file added_tokens.json from cache at None\n",
|
||
"[INFO|tokenization_utils_base.py:1802] 2023-02-12 18:48:12,933 >> loading file special_tokens_map.json from cache at None\n",
|
||
"[INFO|tokenization_utils_base.py:1802] 2023-02-12 18:48:12,933 >> loading file tokenizer_config.json from cache at None\n",
|
||
"[INFO|configuration_utils.py:660] 2023-02-12 18:48:12,934 >> loading configuration file config.json from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/config.json\n",
|
||
"[INFO|configuration_utils.py:712] 2023-02-12 18:48:12,935 >> Model config GPT2Config {\n",
|
||
" \"_name_or_path\": \"gpt2\",\n",
|
||
" \"activation_function\": \"gelu_new\",\n",
|
||
" \"architectures\": [\n",
|
||
" \"GPT2LMHeadModel\"\n",
|
||
" ],\n",
|
||
" \"attn_pdrop\": 0.1,\n",
|
||
" \"bos_token_id\": 50256,\n",
|
||
" \"embd_pdrop\": 0.1,\n",
|
||
" \"eos_token_id\": 50256,\n",
|
||
" \"initializer_range\": 0.02,\n",
|
||
" \"layer_norm_epsilon\": 1e-05,\n",
|
||
" \"model_type\": \"gpt2\",\n",
|
||
" \"n_ctx\": 1024,\n",
|
||
" \"n_embd\": 768,\n",
|
||
" \"n_head\": 12,\n",
|
||
" \"n_inner\": null,\n",
|
||
" \"n_layer\": 12,\n",
|
||
" \"n_positions\": 1024,\n",
|
||
" \"reorder_and_upcast_attn\": false,\n",
|
||
" \"resid_pdrop\": 0.1,\n",
|
||
" \"scale_attn_by_inverse_layer_idx\": false,\n",
|
||
" \"scale_attn_weights\": true,\n",
|
||
" \"summary_activation\": null,\n",
|
||
" \"summary_first_dropout\": 0.1,\n",
|
||
" \"summary_proj_to_labels\": true,\n",
|
||
" \"summary_type\": \"cls_index\",\n",
|
||
" \"summary_use_proj\": true,\n",
|
||
" \"task_specific_params\": {\n",
|
||
" \"text-generation\": {\n",
|
||
" \"do_sample\": true,\n",
|
||
" \"max_length\": 50\n",
|
||
" }\n",
|
||
" },\n",
|
||
" \"transformers_version\": \"4.26.1\",\n",
|
||
" \"use_cache\": true,\n",
|
||
" \"vocab_size\": 50257\n",
|
||
"}\n",
|
||
"\n",
|
||
"INFO:__main__:Using hidden states in model: True\n",
|
||
"INFO:__main__:Using implementation from class: GPT2ForSequenceClassificationCustom\n",
|
||
"Downloading (…)\"pytorch_model.bin\";: 100% 548M/548M [00:02<00:00, 259MB/s]\n",
|
||
"[INFO|modeling_utils.py:2275] 2023-02-12 18:48:15,229 >> loading weights file pytorch_model.bin from cache at .cache_training/models--gpt2/snapshots/e7da7f221d5bf496a48136c0cd264e630fe9fcc8/pytorch_model.bin\n",
|
||
"[INFO|modeling_utils.py:2857] 2023-02-12 18:48:20,237 >> All model checkpoint weights were used when initializing GPT2ForSequenceClassificationCustom.\n",
|
||
"\n",
|
||
"[WARNING|modeling_utils.py:2859] 2023-02-12 18:48:20,237 >> Some weights of GPT2ForSequenceClassificationCustom were not initialized from the model checkpoint at gpt2 and are newly initialized: ['score.dense_2.bias', 'score.out_proj.weight', 'score.dense_2.weight', 'score.dense_1_hidden.bias', 'score.dense_1_input.weight', 'score.dense_1_input.bias', 'score.dense_1_hidden.weight']\n",
|
||
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
|
||
"INFO:__main__:Freezing encoder weights\n",
|
||
"INFO:__main__:Freezing layer 1\n",
|
||
"INFO:__main__:Freezing layer 2\n",
|
||
"INFO:__main__:Freezing layer 3\n",
|
||
"INFO:__main__:Freezing layer 4\n",
|
||
"INFO:__main__:Freezing layer 5\n",
|
||
"INFO:__main__:Freezing layer 6\n",
|
||
"INFO:__main__:Freezing layer 7\n",
|
||
"INFO:__main__:Freezing layer 8\n",
|
||
"INFO:__main__:Freezing layer 9\n",
|
||
"INFO:__main__:Freezing layer 10\n",
|
||
"INFO:__main__:Freezing layer 11\n",
|
||
"INFO:__main__:Freezing layer 12\n",
|
||
"INFO:__main__:Freezing layer 13\n",
|
||
"INFO:__main__:Freezing layer 14\n",
|
||
"INFO:__main__:Freezing layer 15\n",
|
||
"INFO:__main__:Freezing layer 16\n",
|
||
"INFO:__main__:Freezing layer 17\n",
|
||
"INFO:__main__:Freezing layer 18\n",
|
||
"INFO:__main__:Freezing layer 19\n",
|
||
"INFO:__main__:Freezing layer 20\n",
|
||
"INFO:__main__:Freezing layer 21\n",
|
||
"INFO:__main__:Freezing layer 22\n",
|
||
"INFO:__main__:Freezing layer 23\n",
|
||
"INFO:__main__:Freezing layer 24\n",
|
||
"INFO:__main__:Freezing layer 25\n",
|
||
"INFO:__main__:Freezing layer 26\n",
|
||
"INFO:__main__:Freezing layer 27\n",
|
||
"INFO:__main__:Freezing layer 28\n",
|
||
"INFO:__main__:Freezing layer 29\n",
|
||
"INFO:__main__:Freezing layer 30\n",
|
||
"INFO:__main__:Freezing layer 31\n",
|
||
"INFO:__main__:Freezing layer 32\n",
|
||
"INFO:__main__:Freezing layer 33\n",
|
||
"INFO:__main__:Freezing layer 34\n",
|
||
"INFO:__main__:Freezing layer 35\n",
|
||
"INFO:__main__:Freezing layer 36\n",
|
||
"INFO:__main__:Freezing layer 37\n",
|
||
"INFO:__main__:Freezing layer 38\n",
|
||
"INFO:__main__:Freezing layer 39\n",
|
||
"INFO:__main__:Freezing layer 40\n",
|
||
"INFO:__main__:Ignoring layer 41\n",
|
||
"INFO:__main__:Ignoring layer 42\n",
|
||
"INFO:__main__:Ignoring layer 43\n",
|
||
"INFO:__main__:Ignoring layer 44\n",
|
||
"INFO:__main__:Ignoring layer 45\n",
|
||
"INFO:__main__:Ignoring layer 46\n",
|
||
"INFO:__main__:Ignoring layer 47\n",
|
||
"INFO:__main__:Ignoring layer 48\n",
|
||
"INFO:__main__:Ignoring layer 49\n",
|
||
"INFO:__main__:Ignoring layer 50\n",
|
||
"INFO:__main__:Ignoring layer 51\n",
|
||
"INFO:__main__:Ignoring layer 52\n",
|
||
"INFO:__main__:Ignoring layer 53\n",
|
||
"INFO:__main__:Ignoring layer 54\n",
|
||
"INFO:__main__:Ignoring layer 55\n",
|
||
"INFO:__main__:Ignoring layer 56\n",
|
||
"INFO:__main__:Ignoring layer 57\n",
|
||
"INFO:__main__:Ignoring layer 58\n",
|
||
"INFO:__main__:Ignoring layer 59\n",
|
||
"INFO:__main__:Ignoring layer 60\n",
|
||
"INFO:__main__:Ignoring layer 61\n",
|
||
"INFO:__main__:Ignoring layer 62\n",
|
||
"INFO:__main__:Ignoring layer 63\n",
|
||
"INFO:__main__:Ignoring layer 64\n",
|
||
"INFO:__main__:Ignoring layer 65\n",
|
||
"INFO:__main__:Ignoring layer 66\n",
|
||
"INFO:__main__:Ignoring layer 67\n",
|
||
"INFO:__main__:Ignoring layer 68\n",
|
||
"INFO:__main__:Ignoring layer 69\n",
|
||
"INFO:__main__:Ignoring layer 70\n",
|
||
"INFO:__main__:Ignoring layer 71\n",
|
||
"INFO:__main__:Ignoring layer 72\n",
|
||
"INFO:__main__:Ignoring layer 73\n",
|
||
"INFO:__main__:Ignoring layer 74\n",
|
||
"INFO:__main__:Ignoring layer 75\n",
|
||
"INFO:__main__:Ignoring layer 76\n",
|
||
"INFO:__main__:Ignoring layer 77\n",
|
||
"INFO:__main__:Ignoring layer 78\n",
|
||
"INFO:__main__:Ignoring layer 79\n",
|
||
"INFO:__main__:Ignoring layer 80\n",
|
||
"INFO:__main__:Ignoring layer 81\n",
|
||
"INFO:__main__:Ignoring layer 82\n",
|
||
"INFO:__main__:Ignoring layer 83\n",
|
||
"INFO:__main__:Ignoring layer 84\n",
|
||
"INFO:__main__:Ignoring layer 85\n",
|
||
"INFO:__main__:Ignoring layer 86\n",
|
||
"INFO:__main__:Ignoring layer 87\n",
|
||
"INFO:__main__:Ignoring layer 88\n",
|
||
"INFO:__main__:Ignoring layer 89\n",
|
||
"INFO:__main__:Ignoring layer 90\n",
|
||
"INFO:__main__:Ignoring layer 91\n",
|
||
"INFO:__main__:Ignoring layer 92\n",
|
||
"INFO:__main__:Ignoring layer 93\n",
|
||
"INFO:__main__:Ignoring layer 94\n",
|
||
"INFO:__main__:Ignoring layer 95\n",
|
||
"INFO:__main__:Ignoring layer 96\n",
|
||
"INFO:__main__:Ignoring layer 97\n",
|
||
"INFO:__main__:Ignoring layer 98\n",
|
||
"INFO:__main__:Ignoring layer 99\n",
|
||
"INFO:__main__:Ignoring layer 100\n",
|
||
"INFO:__main__:Ignoring layer 101\n",
|
||
"INFO:__main__:Ignoring layer 102\n",
|
||
"INFO:__main__:Ignoring layer 103\n",
|
||
"INFO:__main__:Ignoring layer 104\n",
|
||
"INFO:__main__:Ignoring layer 105\n",
|
||
"INFO:__main__:Ignoring layer 106\n",
|
||
"INFO:__main__:Ignoring layer 107\n",
|
||
"INFO:__main__:Ignoring layer 108\n",
|
||
"INFO:__main__:Ignoring layer 109\n",
|
||
"INFO:__main__:Ignoring layer 110\n",
|
||
"INFO:__main__:Ignoring layer 111\n",
|
||
"INFO:__main__:Ignoring layer 112\n",
|
||
"INFO:__main__:Ignoring layer 113\n",
|
||
"INFO:__main__:Ignoring layer 114\n",
|
||
"INFO:__main__:Ignoring layer 115\n",
|
||
"INFO:__main__:Ignoring layer 116\n",
|
||
"INFO:__main__:Ignoring layer 117\n",
|
||
"INFO:__main__:Ignoring layer 118\n",
|
||
"INFO:__main__:Ignoring layer 119\n",
|
||
"INFO:__main__:Ignoring layer 120\n",
|
||
"INFO:__main__:Ignoring layer 121\n",
|
||
"INFO:__main__:Ignoring layer 122\n",
|
||
"INFO:__main__:Ignoring layer 123\n",
|
||
"INFO:__main__:Ignoring layer 124\n",
|
||
"INFO:__main__:Ignoring layer 125\n",
|
||
"INFO:__main__:Ignoring layer 126\n",
|
||
"INFO:__main__:Ignoring layer 127\n",
|
||
"INFO:__main__:Ignoring layer 128\n",
|
||
"INFO:__main__:Ignoring layer 129\n",
|
||
"INFO:__main__:Ignoring layer 130\n",
|
||
"INFO:__main__:Ignoring layer 131\n",
|
||
"INFO:__main__:Ignoring layer 132\n",
|
||
"INFO:__main__:Ignoring layer 133\n",
|
||
"INFO:__main__:Ignoring layer 134\n",
|
||
"INFO:__main__:Ignoring layer 135\n",
|
||
"INFO:__main__:Ignoring layer 136\n",
|
||
"INFO:__main__:Ignoring layer 137\n",
|
||
"INFO:__main__:Ignoring layer 138\n",
|
||
"INFO:__main__:Ignoring layer 139\n",
|
||
"INFO:__main__:Ignoring layer 140\n",
|
||
"INFO:__main__:Ignoring layer 141\n",
|
||
"INFO:__main__:Ignoring layer 142\n",
|
||
"INFO:__main__:Ignoring layer 143\n",
|
||
"INFO:__main__:Ignoring layer 144\n",
|
||
"INFO:__main__:Ignoring layer 145\n",
|
||
"INFO:__main__:Ignoring layer 146\n",
|
||
"INFO:__main__:Ignoring layer 147\n",
|
||
"INFO:__main__:Ignoring layer 148\n",
|
||
"INFO:__main__:Ignoring layer 149\n",
|
||
"INFO:__main__:Ignoring layer 150\n",
|
||
"INFO:__main__:Ignoring layer 151\n",
|
||
"INFO:__main__:Ignoring layer 152\n",
|
||
"INFO:__main__:Ignoring layer 153\n",
|
||
"INFO:__main__:Ignoring layer 154\n",
|
||
"INFO:__main__:Ignoring layer 155\n",
|
||
"[ERROR|tokenization_utils_base.py:1042] 2023-02-12 18:48:20,265 >> Using pad_token, but it is not set yet.\n",
|
||
"INFO:__main__:Set PAD token to EOS: <|endoftext|>\n",
|
||
"Running tokenizer on dataset: 0% 0/5 [00:00<?, ?ba/s]INFO:datasets.arrow_dataset:Caching processed dataset at /content/.cache_training/json/default-eb684d402fe5af19/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51/cache-226821bed74c0e17.arrow\n",
|
||
"Running tokenizer on dataset: 100% 5/5 [00:01<00:00, 3.34ba/s]\n",
|
||
"Running tokenizer on dataset: 0% 0/2 [00:00<?, ?ba/s]INFO:datasets.arrow_dataset:Caching processed dataset at /content/.cache_training/json/default-eb684d402fe5af19/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51/cache-b1f24dce00ae0c47.arrow\n",
|
||
"Running tokenizer on dataset: 100% 2/2 [00:00<00:00, 2.35ba/s]\n",
|
||
"Running tokenizer on dataset: 0% 0/2 [00:00<?, ?ba/s]INFO:datasets.arrow_dataset:Caching processed dataset at /content/.cache_training/json/default-eb684d402fe5af19/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51/cache-13134a48c79051f9.arrow\n",
|
||
"Running tokenizer on dataset: 100% 2/2 [00:00<00:00, 4.98ba/s]\n",
|
||
"INFO:__main__:Sample 912 of the training set: {'label': 2, 'text': 'i feel we need a little romantic boost in the relationship', 'input_ids': [72, 1254, 356, 761, 257, 1310, 14348, 5750, 287, 262, 2776, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}.\n",
|
||
"INFO:__main__:Sample 204 of the training set: {'label': 1, 'text': 'i feel pretty mellow so far about whatever healing wounding process may be getting underway', 'input_ids': [72, 1254, 2495, 33748, 322, 523, 1290, 546, 4232, 11516, 40942, 1429, 743, 307, 1972, 17715, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}.\n",
|
||
"INFO:__main__:Sample 2253 of the training set: {'label': 1, 'text': 'i feel ive answered those questions for her and shes pretty trusting for the most part', 'input_ids': [72, 1254, 220, 425, 9373, 883, 2683, 329, 607, 290, 673, 82, 2495, 33914, 329, 262, 749, 636, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256, 50256], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}.\n",
|
||
"Downloading builder script: 100% 4.20k/4.20k [00:00<00:00, 3.58MB/s]\n",
|
||
"[INFO|trainer.py:710] 2023-02-12 18:48:30,921 >> The following columns in the training set don't have a corresponding argument in `GPT2ForSequenceClassificationCustom.forward` and have been ignored: text. If text are not expected by `GPT2ForSequenceClassificationCustom.forward`, you can safely ignore this message.\n",
|
||
"/usr/local/lib/python3.8/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
|
||
" warnings.warn(\n",
|
||
"[INFO|trainer.py:1650] 2023-02-12 18:48:30,927 >> ***** Running training *****\n",
|
||
"[INFO|trainer.py:1651] 2023-02-12 18:48:30,927 >> Num examples = 4999\n",
|
||
"[INFO|trainer.py:1652] 2023-02-12 18:48:30,927 >> Num Epochs = 5\n",
|
||
"[INFO|trainer.py:1653] 2023-02-12 18:48:30,927 >> Instantaneous batch size per device = 24\n",
|
||
"[INFO|trainer.py:1654] 2023-02-12 18:48:30,927 >> Total train batch size (w. parallel, distributed & accumulation) = 24\n",
|
||
"[INFO|trainer.py:1655] 2023-02-12 18:48:30,927 >> Gradient Accumulation steps = 1\n",
|
||
"[INFO|trainer.py:1656] 2023-02-12 18:48:30,927 >> Total optimization steps = 1045\n",
|
||
"[INFO|trainer.py:1657] 2023-02-12 18:48:30,928 >> Number of trainable parameters = 68517888\n",
|
||
"{'loss': 1.0247, 'learning_rate': 1.0430622009569378e-05, 'epoch': 2.39}\n",
|
||
" 48% 500/1045 [03:49<04:14, 2.14it/s][INFO|trainer.py:2709] 2023-02-12 18:52:20,075 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-500\n",
|
||
"[INFO|configuration_utils.py:453] 2023-02-12 18:52:20,076 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-500/config.json\n",
|
||
"[INFO|modeling_utils.py:1704] 2023-02-12 18:52:21,822 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-500/pytorch_model.bin\n",
|
||
"[INFO|tokenization_utils_base.py:2160] 2023-02-12 18:52:21,823 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-500/tokenizer_config.json\n",
|
||
"[INFO|tokenization_utils_base.py:2167] 2023-02-12 18:52:21,823 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-500/special_tokens_map.json\n",
|
||
"{'loss': 0.3843, 'learning_rate': 8.612440191387561e-07, 'epoch': 4.78}\n",
|
||
" 96% 1000/1045 [07:46<00:20, 2.15it/s][INFO|trainer.py:2709] 2023-02-12 18:56:17,122 >> Saving model checkpoint to out/imdb-5k/gpt2/checkpoint-1000\n",
|
||
"[INFO|configuration_utils.py:453] 2023-02-12 18:56:17,123 >> Configuration saved in out/imdb-5k/gpt2/checkpoint-1000/config.json\n",
|
||
"[INFO|modeling_utils.py:1704] 2023-02-12 18:56:18,817 >> Model weights saved in out/imdb-5k/gpt2/checkpoint-1000/pytorch_model.bin\n",
|
||
"[INFO|tokenization_utils_base.py:2160] 2023-02-12 18:56:18,817 >> tokenizer config file saved in out/imdb-5k/gpt2/checkpoint-1000/tokenizer_config.json\n",
|
||
"[INFO|tokenization_utils_base.py:2167] 2023-02-12 18:56:18,818 >> Special tokens file saved in out/imdb-5k/gpt2/checkpoint-1000/special_tokens_map.json\n",
|
||
"100% 1045/1045 [08:10<00:00, 2.65it/s][INFO|trainer.py:1901] 2023-02-12 18:56:41,796 >> \n",
|
||
"\n",
|
||
"Training completed. Do not forget to share your model on huggingface.co/models =)\n",
|
||
"\n",
|
||
"\n",
|
||
"{'train_runtime': 490.8844, 'train_samples_per_second': 50.918, 'train_steps_per_second': 2.129, 'train_loss': 0.689463275015069, 'epoch': 5.0}\n",
|
||
"100% 1045/1045 [08:10<00:00, 2.13it/s]\n",
|
||
"[INFO|trainer.py:2709] 2023-02-12 18:56:41,814 >> Saving model checkpoint to out/imdb-5k/gpt2\n",
|
||
"[INFO|configuration_utils.py:453] 2023-02-12 18:56:41,815 >> Configuration saved in out/imdb-5k/gpt2/config.json\n",
|
||
"[INFO|modeling_utils.py:1704] 2023-02-12 18:56:43,512 >> Model weights saved in out/imdb-5k/gpt2/pytorch_model.bin\n",
|
||
"[INFO|tokenization_utils_base.py:2160] 2023-02-12 18:56:43,513 >> tokenizer config file saved in out/imdb-5k/gpt2/tokenizer_config.json\n",
|
||
"[INFO|tokenization_utils_base.py:2167] 2023-02-12 18:56:43,513 >> Special tokens file saved in out/imdb-5k/gpt2/special_tokens_map.json\n",
|
||
"***** train metrics *****\n",
|
||
" epoch = 5.0\n",
|
||
" train_loss = 0.6895\n",
|
||
" train_runtime = 0:08:10.88\n",
|
||
" train_samples = 4999\n",
|
||
" train_samples_per_second = 50.918\n",
|
||
" train_steps_per_second = 2.129\n",
|
||
"INFO:__main__:*** Evaluate ***\n",
|
||
"[INFO|trainer.py:710] 2023-02-12 18:56:43,641 >> The following columns in the evaluation set don't have a corresponding argument in `GPT2ForSequenceClassificationCustom.forward` and have been ignored: text. If text are not expected by `GPT2ForSequenceClassificationCustom.forward`, you can safely ignore this message.\n",
|
||
"[INFO|trainer.py:2964] 2023-02-12 18:56:43,642 >> ***** Running Evaluation *****\n",
|
||
"[INFO|trainer.py:2966] 2023-02-12 18:56:43,642 >> Num examples = 1274\n",
|
||
"[INFO|trainer.py:2969] 2023-02-12 18:56:43,642 >> Batch size = 24\n",
|
||
"100% 54/54 [00:09<00:00, 5.50it/s]\n",
|
||
"***** eval metrics *****\n",
|
||
" epoch = 5.0\n",
|
||
" eval_accuracy = 0.9231\n",
|
||
" eval_loss = 0.2178\n",
|
||
" eval_runtime = 0:00:10.05\n",
|
||
" eval_samples = 1274\n",
|
||
" eval_samples_per_second = 126.717\n",
|
||
" eval_steps_per_second = 5.371\n",
|
||
"INFO:__main__:*** Predict ***\n",
|
||
"[INFO|trainer.py:710] 2023-02-12 18:56:53,699 >> The following columns in the test set don't have a corresponding argument in `GPT2ForSequenceClassificationCustom.forward` and have been ignored: text. If text are not expected by `GPT2ForSequenceClassificationCustom.forward`, you can safely ignore this message.\n",
|
||
"[INFO|trainer.py:2964] 2023-02-12 18:56:53,701 >> ***** Running Prediction *****\n",
|
||
"[INFO|trainer.py:2966] 2023-02-12 18:56:53,701 >> Num examples = 1278\n",
|
||
"[INFO|trainer.py:2969] 2023-02-12 18:56:53,701 >> Batch size = 24\n",
|
||
"100% 54/54 [00:09<00:00, 5.49it/s]\n",
|
||
"INFO:__main__:***** Predict results None *****\n",
|
||
"[INFO|modelcard.py:449] 2023-02-12 18:57:03,752 >> Dropping the following result as it does not have all the necessary fields:\n",
|
||
"{'task': {'name': 'Text Classification', 'type': 'text-classification'}, 'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.9230769276618958}]}\n"
|
||
]
|
||
}
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"source": [
|
||
"CUDA_LAUNCH_BLOCKING=1"
|
||
],
|
||
"metadata": {
|
||
"id": "vTup03PZl1IO"
|
||
},
|
||
"execution_count": null,
|
||
"outputs": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 1000
|
||
},
|
||
"id": "Wvhv6_uyymcs",
|
||
"outputId": "4c5cb0b8-e8fc-49bb-c1db-cfd3e21fd7ee"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"output_type": "stream",
|
||
"name": "stderr",
|
||
"text": [
|
||
"loading file vocab.json from cache at /root/.cache/huggingface/hub/models--microsoft--DialogRPT-updown/snapshots/afe1247fd7e1b3abea28a52ea72db4ce1c8d2186/vocab.json\n",
|
||
"loading file merges.txt from cache at /root/.cache/huggingface/hub/models--microsoft--DialogRPT-updown/snapshots/afe1247fd7e1b3abea28a52ea72db4ce1c8d2186/merges.txt\n",
|
||
"loading file added_tokens.json from cache at None\n",
|
||
"loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--microsoft--DialogRPT-updown/snapshots/afe1247fd7e1b3abea28a52ea72db4ce1c8d2186/special_tokens_map.json\n",
|
||
"loading file tokenizer_config.json from cache at None\n",
|
||
"loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--microsoft--DialogRPT-updown/snapshots/afe1247fd7e1b3abea28a52ea72db4ce1c8d2186/config.json\n",
|
||
"Model config GPT2Config {\n",
|
||
" \"_name_or_path\": \"microsoft/DialogRPT-updown\",\n",
|
||
" \"activation_function\": \"gelu_new\",\n",
|
||
" \"architectures\": [\n",
|
||
" \"GPT2ForSequenceClassification\"\n",
|
||
" ],\n",
|
||
" \"attn_pdrop\": 0.1,\n",
|
||
" \"bos_token_id\": 50256,\n",
|
||
" \"embd_pdrop\": 0.1,\n",
|
||
" \"eos_token_id\": 50256,\n",
|
||
" \"id2label\": {\n",
|
||
" \"0\": \"LABEL_0\"\n",
|
||
" },\n",
|
||
" \"initializer_range\": 0.02,\n",
|
||
" \"label2id\": {\n",
|
||
" \"LABEL_0\": 0\n",
|
||
" },\n",
|
||
" \"layer_norm_epsilon\": 1e-05,\n",
|
||
" \"model_type\": \"gpt2\",\n",
|
||
" \"n_ctx\": 1024,\n",
|
||
" \"n_embd\": 1024,\n",
|
||
" \"n_head\": 16,\n",
|
||
" \"n_inner\": null,\n",
|
||
" \"n_layer\": 24,\n",
|
||
" \"n_positions\": 1024,\n",
|
||
" \"n_special\": 0,\n",
|
||
" \"pad_token_id\": 50256,\n",
|
||
" \"predict_special_tokens\": true,\n",
|
||
" \"reorder_and_upcast_attn\": false,\n",
|
||
" \"resid_pdrop\": 0.1,\n",
|
||
" \"scale_attn_by_inverse_layer_idx\": false,\n",
|
||
" \"scale_attn_weights\": true,\n",
|
||
" \"summary_activation\": null,\n",
|
||
" \"summary_first_dropout\": 0.1,\n",
|
||
" \"summary_proj_to_labels\": true,\n",
|
||
" \"summary_type\": \"cls_index\",\n",
|
||
" \"summary_use_proj\": true,\n",
|
||
" \"task_specific_params\": {\n",
|
||
" \"text-generation\": {\n",
|
||
" \"do_sample\": true,\n",
|
||
" \"max_length\": 50\n",
|
||
" }\n",
|
||
" },\n",
|
||
" \"transformers_version\": \"4.26.1\",\n",
|
||
" \"use_cache\": true,\n",
|
||
" \"vocab_size\": 50257\n",
|
||
"}\n",
|
||
"\n",
|
||
"Assigning [PAD] to the pad_token key of the tokenizer\n",
|
||
"Adding [PAD] to the vocabulary\n",
|
||
"loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--microsoft--DialogRPT-updown/snapshots/afe1247fd7e1b3abea28a52ea72db4ce1c8d2186/config.json\n",
|
||
"Model config GPT2Config {\n",
|
||
" \"activation_function\": \"gelu_new\",\n",
|
||
" \"architectures\": [\n",
|
||
" \"GPT2ForSequenceClassification\"\n",
|
||
" ],\n",
|
||
" \"attn_pdrop\": 0.1,\n",
|
||
" \"bos_token_id\": 50256,\n",
|
||
" \"embd_pdrop\": 0.1,\n",
|
||
" \"eos_token_id\": 50256,\n",
|
||
" \"id2label\": {\n",
|
||
" \"0\": \"LABEL_0\",\n",
|
||
" \"1\": \"LABEL_1\",\n",
|
||
" \"2\": \"LABEL_2\",\n",
|
||
" \"3\": \"LABEL_3\",\n",
|
||
" \"4\": \"LABEL_4\",\n",
|
||
" \"5\": \"LABEL_5\"\n",
|
||
" },\n",
|
||
" \"initializer_range\": 0.02,\n",
|
||
" \"label2id\": {\n",
|
||
" \"LABEL_0\": 0,\n",
|
||
" \"LABEL_1\": 1,\n",
|
||
" \"LABEL_2\": 2,\n",
|
||
" \"LABEL_3\": 3,\n",
|
||
" \"LABEL_4\": 4,\n",
|
||
" \"LABEL_5\": 5\n",
|
||
" },\n",
|
||
" \"layer_norm_epsilon\": 1e-05,\n",
|
||
" \"model_type\": \"gpt2\",\n",
|
||
" \"n_ctx\": 1024,\n",
|
||
" \"n_embd\": 1024,\n",
|
||
" \"n_head\": 16,\n",
|
||
" \"n_inner\": null,\n",
|
||
" \"n_layer\": 24,\n",
|
||
" \"n_positions\": 1024,\n",
|
||
" \"n_special\": 0,\n",
|
||
" \"pad_token_id\": 50256,\n",
|
||
" \"predict_special_tokens\": true,\n",
|
||
" \"reorder_and_upcast_attn\": false,\n",
|
||
" \"resid_pdrop\": 0.1,\n",
|
||
" \"scale_attn_by_inverse_layer_idx\": false,\n",
|
||
" \"scale_attn_weights\": true,\n",
|
||
" \"summary_activation\": null,\n",
|
||
" \"summary_first_dropout\": 0.1,\n",
|
||
" \"summary_proj_to_labels\": true,\n",
|
||
" \"summary_type\": \"cls_index\",\n",
|
||
" \"summary_use_proj\": true,\n",
|
||
" \"task_specific_params\": {\n",
|
||
" \"text-generation\": {\n",
|
||
" \"do_sample\": true,\n",
|
||
" \"max_length\": 50\n",
|
||
" }\n",
|
||
" },\n",
|
||
" \"transformers_version\": \"4.26.1\",\n",
|
||
" \"use_cache\": true,\n",
|
||
" \"vocab_size\": 50257\n",
|
||
"}\n",
|
||
"\n",
|
||
"loading weights file pytorch_model.bin from cache at /root/.cache/huggingface/hub/models--microsoft--DialogRPT-updown/snapshots/afe1247fd7e1b3abea28a52ea72db4ce1c8d2186/pytorch_model.bin\n",
|
||
"All model checkpoint weights were used when initializing GPT2ForSequenceClassification.\n",
|
||
"\n",
|
||
"Some weights of GPT2ForSequenceClassification were not initialized from the model checkpoint at microsoft/DialogRPT-updown and are newly initialized because the shapes did not match:\n",
|
||
"- score.weight: found shape torch.Size([1, 1024]) in the checkpoint and torch.Size([6, 1024]) in the model instantiated\n",
|
||
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
|
||
]
|
||
},
|
||
{
|
||
"output_type": "error",
|
||
"ename": "RuntimeError",
|
||
"evalue": "ignored",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
|
||
"\u001b[0;32m<ipython-input-4-1d5e45df897c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGPT2ForSequenceClassification\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"microsoft/DialogRPT-updown\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_labels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_mismatched_sizes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mtokenization\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatched_text\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36mcuda\u001b[0;34m(self, device)\u001b[0m\n\u001b[1;32m 747\u001b[0m \u001b[0mModule\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 748\u001b[0m \"\"\"\n\u001b[0;32m--> 749\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 750\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 751\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mipu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mUnion\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_apply\u001b[0;34m(self, fn)\u001b[0m\n\u001b[1;32m 639\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_apply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 640\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mmodule\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchildren\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 641\u001b[0;31m \u001b[0mmodule\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 643\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompute_should_use_set_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtensor_applied\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_apply\u001b[0;34m(self, fn)\u001b[0m\n\u001b[1;32m 639\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_apply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 640\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mmodule\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchildren\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 641\u001b[0;31m \u001b[0mmodule\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 642\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 643\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompute_should_use_set_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtensor_applied\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m_apply\u001b[0;34m(self, fn)\u001b[0m\n\u001b[1;32m 662\u001b[0m \u001b[0;31m# `with torch.no_grad():`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 663\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mno_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 664\u001b[0;31m \u001b[0mparam_applied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparam\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 665\u001b[0m \u001b[0mshould_use_set_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompute_should_use_set_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparam\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparam_applied\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 666\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mshould_use_set_data\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;32m/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(t)\u001b[0m\n\u001b[1;32m 747\u001b[0m \u001b[0mModule\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 748\u001b[0m \"\"\"\n\u001b[0;32m--> 749\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_apply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 750\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 751\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mipu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mUnion\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdevice\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||
"\u001b[0;31mRuntimeError\u001b[0m: CUDA error: device-side assert triggered\nCUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1."
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from transformers import GPT2Config, GPT2Tokenizer, GPT2Model, Trainer, TrainingArguments, GPT2ForSequenceClassification\n",
|
||
"from datasets import load_dataset\n",
|
||
"import torch\n",
|
||
"from sklearn.metrics import accuracy_score, precision_recall_fscore_support\n",
|
||
"\n",
|
||
"config=GPT2Config(vocab_size=2048, num_labels=6)\n",
|
||
"tokenizer = GPT2Tokenizer.from_pretrained('gpt2')\n",
|
||
"tokenizer.add_special_tokens({'pad_token': '[PAD]'})\n",
|
||
"\n",
|
||
"model = GPT2ForSequenceClassification(config).from_pretrained('gpt2', num_labels=6)\n",
|
||
"model.cuda()\n",
|
||
"\n",
|
||
"def tokenization(batched_text):\n",
|
||
" return tokenizer(batched_text['text'], return_tensors='pt', padding=True)\n",
|
||
"\n",
|
||
"def compute_metrics(pred):\n",
|
||
" labels = pred.label_ids\n",
|
||
" preds = pred.predictions.argmax(-1)\n",
|
||
" precision, recall, f1, _ = precision_recall_fscore_support(labels, preds, average='micro')\n",
|
||
" acc = accuracy_score(labels, preds)\n",
|
||
" return {\n",
|
||
" 'accuracy': acc,\n",
|
||
" 'f1': f1,\n",
|
||
" 'precision': precision,\n",
|
||
" 'recall': recall\n",
|
||
" }\n",
|
||
"\n",
|
||
"\n",
|
||
"dataset = load_dataset(\"emotion\")\n",
|
||
"\n",
|
||
"train_data= dataset[\"train\"]\n",
|
||
"test_data = dataset[\"test\"]\n",
|
||
"eval_data = dataset[\"validation\"]\n",
|
||
"\n",
|
||
"train_data = train_data.map(tokenization, batched=True, batch_size=len(train_data))\n",
|
||
"eval_data = eval_data.map(tokenization, batched=True, batch_size=len(eval_data))\n",
|
||
"\n",
|
||
"train_data.set_format('torch', columns=['input_ids', 'attention_mask', 'label'])\n",
|
||
"eval_data.set_format('torch', columns=['input_ids', 'attention_mask', 'label'])\n",
|
||
"\n",
|
||
"\n",
|
||
"training_args = TrainingArguments(\n",
|
||
" output_dir=\"./output\",\n",
|
||
" num_train_epochs=3,\n",
|
||
" per_device_train_batch_size = 8,\n",
|
||
" gradient_accumulation_steps = 16, \n",
|
||
" per_device_eval_batch_size= 8,\n",
|
||
" evaluation_strategy = \"epoch\",\n",
|
||
" save_strategy = \"epoch\",\n",
|
||
" disable_tqdm = False, \n",
|
||
" load_best_model_at_end=True,\n",
|
||
" warmup_steps=10,\n",
|
||
" weight_decay=0.01,\n",
|
||
" logging_steps = 4,\n",
|
||
" fp16 = True,\n",
|
||
" dataloader_num_workers = 2,\n",
|
||
" run_name = 'gpt-2-classification'\n",
|
||
")\n",
|
||
"\n",
|
||
"trainer = Trainer(\n",
|
||
" model=model,\n",
|
||
" args=training_args,\n",
|
||
" compute_metrics=compute_metrics,\n",
|
||
" train_dataset=train_data,\n",
|
||
" eval_dataset=eval_data,\n",
|
||
"\n",
|
||
")\n",
|
||
"\n",
|
||
"trainer.train()\n",
|
||
"i = 0\n",
|
||
"sum_preds = 0\n",
|
||
"model = model.to('cpu')\n",
|
||
"for line in test_data:\n",
|
||
"\n",
|
||
" inputs = tokenizer(line.get('text'), return_tensors=\"pt\")\n",
|
||
" labels = torch.tensor([1]).unsqueeze(0) # Batch size 1\n",
|
||
" outputs = model(**inputs, labels=labels)\n",
|
||
" _, predictions = torch.max(outputs[1], 1)\n",
|
||
" a = int(predictions.int())\n",
|
||
" b = line.get('label')\n",
|
||
" print(i)\n",
|
||
" i += 1\n",
|
||
" sum_preds += int(a == b)\n",
|
||
"\n",
|
||
"print(f\"ACCURACY: {(sum_preds/i * 100)}\")"
|
||
]
|
||
}
|
||
]
|
||
} |