Repository Analysis

TingsongYu/PyTorch-Tutorial-2nd

《Pytorch实用教程》(第二版)无论是零基础入门,还是CV、NLP、LLM项目应用,或是进阶工程化部署落地,在这里都有。相信在本书的帮助下,读者将能够轻松掌握 PyTorch 的使用,成为一名优秀的深度学习工程师。

7.1 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of TingsongYu/PyTorch-Tutorial-2nd, a Jupyter Notebook project with 4,579 GitHub stars. SynthScan v2.0 examined 206,044 lines of code across 483 source files, recording 1169 pattern matches distributed across 20 syntactic categories. The overall adjusted score of 7.1 places this repository in the Low AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

7.1
Adjusted Score
7.1
Raw Score
100%
Time Factor
2026-08-09
Last Push
4.6K
Stars
Jupyter Notebook
Language
206.0K
Lines of Code
483
Files
1.2K
Pattern Hits
2026-08-09
Scan Date
0.21
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 103MEDIUM 23LOW 1043

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 1169 distinct pattern matches across 20 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Cross-File Repetition94 hits · 470 pts
SeverityFileLineSnippetContext
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HIGHcode/chapter-9/b_seq2seq/utils/my_utils.py0@file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数STRING
HIGHcode/chapter-9/c_transformer/utils/my_utils.py0@file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数STRING
HIGHcode/chapter-8/02_segmentation/utils/utils.py0@file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数STRING
HIGHcode/chapter-8/01_classification/utils/my_utils.py0@file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数STRING
HIGHcode/chapter-6/my_utils.py0@file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数STRING
HIGHcode/chapter-7/my_utils.py0混淆矩阵绘制并保存图片 :param confusion_mat: nd.array :param classes: list or tuple, 类别名称 :param set_name: str, 数据集名称 train or valiSTRING
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HIGHcode/chapter-9/b_seq2seq/utils/my_utils.py0混淆矩阵绘制并保存图片 :param confusion_mat: nd.array :param classes: list or tuple, 类别名称 :param set_name: str, 数据集名称 train or valiSTRING
HIGHcode/chapter-9/c_transformer/utils/my_utils.py0混淆矩阵绘制并保存图片 :param confusion_mat: nd.array :param classes: list or tuple, 类别名称 :param set_name: str, 数据集名称 train or valiSTRING
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HIGHcode/chapter-9/a_rnn_lstm/utils/my_utils.py0computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/masSTRING
HIGHcode/chapter-9/b_seq2seq/utils/my_utils.py0computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/masSTRING
HIGHcode/chapter-9/c_transformer/utils/my_utils.py0computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/masSTRING
HIGHcode/chapter-8/02_segmentation/utils/utils.py0computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/masSTRING
HIGHcode/chapter-8/01_classification/utils/my_utils.py0computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/masSTRING
HIGHcode/chapter-7/my_utils.py0computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/STRING
HIGHcode/chapter-9/a_rnn_lstm/utils/my_utils.py0computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/STRING
HIGHcode/chapter-9/b_seq2seq/utils/my_utils.py0computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/STRING
HIGHcode/chapter-9/c_transformer/utils/my_utils.py0computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/STRING
HIGHcode/chapter-8/02_segmentation/utils/utils.py0computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/STRING
HIGHcode/chapter-8/01_classification/utils/my_utils.py0computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/STRING
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HIGHcode/chapter-11/02_resnet_inference.py0加载标签名 :param p_clsnames: :param p_clsnames_cn: :return:STRING
HIGHcode/chapter-12/a_trt_infer_engine_resnet50.py0加载标签名 :param p_clsnames: :param p_clsnames_cn: :return:STRING
HIGHcode/chapter-12/01_trt_resnet50_cuda.py0加载标签名 :param p_clsnames: :param p_clsnames_cn: :return:STRING
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HIGHcode/chapter-8/01_classification/train_aug.py0@file name : train_script.py @author : tingsongyu https://github.com/tingsongyu @date : 2023-02-04 @brief : 肺炎xray图像分类训练STRING
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HIGHcode/chapter-8/05_cyclegan/models/test_model.py0initialize the cyclegan class. parameters: opt (option class)-- stores all the experiment flags; needs to be a subclass STRING
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HIGHcode/chapter-8/05_cyclegan/models/cycle_gan_model.py0initialize the cyclegan class. parameters: opt (option class)-- stores all the experiment flags; needs to be a subclass STRING
34 more matches not shown…
Over-Commented Block449 hits · 254 pts
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Unused Imports206 hits · 206 pts
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Deep Nesting127 hits · 127 pts
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LOWcode/chapter-9/d_bert/run_ner_softmax.py196CODE
LOWcode/chapter-9/d_bert/tools/common.py280CODE
LOWcode/chapter-9/d_bert/tools/common.py295CODE
LOWcode/chapter-9/d_bert/tools/common.py296CODE
LOWcode/chapter-9/d_bert/processors/utils_ner.py78CODE
LOWcode/chapter-9/d_bert/processors/utils_ner.py122CODE
LOWcode/chapter-9/d_bert/processors/utils_ner.py32CODE
LOWcode/chapter-9/d_bert/processors/utils_ner.py56CODE
LOWcode/chapter-9/d_bert/processors/ner_seq.py181CODE
LOWcode/chapter-9/d_bert/processors/ner_span.py197CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py143CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py301CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py351CODE
LOWcode/chapter-9/d_bert/callback/trainingmonitor.py26CODE
LOWcode/chapter-9/d_bert/callback/optimizater/sgdw.py47CODE
LOWcode/chapter-9/d_bert/callback/optimizater/adafactor.py67CODE
LOWcode/chapter-9/d_bert/callback/optimizater/lars.py45CODE
LOWcode/chapter-9/d_bert/callback/optimizater/radam.py25CODE
LOWcode/chapter-9/d_bert/callback/optimizater/adabound.py52CODE
LOWcode/chapter-9/d_bert/callback/optimizater/ralamb.py20CODE
LOWcode/chapter-9/d_bert/callback/optimizater/lookahead.py80CODE
LOWcode/chapter-9/c_transformer/train_transformer.py148CODE
LOWcode/chapter-8/03_detection/visdrone2yolo.py16CODE
LOW…de/chapter-8/03_detection/yolov5-master/00-save-gif.py54CODE
LOWcode/chapter-8/03_detection/yolov5-master/val.py99CODE
LOWcode/chapter-8/03_detection/yolov5-master/val.py372CODE
LOWcode/chapter-8/03_detection/yolov5-master/train.py70CODE
LOWcode/chapter-8/03_detection/yolov5-master/train.py481CODE
LOWcode/chapter-8/03_detection/yolov5-master/hubconf.py16CODE
LOWcode/chapter-8/03_detection/yolov5-master/detect.py55CODE
LOW…e/chapter-8/03_detection/yolov5-master/classify/val.py45CODE
LOW…apter-8/03_detection/yolov5-master/classify/predict.py56CODE
LOW…chapter-8/03_detection/yolov5-master/classify/train.py56CODE
LOW…de/chapter-8/03_detection/yolov5-master/segment/val.py130CODE
LOW…de/chapter-8/03_detection/yolov5-master/segment/val.py436CODE
LOW…hapter-8/03_detection/yolov5-master/segment/predict.py56CODE
LOW…/chapter-8/03_detection/yolov5-master/segment/train.py69CODE
LOW…/chapter-8/03_detection/yolov5-master/segment/train.py507CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/metrics.py222CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py930CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py990CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py241CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py439CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py750CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py808CODE
LOW…hapter-8/03_detection/yolov5-master/utils/downloads.py84CODE
LOW…de/chapter-8/03_detection/yolov5-master/utils/plots.py230CODE
LOW…de/chapter-8/03_detection/yolov5-master/utils/plots.py514CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py66CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py151CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py212CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py318CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py468CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py506CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py628CODE
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Excessive Try-Catch Wrapping87 hits · 94 pts
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LOWcode/chapter-8/03_detection/yolov5-master/val.py326 except Exception as e:CODE
LOWcode/chapter-8/03_detection/yolov5-master/export.py109 except Exception as e:CODE
LOWcode/chapter-8/03_detection/yolov5-master/export.py183 except Exception as e:CODE
LOWcode/chapter-8/03_detection/yolov5-master/export.py254 except Exception:CODE
LOWcode/chapter-8/03_detection/yolov5-master/export.py326 except Exception:CODE
LOWcode/chapter-8/03_detection/yolov5-master/hubconf.py59 except Exception:CODE
LOWcode/chapter-8/03_detection/yolov5-master/hubconf.py75 except Exception as e:CODE
LOWcode/chapter-8/03_detection/yolov5-master/benchmarks.py91 except Exception as e:CODE
LOWcode/chapter-8/03_detection/yolov5-master/benchmarks.py133 except Exception:CODE
LOW…de/chapter-8/03_detection/yolov5-master/segment/val.py392 except Exception as e:CODE
LOW…hapter-8/03_detection/yolov5-master/utils/autobatch.py55 except Exception as e:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py482 except Exception as e:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py492 except Exception:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py640 except Exception as e:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py1036 except Exception as e:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py1065 except Exception as e:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py1105 except Exception as e: # use OpenCVCODE
LOW…hapter-8/03_detection/yolov5-master/utils/downloads.py70 except Exception as e: # url2CODE
LOW…hapter-8/03_detection/yolov5-master/utils/downloads.py112 except Exception:CODE
LOW…hapter-8/03_detection/yolov5-master/utils/downloads.py115 except Exception:CODE
LOW…hapter-8/03_detection/yolov5-master/utils/downloads.py118 except Exception:CODE
LOW…de/chapter-8/03_detection/yolov5-master/utils/plots.py61 except Exception: # download if missingCODE
LOW…de/chapter-8/03_detection/yolov5-master/utils/plots.py507 except Exception as e:CODE
LOW…de/chapter-8/03_detection/yolov5-master/utils/plots.py539 except Exception as e:CODE
LOW…apter-8/03_detection/yolov5-master/utils/autoanchor.py136 except Exception:CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py104 except Exception:CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py174 except Exception:CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py185 except Exception: # no backward methodCODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py195 except Exception as e:CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py290 except Exception:CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py357 except Exception:CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py322 except Exception:CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py420 except Exception as e:CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py446 except Exception as e:CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py594 except Exception:CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py1130 except Exception:CODE
MEDIUM…/chapter-8/03_detection/yolov5-master/utils/general.py1126def imwrite(path, im):CODE
LOW…er-8/03_detection/yolov5-master/utils/augmentations.py45 except Exception as e:CODE
LOW…er-8/03_detection/yolov5-master/utils/augmentations.py343 except Exception as e:CODE
LOW…8/03_detection/yolov5-master/utils/loggers/__init__.py113 except Exception:CODE
LOW…8/03_detection/yolov5-master/utils/loggers/__init__.py392 except Exception as e:CODE
LOW…ction/yolov5-master/utils/loggers/comet/comet_utils.py61 except Exception as e:CODE
LOW…er-8/03_detection/yolov5-master/utils/segment/plots.py139 except Exception as e:CODE
LOW…de/chapter-8/03_detection/yolov5-master/models/yolo.py387 except Exception as e:CODE
MEDIUM…de/chapter-8/03_detection/yolov5-master/models/yolo.py388 print(f'Error in {cfg}: {e}')CODE
LOW…pter-8/03_detection/yolov5-master/data/Objects365.yaml437 except Exception as e:CODE
LOW…e/chapter-8/03_detection/yolov5-master/data/xView.yaml132 except Exception as e:CODE
LOWcode/chapter-8/04_tracking/utils/autobatch.py55 except Exception as e:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py482 except Exception as e:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py492 except Exception:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py640 except Exception as e:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py1036 except Exception as e:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py1065 except Exception as e:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py1105 except Exception as e: # use OpenCVCODE
LOWcode/chapter-8/04_tracking/utils/downloads.py70 except Exception as e: # url2CODE
LOWcode/chapter-8/04_tracking/utils/downloads.py112 except Exception:CODE
LOWcode/chapter-8/04_tracking/utils/downloads.py115 except Exception:CODE
LOWcode/chapter-8/04_tracking/utils/downloads.py118 except Exception:CODE
LOWcode/chapter-8/04_tracking/utils/plots.py61 except Exception: # download if missingCODE
LOWcode/chapter-8/04_tracking/utils/plots.py507 except Exception as e:CODE
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AI Structural Patterns55 hits · 55 pts
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LOWcode/chapter-7/my_utils.py87CODE
LOWcode/chapter-7/my_utils.py124CODE
LOWcode/chapter-9/e_gpt/tokenizations/tokenization_bert.py105CODE
LOW…-9/e_gpt/tokenizations/tokenization_bert_word_level.py108CODE
LOWcode/chapter-9/d_bert/processors/ner_seq.py68CODE
LOWcode/chapter-9/d_bert/processors/ner_seq.py29CODE
LOWcode/chapter-9/d_bert/processors/ner_seq.py49CODE
LOWcode/chapter-9/d_bert/processors/ner_span.py64CODE
LOWcode/chapter-9/d_bert/processors/ner_span.py21CODE
LOWcode/chapter-9/d_bert/processors/ner_span.py44CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py143CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py261CODE
LOWcode/chapter-9/d_bert/callback/optimizater/adafactor.py18CODE
LOWcode/chapter-9/c_transformer/c_train_curve_plot.py23CODE
LOWcode/chapter-9/c_transformer/transformer/Models.py132CODE
LOW…de/chapter-8/03_detection/yolov5-master/00-save-gif.py54CODE
LOWcode/chapter-8/03_detection/yolov5-master/val.py99CODE
LOWcode/chapter-8/03_detection/yolov5-master/export.py311CODE
LOWcode/chapter-8/03_detection/yolov5-master/export.py510CODE
LOWcode/chapter-8/03_detection/yolov5-master/detect.py55CODE
LOWcode/chapter-8/03_detection/yolov5-master/benchmarks.py52CODE
LOWcode/chapter-8/03_detection/yolov5-master/benchmarks.py114CODE
LOW…e/chapter-8/03_detection/yolov5-master/classify/val.py45CODE
LOW…apter-8/03_detection/yolov5-master/classify/predict.py56CODE
LOW…de/chapter-8/03_detection/yolov5-master/segment/val.py130CODE
LOW…hapter-8/03_detection/yolov5-master/segment/predict.py56CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py103CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py439CODE
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py889CODE
LOW…er-8/03_detection/yolov5-master/utils/augmentations.py144CODE
LOW…er-8/03_detection/yolov5-master/utils/augmentations.py305CODE
LOW…3_detection/yolov5-master/utils/segment/dataloaders.py23CODE
LOW…3_detection/yolov5-master/utils/segment/dataloaders.py84CODE
LOW…detection/yolov5-master/utils/segment/augmentations.py25CODE
LOWcode/chapter-8/05_cyclegan/models/networks.py433CODE
LOWcode/chapter-8/01_classification/utils/my_utils.py89CODE
LOWcode/chapter-8/01_classification/utils/my_utils.py126CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py103CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py439CODE
LOWcode/chapter-8/04_tracking/utils/general.py889CODE
LOWcode/chapter-8/04_tracking/utils/augmentations.py144CODE
LOWcode/chapter-8/04_tracking/utils/augmentations.py305CODE
LOWcode/chapter-8/04_tracking/utils/segment/dataloaders.py23CODE
LOWcode/chapter-8/04_tracking/utils/segment/dataloaders.py84CODE
LOW…e/chapter-8/04_tracking/utils/segment/augmentations.py25CODE
LOW…chapter-8/04_tracking/deep_sort/deep_sort/deep_sort.py14CODE
LOW…-8/07_image_captioning/clip_cap_base/my_utils/utils.py90CODE
LOW…/07_image_captioning/clip_cap_base/my_models/models.py147CODE
LOW…/07_image_captioning/clip_cap_base/my_models/models.py171CODE
LOW…e/chapter-8/07_image_captioning/cnn_rnn_base/models.py39CODE
LOWcode/chapter-6/my_utils.py61CODE
LOWcode/chapter-6/my_utils.py95CODE
LOWcode/chapter-2/02_COVID_19_cls.py97CODE
LOWcode/chapter-5/02_sgd.py95CODE
LOWcode/chapter-5/03_lr_scheduler.py97CODE
Redundant / Tautological Comments33 hits · 50 pts
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LOWcode/chapter-7/07_model_ensemble.py263 # Print results on different ensemble methodsCOMMENT
LOWcode/chapter-9/d_bert/run_ner_softmax.py62 # Check if saved optimizer or scheduler states existCOMMENT
LOWcode/chapter-9/d_bert/run_ner_softmax.py96 # Check if continuing training from a checkpointCOMMENT
LOWcode/chapter-9/d_bert/tools/plot.py52 # Loop over data dimensions and create text annotations.COMMENT
LOWcode/chapter-9/d_bert/models/layers/crf.py231 # Set score to the next score if this timestep is valid (mask == 1)COMMENT
LOWcode/chapter-9/d_bert/models/layers/crf.py294 # Set score to the next score if this timestep is valid (mask == 1)COMMENT
LOWcode/chapter-9/d_bert/models/layers/crf.py382 # Set score to the next score if this timestep is valid (mask == 1)COMMENT
LOW…de/chapter-8/03_detection/yolov5-master/00-save-gif.py157 # Print resultsCOMMENT
LOW…de/chapter-8/03_detection/yolov5-master/00-save-gif.py209 # Print resultsCOMMENT
LOWcode/chapter-8/03_detection/yolov5-master/val.py281 # Print resultsCOMMENT
LOWcode/chapter-8/03_detection/yolov5-master/val.py287 # Print results per classCOMMENT
LOWcode/chapter-8/03_detection/yolov5-master/detect.py158 # Print resultsCOMMENT
LOWcode/chapter-8/03_detection/yolov5-master/detect.py210 # Print resultsCOMMENT
LOWcode/chapter-8/03_detection/yolov5-master/benchmarks.py99 # Print resultsCOMMENT
LOWcode/chapter-8/03_detection/yolov5-master/benchmarks.py136 # Print resultsCOMMENT
LOW…e/chapter-8/03_detection/yolov5-master/classify/val.py135 # Print resultsCOMMENT
LOW…apter-8/03_detection/yolov5-master/classify/predict.py140 # Print resultsCOMMENT
LOW…apter-8/03_detection/yolov5-master/classify/predict.py184 # Print resultsCOMMENT
LOW…de/chapter-8/03_detection/yolov5-master/segment/val.py344 # Print resultsCOMMENT
LOW…de/chapter-8/03_detection/yolov5-master/segment/val.py350 # Print results per classCOMMENT
LOW…hapter-8/03_detection/yolov5-master/segment/predict.py170 # Print resultsCOMMENT
LOW…hapter-8/03_detection/yolov5-master/segment/predict.py231 # Print resultsCOMMENT
LOW…hapter-8/03_detection/yolov5-master/utils/downloads.py17 # Check if string is URL and check if URL existsCOMMENT
LOW…/chapter-8/03_detection/yolov5-master/utils/general.py437 # Check if environment supports image displaysCOMMENT
LOW…etection/yolov5-master/utils/loggers/comet/__init__.py157 # Check if running the Experiment with the Comet OptimizerCOMMENT
LOW…etection/yolov5-master/utils/loggers/comet/__init__.py433 # Check if running Experiment with Comet OptimizerCOMMENT
LOW…n/yolov5-master/utils/loggers/clearml/clearml_utils.py112 # Set data to data_dict because wandb will crash without this information and opt is the best wayCOMMENT
LOWcode/chapter-8/04_tracking/utils/downloads.py17 # Check if string is URL and check if URL existsCOMMENT
LOWcode/chapter-8/04_tracking/utils/general.py437 # Check if environment supports image displaysCOMMENT
LOW…/chapter-8/04_tracking/utils/loggers/comet/__init__.py157 # Check if running the Experiment with the Comet OptimizerCOMMENT
LOW…/chapter-8/04_tracking/utils/loggers/comet/__init__.py433 # Check if running Experiment with Comet OptimizerCOMMENT
LOW…r-8/04_tracking/utils/loggers/clearml/clearml_utils.py112 # Set data to data_dict because wandb will crash without this information and opt is the best wayCOMMENT
LOW…chapter-8/07_image_captioning/cnn_rnn_base/01_train.py125 # Check if there was an improvementCOMMENT
Hyper-Verbose Identifiers48 hits · 48 pts
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LOWcode/chapter-9/d_bert/02_predict_parse.py12def extract_entities_from_lines(test_data_path, predictions_path):CODE
LOW…_bert/tools/convert_albert_tf_checkpoint_to_pytorch.py14def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_file, pytorch_dump_path):CODE
LOWcode/chapter-9/d_bert/processors/utils_ner.py6class DataProcessor(object):CODE
LOWcode/chapter-9/d_bert/processors/ner_seq.py68def convert_examples_to_features(examples,label_list,max_seq_length,tokenizer,CODE
LOWcode/chapter-9/d_bert/processors/ner_span.py64def convert_examples_to_features(examples,label_list,max_seq_length,tokenizer,CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py13def get_constant_schedule_with_warmup(optimizer, num_warmup_steps, last_epoch=-1):CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py25def get_linear_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, last_epoch=-1):CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py37def get_cosine_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, num_cycles=.5, last_epoch=-1):CODE
LOWcode/chapter-9/d_bert/callback/lr_scheduler.py51def get_cosine_with_hard_restarts_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, num_cycles=1., lCODE
LOWcode/chapter-9/c_transformer/transformer/Models.py32 def _get_sinusoid_encoding_table(self, n_position, d_hid):CODE
LOWcode/chapter-9/c_transformer/transformer/Translator.py60 def _get_the_best_score_and_idx(self, gen_seq, dec_output, scores, step):CODE
LOW…e/chapter-8/03_detection/yolov5-master/utils/triton.py32 def create_input_placeholders() -> typing.List[InferInput]:CODE
LOW…e/chapter-8/03_detection/yolov5-master/utils/triton.py44 def create_input_placeholders() -> typing.List[InferInput]:CODE
LOW…pter-8/03_detection/yolov5-master/utils/dataloaders.py1197def create_classification_dataloader(path,CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py66def reshape_classifier_output(model, n=1000):CODE
LOW…pter-8/03_detection/yolov5-master/utils/torch_utils.py89def torch_distributed_zero_first(local_rank: int):CODE
LOW…8/03_detection/yolov5-master/utils/loggers/__init__.py151 def on_pretrain_routine_start(self):CODE
LOW…etection/yolov5-master/utils/loggers/comet/__init__.py348 def download_dataset_artifact(self, artifact_path):CODE
LOW…ction/yolov5-master/utils/loggers/comet/comet_utils.py19def download_model_checkpoint(opt, experiment):CODE
LOW…-8/03_detection/yolov5-master/utils/segment/metrics.py17def ap_per_class_box_and_mask(CODE
LOWcode/chapter-8/03_detection/yolov5-master/models/tf.py554def representative_dataset_gen(dataset, ncalib=100):CODE
LOWcode/chapter-8/05_cyclegan/util/visualizer.py107 def create_visdom_connections(self):CODE
LOWcode/chapter-8/05_cyclegan/models/test_model.py12 def modify_commandline_options(parser, is_train=True):CODE
LOWcode/chapter-8/05_cyclegan/models/template_model.py25 def modify_commandline_options(parser, is_train=True):CODE
LOWcode/chapter-8/05_cyclegan/models/cycle_gan_model.py20 def modify_commandline_options(parser, is_train=True):CODE
LOWcode/chapter-8/05_cyclegan/models/pix2pix_model.py17 def modify_commandline_options(parser, is_train=True):CODE
LOWcode/chapter-8/05_cyclegan/models/colorization_model.py15 def modify_commandline_options(parser, is_train=True):CODE
LOWcode/chapter-8/05_cyclegan/models/base_model.py47 def modify_commandline_options(parser, is_train):CODE
LOWcode/chapter-8/05_cyclegan/models/base_model.py162 def __patch_instance_norm_state_dict(self, state_dict, module, keys, i=0):CODE
LOWcode/chapter-8/05_cyclegan/data/colorization_dataset.py16 def modify_commandline_options(parser, is_train):CODE
LOWcode/chapter-8/05_cyclegan/data/base_dataset.py33 def modify_commandline_options(parser, is_train):CODE
LOWcode/chapter-8/05_cyclegan/data/template_dataset.py22 def modify_commandline_options(parser, is_train):CODE
LOW…apter-8/06_diffusion-model/DDPM/Diffusion/Diffusion.py71 def predict_xt_prev_mean_from_eps(self, x_t, t, eps):CODE
LOW…model/DDPM/DiffusionFreeGuidence/DiffusionCondition.py68 def predict_xt_prev_mean_from_eps(self, x_t, t, eps):CODE
LOWcode/chapter-8/04_tracking/01-main.py125 def get_currently_ids_by_area(tracks, bbox_area_list_, area_index):CODE
LOWcode/chapter-8/04_tracking/utils/triton.py32 def create_input_placeholders() -> typing.List[InferInput]:CODE
LOWcode/chapter-8/04_tracking/utils/triton.py44 def create_input_placeholders() -> typing.List[InferInput]:CODE
LOWcode/chapter-8/04_tracking/utils/dataloaders.py1197def create_classification_dataloader(path,CODE
LOWcode/chapter-8/04_tracking/utils/torch_utils.py66def reshape_classifier_output(model, n=1000):CODE
LOWcode/chapter-8/04_tracking/utils/torch_utils.py89def torch_distributed_zero_first(local_rank: int):CODE
LOWcode/chapter-8/04_tracking/utils/loggers/__init__.py151 def on_pretrain_routine_start(self):CODE
LOW…/chapter-8/04_tracking/utils/loggers/comet/__init__.py348 def download_dataset_artifact(self, artifact_path):CODE
LOW…apter-8/04_tracking/utils/loggers/comet/comet_utils.py19def download_model_checkpoint(opt, experiment):CODE
LOWcode/chapter-8/04_tracking/utils/segment/metrics.py17def ap_per_class_box_and_mask(CODE
LOWcode/chapter-8/04_tracking/models/tf.py554def representative_dataset_gen(dataset, ncalib=100):CODE
LOW…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py358 def schedule_output_by_frames(self, frames_quota, frame_counter, output_dir=JsonMeta.PATH_TO_SAVE):CODE
LOW…e/chapter-8/07_image_captioning/cnn_rnn_base/models.py133 def load_pretrained_embeddings(self, embeddings):CODE
LOW…ter-8/07_image_captioning/cnn_rnn_base/02_inference.py21def caption_image_beam_search(encoder, decoder, img, word_map, beam_size=3):CODE
Docstring Block Structure7 hits · 35 pts
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HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py196 Args: frame_id (int): timestamp (float): opencv captured frame time property RSTRING
HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py228 Args: frame_id: bbox_id: Returns: bbox_id (int): Raises:STRING
HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py246 Args: frame_id (int): bbox_id (int): top (int): left (int): STRING
HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py274 Args: frame_id: bbox_id: category: confidence: the confidence vSTRING
HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py307 Args: output_name: Returns: None Notes: It creates the jsSTRING
HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py328 Notes: Creates folder and then periodically stores the jsons on that address. Args: STRING
HIGH…e/chapter-8/04_tracking/deep_sort/utils/json_logger.py369 Notes: We use this function to output jsons whenever possible. like the time that we exSTRING
Self-Referential Comments14 hits · 34 pts
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MEDIUMcode/chapter-9/a_rnn_lstm/models/rnn.py103 # Create an instance of the RNNTextClassifierCOMMENT
MEDIUM…pter-8/03_detection/yolov5-master/utils/dataloaders.py321 # Create a new video capture objectCOMMENT
MEDIUM…hapter-8/03_detection/yolov5-master/utils/callbacks.py15 # Define the available callbacksCOMMENT
MEDIUM…de/chapter-8/03_detection/yolov5-master/models/yolo.py280 # Create a YOLOv5 classification model from a YOLOv5 detection modelCOMMENT
MEDIUM…de/chapter-8/03_detection/yolov5-master/models/yolo.py295 # Create a YOLOv5 classification model from a *.yaml fileCOMMENT
MEDIUMcode/chapter-8/05_cyclegan/util/image_pool.py6 """This class implements an image buffer that stores previously generated images.STRING
MEDIUMcode/chapter-8/05_cyclegan/models/base_model.py9 """This class is an abstract base class (ABC) for models.STRING
MEDIUMcode/chapter-8/05_cyclegan/data/base_dataset.py1"""This module implements an abstract base class (ABC) 'BaseDataset' for datasets.STRING
MEDIUMcode/chapter-8/05_cyclegan/data/base_dataset.py14 """This class is an abstract base class (ABC) for datasets.STRING
MEDIUMcode/chapter-8/04_tracking/utils/dataloaders.py321 # Create a new video capture objectCOMMENT
MEDIUMcode/chapter-8/04_tracking/utils/callbacks.py15 # Define the available callbacksCOMMENT
MEDIUMcode/chapter-8/04_tracking/models/yolo.py280 # Create a YOLOv5 classification model from a YOLOv5 detection modelCOMMENT
MEDIUMcode/chapter-8/04_tracking/models/yolo.py295 # Create a YOLOv5 classification model from a *.yaml fileCOMMENT
MEDIUM…de/chapter-8/07_image_captioning/cnn_rnn_base/utils.py80 # Create a base/root name for all output filesCOMMENT
Slop Phrases3 hits · 14 pts
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MEDIUMcode/chapter-8/05_cyclegan/models/template_model.py57 # you can use opt.isTrain to specify different behaviors for training and test. For example, some networks will COMMENT
MEDIUMcode/chapter-8/05_cyclegan/models/template_model.py59 # define networks; you can use opt.isTrain to specify different behaviors for training and test.COMMENT
MEDIUMcode/chapter-8/05_cyclegan/models/template_model.py66 # If two networks are updated at the same time, you can use itertools.chain to group them. See cycle_gan_modCOMMENT
Modern Structural Boilerplate13 hits · 13 pts
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LOWcode/chapter-9/e_gpt/tokenizations/tokenization_bert.py27logger = logging.getLogger(__name__)CODE
LOW…-9/e_gpt/tokenizations/tokenization_bert_word_level.py28logger = logging.getLogger(__name__)CODE
LOWcode/chapter-9/d_bert/processors/ner_seq.py8logger = logging.getLogger(__name__)CODE
LOWcode/chapter-9/d_bert/processors/ner_span.py8logger = logging.getLogger(__name__)CODE
LOWcode/chapter-9/c_transformer/transformer/__init__.py9__all__ = [CODE
LOW…etection/yolov5-master/utils/loggers/comet/__init__.py8logger = logging.getLogger(__name__)CODE
LOW…ction/yolov5-master/utils/loggers/comet/comet_utils.py12logger = logging.getLogger(__name__)CODE
LOW…/03_detection/yolov5-master/utils/loggers/comet/hpo.py10logger = logging.getLogger(__name__)CODE
LOW…/chapter-8/04_tracking/utils/loggers/comet/__init__.py8logger = logging.getLogger(__name__)CODE
LOW…apter-8/04_tracking/utils/loggers/comet/comet_utils.py12logger = logging.getLogger(__name__)CODE
LOWcode/chapter-8/04_tracking/utils/loggers/comet/hpo.py10logger = logging.getLogger(__name__)CODE
LOW…/chapter-8/04_tracking/deep_sort/deep_sort/__init__.py4__all__ = ['DeepSort', 'build_tracker']CODE
LOW…chapter-8/04_tracking/deep_sort/deep_sort/deep_sort.py10__all__ = ['DeepSort']CODE
Fake / Example Data11 hits · 12 pts
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LOWcode/chapter-11/01_resnet_export_onnx.py18 dummy_data = torch.randn((1, 3, 224, 224))CODE
LOWcode/chapter-11/01_resnet_export_onnx.py22 torch.onnx.export(model, (dummy_data), "resnet50_bs_1.onnx",CODE
LOWcode/chapter-11/01_resnet_export_onnx.py30 torch.onnx.export(model, (dummy_data), "resnet50_bs_dynamic.onnx",CODE
LOWcode/chapter-8/05_cyclegan/models/networks.py278def cal_gradient_penalty(netD, real_data, fake_data, device, type='mixed', constant=1.0, lambda_gp=10.0):CODE
LOWcode/chapter-8/05_cyclegan/models/networks.py284 fake_data (tensor array) -- generated images from the generatorSTRING
LOWcode/chapter-8/05_cyclegan/models/networks.py296 interpolatesv = fake_dataCODE
LOWcode/chapter-8/05_cyclegan/models/networks.py300 interpolatesv = alpha * real_data + ((1 - alpha) * fake_data)CODE
LOW…e/chapter-8/01_classification/01_resnet_export_onnx.py34 dummy_data = torch.randn((1, 3, 224, 224))CODE
LOW…e/chapter-8/01_classification/01_resnet_export_onnx.py39 torch.onnx.export(model, (dummy_data), path_out,CODE
LOW…/07_image_captioning/clip_cap_base/my_models/models.py168 dummy_token = self.get_dummy_token(tokens.shape[0], tokens.device)CODE
LOW…/07_image_captioning/clip_cap_base/my_models/models.py169 labels = torch.cat((dummy_token, tokens), dim=1)CODE
Verbosity Indicators5 hits · 10 pts
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LOWcode/chapter-1/03-torch-compile-performance.py148 # Step 1: Normalize the input arrays to have zero mean and unit varianceCOMMENT
LOWcode/chapter-1/03-torch-compile-performance.py159 # Step 2: Perform the tensor product followed by sum over last two dimensionsCOMMENT
LOWcode/chapter-1/03-torch-compile-performance.py162 # Step 3: Apply thresholding to clip values outside of [-1, 1]COMMENT
LOWcode/chapter-1/03-torch-compile-performance.py165 # Step 4: Apply exponential function for non-linearityCOMMENT
LOWcode/chapter-1/03-torch-compile-performance.py168 # Step 5: Add a small regularization term to avoid overfittingCOMMENT
Structural Annotation Overuse5 hits · 10 pts
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LOWcode/chapter-1/03-torch-compile-performance.py148 # Step 1: Normalize the input arrays to have zero mean and unit varianceCOMMENT
LOWcode/chapter-1/03-torch-compile-performance.py159 # Step 2: Perform the tensor product followed by sum over last two dimensionsCOMMENT
LOWcode/chapter-1/03-torch-compile-performance.py162 # Step 3: Apply thresholding to clip values outside of [-1, 1]COMMENT
LOWcode/chapter-1/03-torch-compile-performance.py165 # Step 4: Apply exponential function for non-linearityCOMMENT
LOWcode/chapter-1/03-torch-compile-performance.py168 # Step 5: Add a small regularization term to avoid overfittingCOMMENT
Example Usage Blocks6 hits · 9 pts
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LOWcode/chapter-9/a_rnn_lstm/models/rnn.py96 # Example usageCOMMENT
LOWcode/chapter-9/b_seq2seq/models/seq2seq.py137 # Example usageCOMMENT
LOW…hapter-8/03_detection/yolov5-master/utils/autobatch.py23 # Usage:COMMENT
LOW…/chapter-8/03_detection/yolov5-master/models/common.py318 # Usage:COMMENT
LOWcode/chapter-8/04_tracking/utils/autobatch.py23 # Usage:COMMENT
LOWcode/chapter-8/04_tracking/models/common.py318 # Usage:COMMENT
AI Response Leakage1 hit · 8 pts
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HIGHcode/chapter-6/04_cam_series_demo.py86 # In this example grayscale_cam has only one image in the batch:COMMENT
AI Slop Vocabulary2 hits · 6 pts
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MEDIUM…/chapter-8/03_detection/yolov5-master/models/common.py623 # YOLOv5 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMSCOMMENT
MEDIUMcode/chapter-8/04_tracking/models/common.py623 # YOLOv5 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMSCOMMENT
TODO Padding2 hits · 3 pts
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LOW…er-8/03_detection/yolov5-master/utils/augmentations.py325 # TODO: implement AugMix, AutoAug & RandAug in albumentationCOMMENT
LOWcode/chapter-8/04_tracking/utils/augmentations.py325 # TODO: implement AugMix, AutoAug & RandAug in albumentationCOMMENT
Cross-Language Confusion1 hit · 2 pts
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HIGHcode/chapter-8/03_detection/yolov5-master/export.py41 $ cd .. && git clone https://github.com/zldrobit/tfjs-yolov5-example.git && cd tfjs-yolov5-exampleSTRING