《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。
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).
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.
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.
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.
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.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | code/chapter-7/my_utils.py | 0 | @file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数 | STRING |
| HIGH | code/chapter-9/b_seq2seq/utils/my_utils.py | 0 | @file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数 | STRING |
| HIGH | code/chapter-9/c_transformer/utils/my_utils.py | 0 | @file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数 | STRING |
| HIGH | code/chapter-8/02_segmentation/utils/utils.py | 0 | @file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数 | STRING |
| HIGH | code/chapter-8/01_classification/utils/my_utils.py | 0 | @file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数 | STRING |
| HIGH | code/chapter-6/my_utils.py | 0 | @file name : 03_utils.py @author : tingsongyu https://github.com/tingsongyu @date : 2022-06-14 @brief : 训练所需的函数 | STRING |
| HIGH | code/chapter-7/my_utils.py | 0 | 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 vali | STRING |
| HIGH | code/chapter-9/a_rnn_lstm/utils/my_utils.py | 0 | 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 vali | STRING |
| HIGH | code/chapter-9/b_seq2seq/utils/my_utils.py | 0 | 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 vali | STRING |
| HIGH | code/chapter-9/c_transformer/utils/my_utils.py | 0 | 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 vali | STRING |
| HIGH | code/chapter-8/01_classification/utils/my_utils.py | 0 | 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 vali | STRING |
| HIGH | code/chapter-6/my_utils.py | 0 | 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 vali | STRING |
| HIGH | code/chapter-7/my_utils.py | 0 | compute the average over a list of tensors with the same size. | STRING |
| HIGH | code/chapter-9/a_rnn_lstm/utils/my_utils.py | 0 | compute the average over a list of tensors with the same size. | STRING |
| HIGH | code/chapter-8/01_classification/utils/my_utils.py | 0 | compute the average over a list of tensors with the same size. | STRING |
| HIGH | code/chapter-7/my_utils.py | 0 | 在out_dir文件夹下以当前时间命名,创建日志文件夹,并创建logger用于记录信息 :param out_dir: str :return: | STRING |
| HIGH | code/chapter-9/a_rnn_lstm/utils/my_utils.py | 0 | 在out_dir文件夹下以当前时间命名,创建日志文件夹,并创建logger用于记录信息 :param out_dir: str :return: | STRING |
| HIGH | code/chapter-9/b_seq2seq/utils/my_utils.py | 0 | 在out_dir文件夹下以当前时间命名,创建日志文件夹,并创建logger用于记录信息 :param out_dir: str :return: | STRING |
| HIGH | code/chapter-9/c_transformer/utils/my_utils.py | 0 | 在out_dir文件夹下以当前时间命名,创建日志文件夹,并创建logger用于记录信息 :param out_dir: str :return: | STRING |
| HIGH | code/chapter-8/02_segmentation/utils/utils.py | 0 | 在out_dir文件夹下以当前时间命名,创建日志文件夹,并创建logger用于记录信息 :param out_dir: str :return: | STRING |
| HIGH | code/chapter-8/01_classification/utils/my_utils.py | 0 | 在out_dir文件夹下以当前时间命名,创建日志文件夹,并创建logger用于记录信息 :param out_dir: str :return: | STRING |
| HIGH | code/chapter-7/my_utils.py | 0 | computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/mas | STRING |
| HIGH | code/chapter-9/a_rnn_lstm/utils/my_utils.py | 0 | computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/mas | STRING |
| HIGH | code/chapter-9/b_seq2seq/utils/my_utils.py | 0 | computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/mas | STRING |
| HIGH | code/chapter-9/c_transformer/utils/my_utils.py | 0 | computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/mas | STRING |
| HIGH | code/chapter-8/02_segmentation/utils/utils.py | 0 | computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/mas | STRING |
| HIGH | code/chapter-8/01_classification/utils/my_utils.py | 0 | computes and stores the average and current value hacked from https://github.com/rwightman/pytorch-image-models/blob/mas | STRING |
| HIGH | code/chapter-7/my_utils.py | 0 | computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/ | STRING |
| HIGH | code/chapter-9/a_rnn_lstm/utils/my_utils.py | 0 | computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/ | STRING |
| HIGH | code/chapter-9/b_seq2seq/utils/my_utils.py | 0 | computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/ | STRING |
| HIGH | code/chapter-9/c_transformer/utils/my_utils.py | 0 | computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/ | STRING |
| HIGH | code/chapter-8/02_segmentation/utils/utils.py | 0 | computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/ | STRING |
| HIGH | code/chapter-8/01_classification/utils/my_utils.py | 0 | computes the accuracy over the k top predictions for the specified values of k hacked from https://github.com/rwightman/ | STRING |
| HIGH | code/chapter-9/a_rnn_lstm/utils/my_utils.py | 0 | 加载预训练词向量权重 :param glove_file_path: :param word2idx: :return: | STRING |
| HIGH | code/chapter-9/b_seq2seq/utils/my_utils.py | 0 | 加载预训练词向量权重 :param glove_file_path: :param word2idx: :return: | STRING |
| HIGH | code/chapter-9/c_transformer/utils/my_utils.py | 0 | 加载预训练词向量权重 :param glove_file_path: :param word2idx: :return: | STRING |
| HIGH | code/chapter-9/e_gpt/generate.py | 0 | checks whether cp is the codepoint of a cjk character. | STRING |
| HIGH | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 0 | checks whether cp is the codepoint of a cjk character. | STRING |
| HIGH | …-9/e_gpt/tokenizations/tokenization_bert_word_level.py | 0 | checks whether cp is the codepoint of a cjk character. | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/sgdw.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/lamb.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/lars.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/adamw.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/adabound.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/nadam.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/ralars.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-9/d_bert/callback/optimizater/lookahead.py | 0 | performs a single lookahead optimization step. arguments: closure (callable, optional): a closure that reevaluates the m | STRING |
| HIGH | code/chapter-11/02_resnet_inference.py | 0 | 加载标签名 :param p_clsnames: :param p_clsnames_cn: :return: | STRING |
| HIGH | code/chapter-12/a_trt_infer_engine_resnet50.py | 0 | 加载标签名 :param p_clsnames: :param p_clsnames_cn: :return: | STRING |
| HIGH | code/chapter-12/01_trt_resnet50_cuda.py | 0 | 加载标签名 :param p_clsnames: :param p_clsnames_cn: :return: | STRING |
| HIGH | code/chapter-12/04_build_resnet50_by_api.py | 0 | 加载标签名 :param p_clsnames: :param p_clsnames_cn: :return: | STRING |
| HIGH | code/chapter-12/05_trt_resnet50_execute_v3.py | 0 | 加载标签名 :param p_clsnames: :param p_clsnames_cn: :return: | STRING |
| HIGH | code/chapter-12/02_trt_resnet50_pycuda.py | 0 | 加载标签名 :param p_clsnames: :param p_clsnames_cn: :return: | STRING |
| HIGH | code/chapter-8/02_segmentation/02_train_seg.py | 0 | @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 |
| HIGH | code/chapter-8/02_segmentation/03_train_architecture.py | 0 | @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 |
| HIGH | code/chapter-8/01_classification/train_aug.py | 0 | @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 |
| HIGH | code/chapter-8/01_classification/train_main.py | 0 | @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 |
| HIGH | code/chapter-8/05_cyclegan/models/test_model.py | 0 | initialize the cyclegan class. parameters: opt (option class)-- stores all the experiment flags; needs to be a subclass | STRING |
| HIGH | code/chapter-8/05_cyclegan/models/pix2pix_model.py | 0 | initialize the cyclegan class. parameters: opt (option class)-- stores all the experiment flags; needs to be a subclass | STRING |
| HIGH | code/chapter-8/05_cyclegan/models/cycle_gan_model.py | 0 | initialize the cyclegan class. parameters: opt (option class)-- stores all the experiment flags; needs to be a subclass | STRING |
| 34 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | code/chapter-7/01_torch_save_load.py | 41 | # "optimizer": optimizer.state_dict(), | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 8161 | ##9 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 8601 | ##2015 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 8821 | ##bo | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 9161 | 2019 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 9341 | ##46 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 9741 | ##king | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 9761 | ##マ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 10141 | ofweek | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 10281 | vcd | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 11081 | ##atic | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 11361 | ##ack | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 11581 | 328 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 12401 | ##gas | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 12501 | sylvia | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 12941 | diary | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 13061 | ##mes | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab_small.txt | 13121 | 828 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 8161 | ##9 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 8601 | ##2015 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 8821 | ##bo | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 9161 | 2019 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 9341 | ##46 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 9741 | ##king | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 9761 | ##マ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 10141 | ofweek | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 10281 | vcd | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 11081 | ##atic | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 11361 | ##ack | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 11581 | 328 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 12401 | ##gas | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 12501 | sylvia | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 12941 | diary | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13061 | ##mes | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13121 | 828 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13301 | ##anda | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13321 | ##$ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13341 | ##\ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13361 | ##¼ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13381 | ##α | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13401 | ##χ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13421 | ##х | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13441 | ##ي | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13461 | ##ᄇ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13481 | ##ᅯ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13501 | ##‥ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13521 | ##ⅱ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13541 | ##∼ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13561 | ##⑤ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13581 | ##┆ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13601 | ##▇ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13621 | ##☕ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13641 | ##✿ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13661 | ##〓 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13681 | ##ァ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13701 | ##ヨ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13721 | ##ㄤ | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13741 | ##专 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13761 | ##丫 | COMMENT |
| LOW | code/chapter-9/e_gpt/cache/vocab.txt | 13781 | ##乌 | COMMENT |
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| LOW | code/chapter-7/01_torch_save_load.py | 10 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
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| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
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| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
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| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
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| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/06_albumentations-demo.py | 13 | CODE | |
| LOW | code/chapter-7/02_fintune-freeze.py | 15 | CODE | |
| LOW | code/chapter-7/02_fintune-freeze.py | 22 | CODE | |
| LOW | code/chapter-7/02_fintune-multi-lr.py | 15 | CODE | |
| LOW | code/chapter-7/02_fintune-multi-lr.py | 22 | CODE | |
| LOW | code/chapter-9/a_rnn_lstm/a_gen_vocabulary.py | 12 | CODE | |
| LOW | code/chapter-9/a_rnn_lstm/models/rnn.py | 10 | CODE | |
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| LOW | code/chapter-9/e_gpt/train.py | 21 | CODE | |
| LOW | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 17 | CODE | |
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| LOW | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 17 | CODE | |
| LOW | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 17 | CODE | |
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| LOW | …-9/e_gpt/tokenizations/tokenization_bert_word_level.py | 17 | CODE | |
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| LOW | …_bert/tools/convert_albert_tf_checkpoint_to_pytorch.py | 3 | CODE | |
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| LOW | code/chapter-9/d_bert/processors/utils_ner.py | 4 | CODE | |
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| LOW | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 347 | CODE | |
| LOW | …-9/e_gpt/tokenizations/tokenization_bert_word_level.py | 364 | CODE | |
| LOW | code/chapter-9/d_bert/run_ner_softmax.py | 35 | CODE | |
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| LOW | code/chapter-9/d_bert/tools/common.py | 280 | CODE | |
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| LOW | code/chapter-9/d_bert/processors/utils_ner.py | 78 | CODE | |
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| LOW | code/chapter-9/d_bert/processors/ner_seq.py | 181 | CODE | |
| LOW | code/chapter-9/d_bert/processors/ner_span.py | 197 | CODE | |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 143 | CODE | |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 301 | CODE | |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 351 | CODE | |
| LOW | code/chapter-9/d_bert/callback/trainingmonitor.py | 26 | CODE | |
| LOW | code/chapter-9/d_bert/callback/optimizater/sgdw.py | 47 | CODE | |
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| LOW | code/chapter-8/03_detection/visdrone2yolo.py | 16 | CODE | |
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| LOW | …e/chapter-8/03_detection/yolov5-master/classify/val.py | 45 | CODE | |
| LOW | …apter-8/03_detection/yolov5-master/classify/predict.py | 56 | CODE | |
| LOW | …chapter-8/03_detection/yolov5-master/classify/train.py | 56 | CODE | |
| LOW | …de/chapter-8/03_detection/yolov5-master/segment/val.py | 130 | CODE | |
| LOW | …de/chapter-8/03_detection/yolov5-master/segment/val.py | 436 | CODE | |
| LOW | …hapter-8/03_detection/yolov5-master/segment/predict.py | 56 | CODE | |
| LOW | …/chapter-8/03_detection/yolov5-master/segment/train.py | 69 | CODE | |
| LOW | …/chapter-8/03_detection/yolov5-master/segment/train.py | 507 | CODE | |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/metrics.py | 222 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 930 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 990 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 241 | CODE | |
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| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 750 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 808 | CODE | |
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| LOW | …de/chapter-8/03_detection/yolov5-master/utils/plots.py | 230 | CODE | |
| LOW | …de/chapter-8/03_detection/yolov5-master/utils/plots.py | 514 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 66 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 151 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 212 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 318 | CODE | |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 468 | CODE | |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 506 | CODE | |
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| LOW | code/chapter-8/03_detection/yolov5-master/val.py | 326 | except Exception as e: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/export.py | 109 | except Exception as e: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/export.py | 183 | except Exception as e: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/export.py | 254 | except Exception: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/export.py | 326 | except Exception: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/hubconf.py | 59 | except Exception: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/hubconf.py | 75 | except Exception as e: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/benchmarks.py | 91 | except Exception as e: | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/benchmarks.py | 133 | except Exception: | CODE |
| LOW | …de/chapter-8/03_detection/yolov5-master/segment/val.py | 392 | except Exception as e: | CODE |
| LOW | …hapter-8/03_detection/yolov5-master/utils/autobatch.py | 55 | except Exception as e: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 482 | except Exception as e: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 492 | except Exception: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 640 | except Exception as e: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 1036 | except Exception as e: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 1065 | except Exception as e: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 1105 | except Exception as e: # use OpenCV | CODE |
| LOW | …hapter-8/03_detection/yolov5-master/utils/downloads.py | 70 | except Exception as e: # url2 | CODE |
| LOW⚡ | …hapter-8/03_detection/yolov5-master/utils/downloads.py | 112 | except Exception: | CODE |
| LOW⚡ | …hapter-8/03_detection/yolov5-master/utils/downloads.py | 115 | except Exception: | CODE |
| LOW⚡ | …hapter-8/03_detection/yolov5-master/utils/downloads.py | 118 | except Exception: | CODE |
| LOW | …de/chapter-8/03_detection/yolov5-master/utils/plots.py | 61 | except Exception: # download if missing | CODE |
| LOW | …de/chapter-8/03_detection/yolov5-master/utils/plots.py | 507 | except Exception as e: | CODE |
| LOW | …de/chapter-8/03_detection/yolov5-master/utils/plots.py | 539 | except Exception as e: | CODE |
| LOW | …apter-8/03_detection/yolov5-master/utils/autoanchor.py | 136 | except Exception: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 104 | except Exception: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 174 | except Exception: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 185 | except Exception: # no backward method | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 195 | except Exception as e: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 290 | except Exception: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 357 | except Exception: | CODE |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 322 | except Exception: | CODE |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 420 | except Exception as e: | CODE |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 446 | except Exception as e: | CODE |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 594 | except Exception: | CODE |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 1130 | except Exception: | CODE |
| MEDIUM | …/chapter-8/03_detection/yolov5-master/utils/general.py | 1126 | def imwrite(path, im): | CODE |
| LOW | …er-8/03_detection/yolov5-master/utils/augmentations.py | 45 | except Exception as e: | CODE |
| LOW | …er-8/03_detection/yolov5-master/utils/augmentations.py | 343 | except Exception as e: | CODE |
| LOW | …8/03_detection/yolov5-master/utils/loggers/__init__.py | 113 | except Exception: | CODE |
| LOW | …8/03_detection/yolov5-master/utils/loggers/__init__.py | 392 | except Exception as e: | CODE |
| LOW | …ction/yolov5-master/utils/loggers/comet/comet_utils.py | 61 | except Exception as e: | CODE |
| LOW | …er-8/03_detection/yolov5-master/utils/segment/plots.py | 139 | except Exception as e: | CODE |
| LOW | …de/chapter-8/03_detection/yolov5-master/models/yolo.py | 387 | except Exception as e: | CODE |
| MEDIUM | …de/chapter-8/03_detection/yolov5-master/models/yolo.py | 388 | print(f'Error in {cfg}: {e}') | CODE |
| LOW | …pter-8/03_detection/yolov5-master/data/Objects365.yaml | 437 | except Exception as e: | CODE |
| LOW | …e/chapter-8/03_detection/yolov5-master/data/xView.yaml | 132 | except Exception as e: | CODE |
| LOW | code/chapter-8/04_tracking/utils/autobatch.py | 55 | except Exception as e: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 482 | except Exception as e: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 492 | except Exception: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 640 | except Exception as e: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 1036 | except Exception as e: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 1065 | except Exception as e: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 1105 | except Exception as e: # use OpenCV | CODE |
| LOW | code/chapter-8/04_tracking/utils/downloads.py | 70 | except Exception as e: # url2 | CODE |
| LOW⚡ | code/chapter-8/04_tracking/utils/downloads.py | 112 | except Exception: | CODE |
| LOW⚡ | code/chapter-8/04_tracking/utils/downloads.py | 115 | except Exception: | CODE |
| LOW⚡ | code/chapter-8/04_tracking/utils/downloads.py | 118 | except Exception: | CODE |
| LOW | code/chapter-8/04_tracking/utils/plots.py | 61 | except Exception: # download if missing | CODE |
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| LOW | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 105 | CODE | |
| LOW | …-9/e_gpt/tokenizations/tokenization_bert_word_level.py | 108 | CODE | |
| LOW | code/chapter-9/d_bert/processors/ner_seq.py | 68 | CODE | |
| LOW | code/chapter-9/d_bert/processors/ner_seq.py | 29 | CODE | |
| LOW | code/chapter-9/d_bert/processors/ner_seq.py | 49 | CODE | |
| LOW | code/chapter-9/d_bert/processors/ner_span.py | 64 | CODE | |
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| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 143 | CODE | |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 261 | CODE | |
| LOW | code/chapter-9/d_bert/callback/optimizater/adafactor.py | 18 | CODE | |
| LOW | code/chapter-9/c_transformer/c_train_curve_plot.py | 23 | CODE | |
| LOW | code/chapter-9/c_transformer/transformer/Models.py | 132 | CODE | |
| LOW | …de/chapter-8/03_detection/yolov5-master/00-save-gif.py | 54 | CODE | |
| LOW | code/chapter-8/03_detection/yolov5-master/val.py | 99 | CODE | |
| LOW | code/chapter-8/03_detection/yolov5-master/export.py | 311 | CODE | |
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| LOW | code/chapter-8/03_detection/yolov5-master/detect.py | 55 | CODE | |
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| LOW | …e/chapter-8/03_detection/yolov5-master/classify/val.py | 45 | CODE | |
| LOW | …apter-8/03_detection/yolov5-master/classify/predict.py | 56 | CODE | |
| LOW | …de/chapter-8/03_detection/yolov5-master/segment/val.py | 130 | CODE | |
| LOW | …hapter-8/03_detection/yolov5-master/segment/predict.py | 56 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 103 | CODE | |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 439 | CODE | |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 889 | CODE | |
| LOW | …er-8/03_detection/yolov5-master/utils/augmentations.py | 144 | CODE | |
| LOW | …er-8/03_detection/yolov5-master/utils/augmentations.py | 305 | CODE | |
| LOW | …3_detection/yolov5-master/utils/segment/dataloaders.py | 23 | CODE | |
| LOW | …3_detection/yolov5-master/utils/segment/dataloaders.py | 84 | CODE | |
| LOW | …detection/yolov5-master/utils/segment/augmentations.py | 25 | CODE | |
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| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 103 | CODE | |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 439 | CODE | |
| LOW | code/chapter-8/04_tracking/utils/general.py | 889 | CODE | |
| LOW | code/chapter-8/04_tracking/utils/augmentations.py | 144 | CODE | |
| LOW | code/chapter-8/04_tracking/utils/augmentations.py | 305 | CODE | |
| LOW | code/chapter-8/04_tracking/utils/segment/dataloaders.py | 23 | CODE | |
| LOW | code/chapter-8/04_tracking/utils/segment/dataloaders.py | 84 | CODE | |
| LOW | …e/chapter-8/04_tracking/utils/segment/augmentations.py | 25 | CODE | |
| LOW | …chapter-8/04_tracking/deep_sort/deep_sort/deep_sort.py | 14 | CODE | |
| LOW | …-8/07_image_captioning/clip_cap_base/my_utils/utils.py | 90 | CODE | |
| LOW | …/07_image_captioning/clip_cap_base/my_models/models.py | 147 | CODE | |
| LOW | …/07_image_captioning/clip_cap_base/my_models/models.py | 171 | CODE | |
| LOW | …e/chapter-8/07_image_captioning/cnn_rnn_base/models.py | 39 | CODE | |
| LOW | code/chapter-6/my_utils.py | 61 | CODE | |
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| LOW | code/chapter-2/02_COVID_19_cls.py | 97 | CODE | |
| LOW | code/chapter-5/02_sgd.py | 95 | CODE | |
| LOW | code/chapter-5/03_lr_scheduler.py | 97 | CODE |
| Severity | File | Line | Snippet | Context |
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| LOW | code/chapter-7/07_model_ensemble.py | 263 | # Print results on different ensemble methods | COMMENT |
| LOW | code/chapter-9/d_bert/run_ner_softmax.py | 62 | # Check if saved optimizer or scheduler states exist | COMMENT |
| LOW | code/chapter-9/d_bert/run_ner_softmax.py | 96 | # Check if continuing training from a checkpoint | COMMENT |
| LOW | code/chapter-9/d_bert/tools/plot.py | 52 | # Loop over data dimensions and create text annotations. | COMMENT |
| LOW | code/chapter-9/d_bert/models/layers/crf.py | 231 | # Set score to the next score if this timestep is valid (mask == 1) | COMMENT |
| LOW | code/chapter-9/d_bert/models/layers/crf.py | 294 | # Set score to the next score if this timestep is valid (mask == 1) | COMMENT |
| LOW | code/chapter-9/d_bert/models/layers/crf.py | 382 | # 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.py | 157 | # Print results | COMMENT |
| LOW | …de/chapter-8/03_detection/yolov5-master/00-save-gif.py | 209 | # Print results | COMMENT |
| LOW | code/chapter-8/03_detection/yolov5-master/val.py | 281 | # Print results | COMMENT |
| LOW | code/chapter-8/03_detection/yolov5-master/val.py | 287 | # Print results per class | COMMENT |
| LOW | code/chapter-8/03_detection/yolov5-master/detect.py | 158 | # Print results | COMMENT |
| LOW | code/chapter-8/03_detection/yolov5-master/detect.py | 210 | # Print results | COMMENT |
| LOW | code/chapter-8/03_detection/yolov5-master/benchmarks.py | 99 | # Print results | COMMENT |
| LOW | code/chapter-8/03_detection/yolov5-master/benchmarks.py | 136 | # Print results | COMMENT |
| LOW | …e/chapter-8/03_detection/yolov5-master/classify/val.py | 135 | # Print results | COMMENT |
| LOW | …apter-8/03_detection/yolov5-master/classify/predict.py | 140 | # Print results | COMMENT |
| LOW | …apter-8/03_detection/yolov5-master/classify/predict.py | 184 | # Print results | COMMENT |
| LOW | …de/chapter-8/03_detection/yolov5-master/segment/val.py | 344 | # Print results | COMMENT |
| LOW | …de/chapter-8/03_detection/yolov5-master/segment/val.py | 350 | # Print results per class | COMMENT |
| LOW | …hapter-8/03_detection/yolov5-master/segment/predict.py | 170 | # Print results | COMMENT |
| LOW | …hapter-8/03_detection/yolov5-master/segment/predict.py | 231 | # Print results | COMMENT |
| LOW | …hapter-8/03_detection/yolov5-master/utils/downloads.py | 17 | # Check if string is URL and check if URL exists | COMMENT |
| LOW | …/chapter-8/03_detection/yolov5-master/utils/general.py | 437 | # Check if environment supports image displays | COMMENT |
| LOW | …etection/yolov5-master/utils/loggers/comet/__init__.py | 157 | # Check if running the Experiment with the Comet Optimizer | COMMENT |
| LOW | …etection/yolov5-master/utils/loggers/comet/__init__.py | 433 | # Check if running Experiment with Comet Optimizer | COMMENT |
| LOW | …n/yolov5-master/utils/loggers/clearml/clearml_utils.py | 112 | # Set data to data_dict because wandb will crash without this information and opt is the best way | COMMENT |
| LOW | code/chapter-8/04_tracking/utils/downloads.py | 17 | # Check if string is URL and check if URL exists | COMMENT |
| LOW | code/chapter-8/04_tracking/utils/general.py | 437 | # Check if environment supports image displays | COMMENT |
| LOW | …/chapter-8/04_tracking/utils/loggers/comet/__init__.py | 157 | # Check if running the Experiment with the Comet Optimizer | COMMENT |
| LOW | …/chapter-8/04_tracking/utils/loggers/comet/__init__.py | 433 | # Check if running Experiment with Comet Optimizer | COMMENT |
| LOW | …r-8/04_tracking/utils/loggers/clearml/clearml_utils.py | 112 | # Set data to data_dict because wandb will crash without this information and opt is the best way | COMMENT |
| LOW | …chapter-8/07_image_captioning/cnn_rnn_base/01_train.py | 125 | # Check if there was an improvement | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | code/chapter-9/d_bert/02_predict_parse.py | 12 | def extract_entities_from_lines(test_data_path, predictions_path): | CODE |
| LOW | …_bert/tools/convert_albert_tf_checkpoint_to_pytorch.py | 14 | def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_file, pytorch_dump_path): | CODE |
| LOW | code/chapter-9/d_bert/processors/utils_ner.py | 6 | class DataProcessor(object): | CODE |
| LOW | code/chapter-9/d_bert/processors/ner_seq.py | 68 | def convert_examples_to_features(examples,label_list,max_seq_length,tokenizer, | CODE |
| LOW | code/chapter-9/d_bert/processors/ner_span.py | 64 | def convert_examples_to_features(examples,label_list,max_seq_length,tokenizer, | CODE |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 13 | def get_constant_schedule_with_warmup(optimizer, num_warmup_steps, last_epoch=-1): | CODE |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 25 | def get_linear_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, last_epoch=-1): | CODE |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 37 | def get_cosine_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, num_cycles=.5, last_epoch=-1): | CODE |
| LOW | code/chapter-9/d_bert/callback/lr_scheduler.py | 51 | def get_cosine_with_hard_restarts_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, num_cycles=1., l | CODE |
| LOW | code/chapter-9/c_transformer/transformer/Models.py | 32 | def _get_sinusoid_encoding_table(self, n_position, d_hid): | CODE |
| LOW | code/chapter-9/c_transformer/transformer/Translator.py | 60 | 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.py | 32 | def create_input_placeholders() -> typing.List[InferInput]: | CODE |
| LOW | …e/chapter-8/03_detection/yolov5-master/utils/triton.py | 44 | def create_input_placeholders() -> typing.List[InferInput]: | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 1197 | def create_classification_dataloader(path, | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 66 | def reshape_classifier_output(model, n=1000): | CODE |
| LOW | …pter-8/03_detection/yolov5-master/utils/torch_utils.py | 89 | def torch_distributed_zero_first(local_rank: int): | CODE |
| LOW | …8/03_detection/yolov5-master/utils/loggers/__init__.py | 151 | def on_pretrain_routine_start(self): | CODE |
| LOW | …etection/yolov5-master/utils/loggers/comet/__init__.py | 348 | def download_dataset_artifact(self, artifact_path): | CODE |
| LOW | …ction/yolov5-master/utils/loggers/comet/comet_utils.py | 19 | def download_model_checkpoint(opt, experiment): | CODE |
| LOW | …-8/03_detection/yolov5-master/utils/segment/metrics.py | 17 | def ap_per_class_box_and_mask( | CODE |
| LOW | code/chapter-8/03_detection/yolov5-master/models/tf.py | 554 | def representative_dataset_gen(dataset, ncalib=100): | CODE |
| LOW | code/chapter-8/05_cyclegan/util/visualizer.py | 107 | def create_visdom_connections(self): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/test_model.py | 12 | def modify_commandline_options(parser, is_train=True): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/template_model.py | 25 | def modify_commandline_options(parser, is_train=True): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/cycle_gan_model.py | 20 | def modify_commandline_options(parser, is_train=True): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/pix2pix_model.py | 17 | def modify_commandline_options(parser, is_train=True): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/colorization_model.py | 15 | def modify_commandline_options(parser, is_train=True): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/base_model.py | 47 | def modify_commandline_options(parser, is_train): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/base_model.py | 162 | def __patch_instance_norm_state_dict(self, state_dict, module, keys, i=0): | CODE |
| LOW | code/chapter-8/05_cyclegan/data/colorization_dataset.py | 16 | def modify_commandline_options(parser, is_train): | CODE |
| LOW | code/chapter-8/05_cyclegan/data/base_dataset.py | 33 | def modify_commandline_options(parser, is_train): | CODE |
| LOW | code/chapter-8/05_cyclegan/data/template_dataset.py | 22 | def modify_commandline_options(parser, is_train): | CODE |
| LOW | …apter-8/06_diffusion-model/DDPM/Diffusion/Diffusion.py | 71 | def predict_xt_prev_mean_from_eps(self, x_t, t, eps): | CODE |
| LOW | …model/DDPM/DiffusionFreeGuidence/DiffusionCondition.py | 68 | def predict_xt_prev_mean_from_eps(self, x_t, t, eps): | CODE |
| LOW | code/chapter-8/04_tracking/01-main.py | 125 | def get_currently_ids_by_area(tracks, bbox_area_list_, area_index): | CODE |
| LOW | code/chapter-8/04_tracking/utils/triton.py | 32 | def create_input_placeholders() -> typing.List[InferInput]: | CODE |
| LOW | code/chapter-8/04_tracking/utils/triton.py | 44 | def create_input_placeholders() -> typing.List[InferInput]: | CODE |
| LOW | code/chapter-8/04_tracking/utils/dataloaders.py | 1197 | def create_classification_dataloader(path, | CODE |
| LOW | code/chapter-8/04_tracking/utils/torch_utils.py | 66 | def reshape_classifier_output(model, n=1000): | CODE |
| LOW | code/chapter-8/04_tracking/utils/torch_utils.py | 89 | def torch_distributed_zero_first(local_rank: int): | CODE |
| LOW | code/chapter-8/04_tracking/utils/loggers/__init__.py | 151 | def on_pretrain_routine_start(self): | CODE |
| LOW | …/chapter-8/04_tracking/utils/loggers/comet/__init__.py | 348 | def download_dataset_artifact(self, artifact_path): | CODE |
| LOW | …apter-8/04_tracking/utils/loggers/comet/comet_utils.py | 19 | def download_model_checkpoint(opt, experiment): | CODE |
| LOW | code/chapter-8/04_tracking/utils/segment/metrics.py | 17 | def ap_per_class_box_and_mask( | CODE |
| LOW | code/chapter-8/04_tracking/models/tf.py | 554 | def representative_dataset_gen(dataset, ncalib=100): | CODE |
| LOW | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 358 | 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.py | 133 | def load_pretrained_embeddings(self, embeddings): | CODE |
| LOW | …ter-8/07_image_captioning/cnn_rnn_base/02_inference.py | 21 | def caption_image_beam_search(encoder, decoder, img, word_map, beam_size=3): | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 196 | Args: frame_id (int): timestamp (float): opencv captured frame time property R | STRING |
| HIGH | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 228 | Args: frame_id: bbox_id: Returns: bbox_id (int): Raises: | STRING |
| HIGH | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 246 | Args: frame_id (int): bbox_id (int): top (int): left (int): | STRING |
| HIGH | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 274 | Args: frame_id: bbox_id: category: confidence: the confidence v | STRING |
| HIGH | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 307 | Args: output_name: Returns: None Notes: It creates the js | STRING |
| HIGH | …e/chapter-8/04_tracking/deep_sort/utils/json_logger.py | 328 | 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.py | 369 | Notes: We use this function to output jsons whenever possible. like the time that we ex | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | code/chapter-9/a_rnn_lstm/models/rnn.py | 103 | # Create an instance of the RNNTextClassifier | COMMENT |
| MEDIUM | …pter-8/03_detection/yolov5-master/utils/dataloaders.py | 321 | # Create a new video capture object | COMMENT |
| MEDIUM | …hapter-8/03_detection/yolov5-master/utils/callbacks.py | 15 | # Define the available callbacks | COMMENT |
| MEDIUM | …de/chapter-8/03_detection/yolov5-master/models/yolo.py | 280 | # Create a YOLOv5 classification model from a YOLOv5 detection model | COMMENT |
| MEDIUM | …de/chapter-8/03_detection/yolov5-master/models/yolo.py | 295 | # Create a YOLOv5 classification model from a *.yaml file | COMMENT |
| MEDIUM | code/chapter-8/05_cyclegan/util/image_pool.py | 6 | """This class implements an image buffer that stores previously generated images. | STRING |
| MEDIUM | code/chapter-8/05_cyclegan/models/base_model.py | 9 | """This class is an abstract base class (ABC) for models. | STRING |
| MEDIUM | code/chapter-8/05_cyclegan/data/base_dataset.py | 1 | """This module implements an abstract base class (ABC) 'BaseDataset' for datasets. | STRING |
| MEDIUM | code/chapter-8/05_cyclegan/data/base_dataset.py | 14 | """This class is an abstract base class (ABC) for datasets. | STRING |
| MEDIUM | code/chapter-8/04_tracking/utils/dataloaders.py | 321 | # Create a new video capture object | COMMENT |
| MEDIUM | code/chapter-8/04_tracking/utils/callbacks.py | 15 | # Define the available callbacks | COMMENT |
| MEDIUM | code/chapter-8/04_tracking/models/yolo.py | 280 | # Create a YOLOv5 classification model from a YOLOv5 detection model | COMMENT |
| MEDIUM | code/chapter-8/04_tracking/models/yolo.py | 295 | # Create a YOLOv5 classification model from a *.yaml file | COMMENT |
| MEDIUM | …de/chapter-8/07_image_captioning/cnn_rnn_base/utils.py | 80 | # Create a base/root name for all output files | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | code/chapter-8/05_cyclegan/models/template_model.py | 57 | # you can use opt.isTrain to specify different behaviors for training and test. For example, some networks will | COMMENT |
| MEDIUM⚡ | code/chapter-8/05_cyclegan/models/template_model.py | 59 | # define networks; you can use opt.isTrain to specify different behaviors for training and test. | COMMENT |
| MEDIUM⚡ | code/chapter-8/05_cyclegan/models/template_model.py | 66 | # If two networks are updated at the same time, you can use itertools.chain to group them. See cycle_gan_mod | COMMENT |
| Severity | File | Line | Snippet | Context |
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| LOW | code/chapter-9/e_gpt/tokenizations/tokenization_bert.py | 27 | logger = logging.getLogger(__name__) | CODE |
| LOW | …-9/e_gpt/tokenizations/tokenization_bert_word_level.py | 28 | logger = logging.getLogger(__name__) | CODE |
| LOW | code/chapter-9/d_bert/processors/ner_seq.py | 8 | logger = logging.getLogger(__name__) | CODE |
| LOW | code/chapter-9/d_bert/processors/ner_span.py | 8 | logger = logging.getLogger(__name__) | CODE |
| LOW | code/chapter-9/c_transformer/transformer/__init__.py | 9 | __all__ = [ | CODE |
| LOW | …etection/yolov5-master/utils/loggers/comet/__init__.py | 8 | logger = logging.getLogger(__name__) | CODE |
| LOW | …ction/yolov5-master/utils/loggers/comet/comet_utils.py | 12 | logger = logging.getLogger(__name__) | CODE |
| LOW | …/03_detection/yolov5-master/utils/loggers/comet/hpo.py | 10 | logger = logging.getLogger(__name__) | CODE |
| LOW | …/chapter-8/04_tracking/utils/loggers/comet/__init__.py | 8 | logger = logging.getLogger(__name__) | CODE |
| LOW | …apter-8/04_tracking/utils/loggers/comet/comet_utils.py | 12 | logger = logging.getLogger(__name__) | CODE |
| LOW | code/chapter-8/04_tracking/utils/loggers/comet/hpo.py | 10 | logger = logging.getLogger(__name__) | CODE |
| LOW | …/chapter-8/04_tracking/deep_sort/deep_sort/__init__.py | 4 | __all__ = ['DeepSort', 'build_tracker'] | CODE |
| LOW | …chapter-8/04_tracking/deep_sort/deep_sort/deep_sort.py | 10 | __all__ = ['DeepSort'] | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | code/chapter-11/01_resnet_export_onnx.py | 18 | dummy_data = torch.randn((1, 3, 224, 224)) | CODE |
| LOW⚡ | code/chapter-11/01_resnet_export_onnx.py | 22 | torch.onnx.export(model, (dummy_data), "resnet50_bs_1.onnx", | CODE |
| LOW⚡ | code/chapter-11/01_resnet_export_onnx.py | 30 | torch.onnx.export(model, (dummy_data), "resnet50_bs_dynamic.onnx", | CODE |
| LOW | code/chapter-8/05_cyclegan/models/networks.py | 278 | def cal_gradient_penalty(netD, real_data, fake_data, device, type='mixed', constant=1.0, lambda_gp=10.0): | CODE |
| LOW | code/chapter-8/05_cyclegan/models/networks.py | 284 | fake_data (tensor array) -- generated images from the generator | STRING |
| LOW | code/chapter-8/05_cyclegan/models/networks.py | 296 | interpolatesv = fake_data | CODE |
| LOW | code/chapter-8/05_cyclegan/models/networks.py | 300 | interpolatesv = alpha * real_data + ((1 - alpha) * fake_data) | CODE |
| LOW | …e/chapter-8/01_classification/01_resnet_export_onnx.py | 34 | dummy_data = torch.randn((1, 3, 224, 224)) | CODE |
| LOW | …e/chapter-8/01_classification/01_resnet_export_onnx.py | 39 | torch.onnx.export(model, (dummy_data), path_out, | CODE |
| LOW | …/07_image_captioning/clip_cap_base/my_models/models.py | 168 | dummy_token = self.get_dummy_token(tokens.shape[0], tokens.device) | CODE |
| LOW | …/07_image_captioning/clip_cap_base/my_models/models.py | 169 | labels = torch.cat((dummy_token, tokens), dim=1) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | code/chapter-1/03-torch-compile-performance.py | 148 | # Step 1: Normalize the input arrays to have zero mean and unit variance | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 159 | # Step 2: Perform the tensor product followed by sum over last two dimensions | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 162 | # Step 3: Apply thresholding to clip values outside of [-1, 1] | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 165 | # Step 4: Apply exponential function for non-linearity | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 168 | # Step 5: Add a small regularization term to avoid overfitting | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | code/chapter-1/03-torch-compile-performance.py | 148 | # Step 1: Normalize the input arrays to have zero mean and unit variance | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 159 | # Step 2: Perform the tensor product followed by sum over last two dimensions | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 162 | # Step 3: Apply thresholding to clip values outside of [-1, 1] | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 165 | # Step 4: Apply exponential function for non-linearity | COMMENT |
| LOW⚡ | code/chapter-1/03-torch-compile-performance.py | 168 | # Step 5: Add a small regularization term to avoid overfitting | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | code/chapter-9/a_rnn_lstm/models/rnn.py | 96 | # Example usage | COMMENT |
| LOW | code/chapter-9/b_seq2seq/models/seq2seq.py | 137 | # Example usage | COMMENT |
| LOW | …hapter-8/03_detection/yolov5-master/utils/autobatch.py | 23 | # Usage: | COMMENT |
| LOW | …/chapter-8/03_detection/yolov5-master/models/common.py | 318 | # Usage: | COMMENT |
| LOW | code/chapter-8/04_tracking/utils/autobatch.py | 23 | # Usage: | COMMENT |
| LOW | code/chapter-8/04_tracking/models/common.py | 318 | # Usage: | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | code/chapter-6/04_cam_series_demo.py | 86 | # In this example grayscale_cam has only one image in the batch: | COMMENT |
| Severity | File | Line | Snippet | Context |
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| MEDIUM | …/chapter-8/03_detection/yolov5-master/models/common.py | 623 | # YOLOv5 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMS | COMMENT |
| MEDIUM | code/chapter-8/04_tracking/models/common.py | 623 | # YOLOv5 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMS | COMMENT |
| Severity | File | Line | Snippet | Context |
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| LOW | …er-8/03_detection/yolov5-master/utils/augmentations.py | 325 | # TODO: implement AugMix, AutoAug & RandAug in albumentation | COMMENT |
| LOW | code/chapter-8/04_tracking/utils/augmentations.py | 325 | # TODO: implement AugMix, AutoAug & RandAug in albumentation | COMMENT |
| Severity | File | Line | Snippet | Context |
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| HIGH | code/chapter-8/03_detection/yolov5-master/export.py | 41 | $ cd .. && git clone https://github.com/zldrobit/tfjs-yolov5-example.git && cd tfjs-yolov5-example | STRING |