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  1. .config/.last_opt_in_prompt.yaml +1 -0
  2. .config/.last_survey_prompt.yaml +1 -0
  3. .config/.last_update_check.json +1 -0
  4. .config/active_config +1 -0
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  10. .config/logs/2026.04.16/13.27.28.140888.log +788 -0
  11. .config/logs/2026.04.16/13.27.53.684484.log +5 -0
  12. .config/logs/2026.04.16/13.28.05.189231.log +164 -0
  13. .config/logs/2026.04.16/13.28.06.952902.log +5 -0
  14. .config/logs/2026.04.16/13.28.21.827521.log +8 -0
  15. .config/logs/2026.04.16/13.28.22.950479.log +8 -0
  16. .gitattributes +3 -0
  17. MLOps_Assignment2.pdf +3 -0
  18. __pycache__/data.cpython-312.pyc +0 -0
  19. __pycache__/train.cpython-312.pyc +0 -0
  20. __pycache__/utils.cpython-312.pyc +0 -0
  21. data.py +45 -0
  22. eval.py +13 -0
  23. sample_data/README.md +19 -0
  24. sample_data/anscombe.json +49 -0
  25. sample_data/california_housing_test.csv +0 -0
  26. sample_data/california_housing_train.csv +0 -0
  27. sample_data/mnist_test.csv +3 -0
  28. sample_data/mnist_train_small.csv +3 -0
  29. train.py +44 -0
  30. utils.py +21 -0
  31. wandb/debug-internal.log +112 -0
  32. wandb/debug.log +24 -0
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  40. wandb/run-20260506_073538-3bm8fy2p/logs/debug.log +24 -0
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+ 2026-04-16 13:27:43,516 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
497
+
498
+ 2026-04-16 13:27:43,516 INFO ___FILE_ONLY___ ╠═ Downloading: gcloud cli dependencies (Platform Specific) ═╣
499
+
500
+ 2026-04-16 13:27:43,516 INFO ___FILE_ONLY___ ╚
501
+ 2026-04-16 13:27:43,518 DEBUG root On GCE from memory cache: False
502
+ 2026-04-16 13:27:43,519 DEBUG root On GCE from memory cache: False
503
+ 2026-04-16 13:27:43,521 DEBUG urllib3.connectionpool Starting new HTTPS connection (1): dl.google.com:443
504
+ 2026-04-16 13:27:43,595 DEBUG urllib3.connectionpool https://dl.google.com:443 "GET /dl/cloudsdk/channels/rapid/components/google-cloud-sdk-gcloud-deps-linux-x86_64-20210416153011.tar.gz HTTP/1.1" 200 104
505
+ 2026-04-16 13:27:43,596 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
506
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507
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509
+
510
+ 2026-04-16 13:27:43,599 INFO ___FILE_ONLY___ ╠═ Installing: BigQuery Command Line Tool ═╣
511
+
512
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513
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515
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563
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564
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565
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566
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567
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569
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570
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571
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572
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573
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574
+
575
+ 2026-04-16 13:27:44,060 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
576
+
577
+ 2026-04-16 13:27:44,060 INFO ___FILE_ONLY___ ╠═ Installing: BigQuery Command Line Tool (Platform Spec... ═╣
578
+
579
+ 2026-04-16 13:27:44,060 INFO ___FILE_ONLY___ ╚
580
+ 2026-04-16 13:27:44,061 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
581
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582
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583
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584
+
585
+ 2026-04-16 13:27:44,072 INFO ___FILE_ONLY___ ╠═ Installing: Bundled Python 3.13 ═╣
586
+
587
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588
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589
+ 2026-04-16 13:27:44,080 INFO ___FILE_ONLY___ ╝
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+
591
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592
+
593
+ 2026-04-16 13:27:44,083 INFO ___FILE_ONLY___ ╠═ Installing: Bundled Python 3.13 (Platform Specific) ═╣
594
+
595
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596
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599
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625
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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639
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640
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
+ 2026-04-16 13:27:51,518 INFO ___FILE_ONLY___ ╝
657
+
658
+ 2026-04-16 13:27:51,592 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
659
+
660
+ 2026-04-16 13:27:51,592 INFO ___FILE_ONLY___ ╠═ Installing: Cloud Storage Command Line Tool ═╣
661
+
662
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663
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714
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715
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716
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718
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719
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721
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722
+ 2026-04-16 13:27:53,002 INFO ___FILE_ONLY___ ═
723
+ 2026-04-16 13:27:53,003 INFO ___FILE_ONLY___ ╝
724
+
725
+ 2026-04-16 13:27:53,035 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
726
+
727
+ 2026-04-16 13:27:53,035 INFO ___FILE_ONLY___ ╠═ Installing: Cloud Storage Command Line Tool (Platform... ═╣
728
+
729
+ 2026-04-16 13:27:53,035 INFO ___FILE_ONLY___ ╚
730
+ 2026-04-16 13:27:53,036 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
731
+ 2026-04-16 13:27:53,036 INFO ___FILE_ONLY___ ╝
732
+
733
+ 2026-04-16 13:27:53,041 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
734
+
735
+ 2026-04-16 13:27:53,041 INFO ___FILE_ONLY___ ╠═ Installing: Default set of gcloud commands ═╣
736
+
737
+ 2026-04-16 13:27:53,041 INFO ___FILE_ONLY___ ╚
738
+ 2026-04-16 13:27:53,043 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
739
+ 2026-04-16 13:27:53,044 INFO ___FILE_ONLY___ ╝
740
+
741
+ 2026-04-16 13:27:53,045 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
742
+
743
+ 2026-04-16 13:27:53,046 INFO ___FILE_ONLY___ ╠═ Installing: Google Cloud CLI Core Libraries (Platform... ═╣
744
+
745
+ 2026-04-16 13:27:53,046 INFO ___FILE_ONLY___ ╚
746
+ 2026-04-16 13:27:53,047 INFO ___FILE_ONLY___ ══════════════════════════════
747
+ 2026-04-16 13:27:53,047 INFO ___FILE_ONLY___ ══════════════════════════════
748
+ 2026-04-16 13:27:53,047 INFO ___FILE_ONLY___ ╝
749
+
750
+ 2026-04-16 13:27:53,052 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
751
+
752
+ 2026-04-16 13:27:53,052 INFO ___FILE_ONLY___ ╠═ Installing: Google Cloud CRC32C Hash Tool ═╣
753
+
754
+ 2026-04-16 13:27:53,052 INFO ___FILE_ONLY___ ╚
755
+ 2026-04-16 13:27:53,055 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
756
+ 2026-04-16 13:27:53,055 INFO ___FILE_ONLY___ ╝
757
+
758
+ 2026-04-16 13:27:53,057 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
759
+
760
+ 2026-04-16 13:27:53,057 INFO ___FILE_ONLY___ ╠═ Installing: Google Cloud CRC32C Hash Tool (Platform S... ═╣
761
+
762
+ 2026-04-16 13:27:53,057 INFO ___FILE_ONLY___ ╚
763
+ 2026-04-16 13:27:53,096 INFO ___FILE_ONLY___ ══════════════════════════════
764
+ 2026-04-16 13:27:53,096 INFO ___FILE_ONLY___ ══════════════════════════════
765
+ 2026-04-16 13:27:53,096 INFO ___FILE_ONLY___ ╝
766
+
767
+ 2026-04-16 13:27:53,101 INFO ___FILE_ONLY___ ╔════════════════════════════════════════════════════════════╗
768
+
769
+ 2026-04-16 13:27:53,102 INFO ___FILE_ONLY___ ╠═ Installing: gcloud cli dependencies (Platform Specific) ═╣
770
+
771
+ 2026-04-16 13:27:53,102 INFO ___FILE_ONLY___ ╚
772
+ 2026-04-16 13:27:53,102 INFO ___FILE_ONLY___ ════════════════════════════════════════════════════════════
773
+ 2026-04-16 13:27:53,102 INFO ___FILE_ONLY___ ╝
774
+
775
+ 2026-04-16 13:27:53,107 DEBUG root Updating notification cache...
776
+ 2026-04-16 13:27:53,108 INFO ___FILE_ONLY___
777
+
778
+ 2026-04-16 13:27:53,109 INFO ___FILE_ONLY___ Performing post processing steps...
779
+ 2026-04-16 13:27:53,110 DEBUG root Executing command: ['/tools/google-cloud-sdk/bin/gcloud', 'components', 'post-process']
780
+ 2026-04-16 13:28:04,270 DEBUG ___FILE_ONLY___
781
+ 2026-04-16 13:28:04,270 DEBUG ___FILE_ONLY___
782
+ 2026-04-16 13:28:04,401 INFO root descriptor_list: [{'universeDomain': 'googleapis.com', 'universeShortName': '', 'authenticationDomain': 'auth.cloud.google.com', 'projectPrefix': '', 'cloudWebDomain': 'cloud.google.com', 'documentationDomain': 'cloud.google.com', 'version': '1.0.0', 'state': 'primary', 'artifactRegistryDomain': 'pkg.dev'}]
783
+ 2026-04-16 13:28:04,402 INFO ___FILE_ONLY___
784
+ Update done!
785
+
786
+
787
+ 2026-04-16 13:28:04,404 DEBUG root Chosen display Format:none
788
+ 2026-04-16 13:28:04,405 INFO root Display format: "none"
.config/logs/2026.04.16/13.27.53.684484.log ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ 2026-04-16 13:27:53,685 DEBUG root Loaded Command Group: ['gcloud', 'components']
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+ 2026-04-16 13:28:20,702 INFO ___FILE_ONLY___
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+ Update done!
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.gitattributes CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
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35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ MLOps_Assignment2.pdf filter=lfs diff=lfs merge=lfs -text
37
+ sample_data/mnist_test.csv filter=lfs diff=lfs merge=lfs -text
38
+ sample_data/mnist_train_small.csv filter=lfs diff=lfs merge=lfs -text
MLOps_Assignment2.pdf ADDED
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+ oid sha256:aca3a59f730c037160c563d3ac8ea1e0da8ca31b48f18ce62aeb2db4eb19c2af
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+ size 397149
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data.py ADDED
@@ -0,0 +1,45 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+ import gzip
3
+ import random
4
+ import requests
5
+ from transformers import DistilBertTokenizerFast
6
+
7
+ genre_url_dict = {
8
+ 'poetry': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_poetry.json.gz',
9
+ 'children': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_children.json.gz',
10
+ 'comics_graphic': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_comics_graphic.json.gz',
11
+ 'fantasy_paranormal': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_fantasy_paranormal.json.gz',
12
+ 'history_biography': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_history_biography.json.gz',
13
+ 'mystery_thriller_crime': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_mystery_thriller_crime.json.gz',
14
+ 'romance': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_romance.json.gz',
15
+ 'young_adult': 'https://mcauleylab.ucsd.edu/public_datasets/gdrive/goodreads/byGenre/goodreads_reviews_young_adult.json.gz'
16
+ }
17
+
18
+ def load_reviews(url, head=10000, sample_size=2000):
19
+ reviews = []
20
+ response = requests.get(url, stream=True)
21
+ with gzip.open(response.raw, 'rt', encoding='utf-8') as file:
22
+ for i, line in enumerate(file):
23
+ if i >= head: break
24
+ reviews.append(json.loads(line)['review_text'])
25
+ return random.sample(reviews, min(sample_size, len(reviews)))
26
+
27
+ def prepare_data(model_name='distilbert-base-cased'):
28
+ tokenizer = DistilBertTokenizerFast.from_pretrained(model_name)
29
+ train_texts, train_labels, test_texts, test_labels = [], [], [], []
30
+
31
+ for genre, url in genre_url_dict.items():
32
+ reviews = load_reviews(url, head=1000, sample_size=200)
33
+ split = int(len(reviews) * 0.8)
34
+ train_texts.extend(reviews[:split])
35
+ train_labels.extend([genre] * split)
36
+ test_texts.extend(reviews[split:])
37
+ test_labels.extend([genre] * (len(reviews) - split))
38
+
39
+ unique_labels = sorted(list(set(train_labels)))
40
+ label2id = {label: i for i, label in enumerate(unique_labels)}
41
+
42
+ train_encodings = tokenizer(train_texts, truncation=True, padding=True, max_length=512)
43
+ test_encodings = tokenizer(test_texts, truncation=True, padding=True, max_length=512)
44
+
45
+ return train_encodings, [label2id[l] for l in train_labels], test_encodings, [label2id[l] for l in test_labels], label2id
eval.py ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from transformers import DistilBertForSequenceClassification, Trainer
2
+ from train import train_model
3
+
4
+ def evaluate():
5
+ # In a real pipeline, we'd load the saved model
6
+ trainer, test_dataset = train_model()
7
+ results = trainer.evaluate()
8
+ print(results)
9
+ with open('results.txt', 'w') as f:
10
+ f.write(str(results))
11
+
12
+ if __name__ == '__main__':
13
+ evaluate()
sample_data/README.md ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ This directory includes a few sample datasets to get you started.
2
+
3
+ * `california_housing_data*.csv` is California housing data from the 1990 US
4
+ Census; more information is available at:
5
+ https://docs.google.com/document/d/e/2PACX-1vRhYtsvc5eOR2FWNCwaBiKL6suIOrxJig8LcSBbmCbyYsayia_DvPOOBlXZ4CAlQ5nlDD8kTaIDRwrN/pub
6
+
7
+ * `mnist_*.csv` is a small sample of the
8
+ [MNIST database](https://en.wikipedia.org/wiki/MNIST_database), which is
9
+ described at: http://yann.lecun.com/exdb/mnist/
10
+
11
+ * `anscombe.json` contains a copy of
12
+ [Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet); it
13
+ was originally described in
14
+
15
+ Anscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American
16
+ Statistician. 27 (1): 17-21. JSTOR 2682899.
17
+
18
+ and our copy was prepared by the
19
+ [vega_datasets library](https://github.com/altair-viz/vega_datasets/blob/4f67bdaad10f45e3549984e17e1b3088c731503d/vega_datasets/_data/anscombe.json).
sample_data/anscombe.json ADDED
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train.py ADDED
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+ import os
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+ from transformers import DistilBertForSequenceClassification, Trainer, TrainingArguments
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+ from data import prepare_data
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+ from utils import MyDataset, compute_metrics
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+
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+ def train_model():
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+ # Task 3: Load Pre-trained model
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+ train_enc, train_lab, test_enc, test_lab, label2id = prepare_data()
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+ train_dataset = MyDataset(train_enc, train_lab)
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+ test_dataset = MyDataset(test_enc, test_lab)
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+
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+ model = DistilBertForSequenceClassification.from_pretrained(
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+ 'distilbert-base-cased',
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+ num_labels=len(label2id)
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+ )
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+
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+ # Task 4: W&B Experiment Tracking
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+ training_args = TrainingArguments(
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+ output_dir='mlops-assignment2-model',
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+ num_train_epochs=1,
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+ per_device_train_batch_size=16,
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+ logging_dir='./logs',
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+ logging_steps=10,
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+ eval_strategy='steps',
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+ push_to_hub=True, # Task 5: Hub Deployment
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+ hub_model_id='mlops-assignment2-distilbert',
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+ hub_strategy='every_save'
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+ )
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+
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+ trainer = Trainer(
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+ model=model,
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+ args=training_args,
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+ train_dataset=train_dataset,
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+ eval_dataset=test_dataset,
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+ compute_metrics=compute_metrics
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+ )
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+
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+ trainer.train()
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+ trainer.push_to_hub()
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+ return trainer, test_dataset
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+
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+ if __name__ == '__main__':
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+ train_model()
utils.py ADDED
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+ import torch
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+ from sklearn.metrics import accuracy_score
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+
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+ class MyDataset(torch.utils.data.Dataset):
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+ def __init__(self, encodings, labels):
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+ self.encodings = encodings
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+ self.labels = labels
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+
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+ def __getitem__(self, idx):
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+ item['labels'] = torch.tensor(self.labels[idx])
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+ return item
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+
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+ def __len__(self):
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+ return len(self.labels)
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+
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+ def compute_metrics(pred):
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+ labels = pred.label_ids
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+ preds = pred.predictions.argmax(-1)
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+ acc = accuracy_score(labels, preds)
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+ return {'accuracy': acc}
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+ super().__init__(loader)
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+ File "/content/eval.py", line 13, in <module>
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+ evaluate()
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+ File "/content/eval.py", line 6, in evaluate
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+ trainer, test_dataset = train_model()
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+ ^^^^^^^^^^^^^
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+ File "/content/train.py", line 39, in train_model
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+ File "/usr/local/lib/python3.12/dist-packages/transformers/trainer.py", line 2165, in train
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+ ^^^^^^^^^^^^^^^^^^^^
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+ File "/usr/local/lib/python3.12/dist-packages/transformers/trainer.py", line 2536, in _inner_training_loop
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+ tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
16
+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
17
+ File "/usr/local/lib/python3.12/dist-packages/transformers/trainer.py", line 3837, in training_step
18
+ self.accelerator.backward(loss, **kwargs)
19
+ File "/usr/local/lib/python3.12/dist-packages/accelerate/accelerator.py", line 2838, in backward
20
+ loss.backward(**kwargs)
21
+ File "/usr/local/lib/python3.12/dist-packages/torch/_tensor.py", line 630, in backward
22
+ torch.autograd.backward(
23
+ File "/usr/local/lib/python3.12/dist-packages/torch/autograd/__init__.py", line 364, in backward
24
+ _engine_run_backward(
25
+ File "/usr/local/lib/python3.12/dist-packages/torch/autograd/graph.py", line 865, in _engine_run_backward
26
+ return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
27
+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
28
+ KeyboardInterrupt
wandb/run-20260506_073538-3bm8fy2p/files/requirements.txt ADDED
@@ -0,0 +1,685 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ setuptools==75.2.0
2
+ types-setuptools==82.0.0.20260402
3
+ pip==24.1.2
4
+ requirements-parser==0.9.0
5
+ PyPDF2==3.0.1
6
+ google-colab==1.0.0
7
+ future==1.0.0
8
+ annotated-doc==0.0.4
9
+ textblob==0.19.0
10
+ nbformat==5.10.4
11
+ Flask==3.1.3
12
+ requests-oauthlib==2.0.0
13
+ gym==0.25.2
14
+ weasel==1.0.0
15
+ GDAL==3.8.4
16
+ PyDrive2==1.21.3
17
+ ale-py==0.11.2
18
+ gast==0.7.0
19
+ h5netcdf==1.8.1
20
+ deprecation==2.1.0
21
+ srsly==2.5.3
22
+ pydub==0.25.1
23
+ types-pytz==2026.1.1.20260408
24
+ umap-learn==0.5.12
25
+ traittypes==0.2.3
26
+ six==1.17.0
27
+ vega-datasets==0.9.0
28
+ intel-cmplr-lib-ur==2025.3.3
29
+ typing-inspection==0.4.2
30
+ dlib==19.24.6
31
+ scs==3.2.11
32
+ apsw==3.53.0.0
33
+ sse-starlette==3.3.4
34
+ uuid_utils==0.14.1
35
+ toml==0.10.2
36
+ contourpy==1.3.3
37
+ colorlover==0.3.0
38
+ nibabel==5.4.2
39
+ openpyxl==3.1.5
40
+ peewee==4.0.5
41
+ numba==0.60.0
42
+ termcolor==3.3.0
43
+ gcsfs==2025.3.0
44
+ partd==1.4.2
45
+ jax==0.7.2
46
+ xarray-einstats==0.10.0
47
+ spglm==1.1.0
48
+ text-unidecode==1.3
49
+ splot==1.1.7
50
+ PuLP==3.3.0
51
+ torchcodec==0.10.0
52
+ keras-nlp==0.26.0
53
+ torchao==0.10.0
54
+ google-cloud-aiplatform==1.148.1
55
+ pyperclip==1.11.0
56
+ pynndescent==0.6.0
57
+ miniKanren==1.0.5
58
+ iniconfig==2.3.0
59
+ mmh3==5.2.1
60
+ torchsummary==1.5.1
61
+ fastlite==0.2.4
62
+ geopandas==1.1.3
63
+ opentelemetry-exporter-otlp-proto-http==1.38.0
64
+ pandas-datareader==0.10.0
65
+ docutils==0.21.2
66
+ pydotplus==2.0.2
67
+ gradio_client==1.14.0
68
+ pyasn1==0.6.3
69
+ rich==13.9.4
70
+ array_record==0.8.3
71
+ torchtune==0.6.1
72
+ hyperopt==0.2.7
73
+ greenlet==3.4.0
74
+ polars-runtime-32==1.35.2
75
+ dataproc-spark-connect==1.1.0
76
+ rtree==1.4.1
77
+ sphinxcontrib-jsmath==1.0.1
78
+ jupyter-console==6.6.3
79
+ sphinxcontrib-devhelp==2.0.0
80
+ tensorflow==2.20.0
81
+ jupyter_client==7.4.9
82
+ zipp==3.23.1
83
+ typing_extensions==4.15.0
84
+ overrides==7.7.0
85
+ confection==1.3.3
86
+ wandb==0.26.1
87
+ tensorflow-probability==0.25.0
88
+ firebase-admin==6.9.0
89
+ inequality==1.1.2
90
+ spint==1.0.7
91
+ opentelemetry-proto==1.38.0
92
+ defusedxml==0.7.1
93
+ pyomo==6.10.0
94
+ google-cloud-bigtable==2.36.0
95
+ google-auth==2.47.0
96
+ multidict==6.7.1
97
+ cycler==0.12.1
98
+ scipy==1.16.3
99
+ tensorflow-text==2.20.1
100
+ libpysal==4.14.1
101
+ jsonpickle==4.1.1
102
+ fastjsonschema==2.21.2
103
+ matplotlib-inline==0.2.1
104
+ grpc-google-iam-v1==0.14.4
105
+ pyproj==3.7.2
106
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107
+ frozenlist==1.8.0
108
+ sklearn-pandas==2.2.0
109
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110
+ optree==0.19.0
111
+ sphinxcontrib-serializinghtml==2.0.0
112
+ cloudpickle==3.1.2
113
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114
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115
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116
+ mistune==3.2.0
117
+ fiona==1.10.1
118
+ libclang==18.1.1
119
+ anywidget==0.9.21
120
+ python-dotenv==1.2.2
121
+ pysal==25.7
122
+ blobfile==3.2.0
123
+ ormsgpack==1.12.2
124
+ access==1.1.10.post3
125
+ cufflinks==0.17.3
126
+ preshed==3.0.13
127
+ keras==3.13.2
128
+ MarkupSafe==3.0.3
129
+ distro==1.9.0
130
+ peft==0.19.1
131
+ sqlglot==25.20.2
132
+ spacy-loggers==1.0.5
133
+ flax==0.11.2
134
+ tensorboard==2.20.0
135
+ ibis-framework==9.5.0
136
+ python-box==7.4.1
137
+ yellowbrick==1.5
138
+ PySocks==1.7.1
139
+ db-dtypes==1.5.1
140
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141
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142
+ httpx==0.28.1
143
+ jsonschema-specifications==2025.9.1
144
+ google-cloud-secret-manager==2.27.0
145
+ catalogue==2.0.10
146
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147
+ yfinance==0.2.66
148
+ msgpack==1.1.2
149
+ googledrivedownloader==1.1.0
150
+ linkify-it-py==2.1.0
151
+ frozendict==2.4.7
152
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153
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154
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155
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156
+ google-cloud-logging==3.15.0
157
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158
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159
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160
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161
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162
+ google-cloud-core==2.5.1
163
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164
+ murmurhash==1.0.15
165
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166
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167
+ python-snappy==0.7.3
168
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169
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170
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171
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172
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173
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174
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175
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176
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177
+ pytensor==2.38.2
178
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179
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180
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181
+ nltk==3.9.1
182
+ py4j==0.10.9.9
183
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184
+ cligj==0.7.2
185
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186
+ plotly==5.24.1
187
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188
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189
+ pydantic-settings==2.14.0
190
+ python-fasthtml==0.12.50
191
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192
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193
+ ruff==0.15.11
194
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195
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196
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197
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198
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199
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200
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201
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202
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203
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204
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205
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206
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207
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208
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209
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210
+ holidays==0.95
211
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212
+ referencing==0.37.0
213
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214
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215
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216
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217
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218
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219
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220
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221
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222
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223
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224
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225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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236
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237
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238
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239
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240
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241
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242
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243
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244
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245
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246
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247
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248
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249
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250
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251
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252
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253
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254
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255
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256
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257
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258
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259
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260
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261
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262
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263
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264
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265
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266
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267
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268
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269
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270
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271
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272
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273
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274
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275
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276
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277
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278
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279
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280
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281
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282
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283
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284
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285
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286
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287
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288
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289
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290
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291
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292
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293
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294
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295
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296
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297
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298
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299
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300
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301
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302
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303
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304
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305
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306
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307
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308
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309
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310
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311
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312
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313
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314
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315
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316
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317
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318
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319
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320
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321
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322
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323
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324
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325
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326
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327
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328
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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341
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342
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343
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344
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345
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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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360
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361
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362
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363
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364
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365
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366
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367
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368
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369
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370
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371
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372
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373
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374
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375
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376
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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390
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391
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392
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393
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394
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395
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396
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397
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398
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399
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400
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401
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402
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403
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404
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405
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406
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407
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408
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409
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410
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411
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412
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413
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414
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415
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416
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417
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418
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419
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420
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421
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422
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423
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424
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425
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426
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427
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428
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429
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430
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431
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432
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433
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434
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435
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436
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437
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438
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439
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440
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441
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442
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443
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444
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445
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446
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447
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448
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449
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450
+ thinc==8.3.13
451
+ tensorflow-hub==0.16.1
452
+ opencv-python-headless==4.13.0.92
453
+ humanize==4.15.0
454
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455
+ arviz==0.22.0
456
+ wrapt==2.1.2
457
+ pandas==2.2.2
458
+ pycryptodomex==3.23.0
459
+ google-genai==1.68.0
460
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