ErrLookup › d2l-ai/d2l-zh
d2l-ai/d2l-zh
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。 · Python · 14 source files
Analyzed at e6b18ccea7 on 2026-08-14. 30 documented errors.
| Code / Message | Type | Severity | Tags |
|---|---|---|---|
| train_loss < 0.5 | validation | error | d2l, mxnet, assertion, training, convergence, fashion-mnist |
| train_acc <= 1 and train_acc > 0.7 | validation | error | d2l, mxnet, assertion, training, accuracy, convergence |
| test_acc <= 1 and test_acc > 0.7 | validation | error | d2l, mxnet, assertion, evaluation, generalization, fashion-mnist |
| f"{name} 不存在于 {DATA_HUB}" | validation | error | d2l, mxnet, assertion, dataset, data-hub, download |
| 只有zip/tar文件可以被解压缩 | validation | error | d2l, mxnet, assertion, archive, zip, tar, download |
| NotImplementedError | exception | error | d2l, mxnet, not-implemented, abstract-class, encoder-decoder, inheritance |
| X.shape[0] == y.shape[0] | validation | error | d2l, mxnet, assertion, multi-gpu, data-shape, batch |
| train_loss < 0.5 | validation | error | d2l, pytorch, assertion, training, convergence, fashion-mnist |
| train_acc <= 1 and train_acc > 0.7 | validation | error | d2l, pytorch, assertion, training, accuracy, convergence |
| test_acc <= 1 and test_acc > 0.7 | validation | error | d2l, pytorch, assertion, evaluation, generalization, fashion-mnist |
| f"{name} 不存在于 {DATA_HUB}" | validation | error | d2l, pytorch, assertion, dataset, data-hub, download |
| 只有zip/tar文件可以被解压缩 | validation | error | d2l, pytorch, assertion, archive, zip, tar, download |
| NotImplementedError | exception | error | d2l, pytorch, not-implemented, abstract-class, encoder-decoder, inheritance |
| X.shape[0] == y.shape[0] | validation | error | d2l, pytorch, assertion, multi-gpu, data-shape, batch |
| len(centers) == len(contexts) == len(negatives) | validation | error | d2l, word2vec, nlp, dataset, assertion, pytorch |
| train_loss < 0.5 | validation | error | d2l, tensorflow, training, softmax-regression, assertion, hyperparameters |
| train_acc <= 1 and train_acc > 0.7 | validation | error | d2l, tensorflow, training, accuracy, assertion |
| test_acc <= 1 and test_acc > 0.7 | validation | error | d2l, tensorflow, training, evaluation, assertion |
| f"{name} 不存在于 {DATA_HUB}" | validation | error | d2l, tensorflow, download, data-hub, kaggle, assertion |
| 只有zip/tar文件可以被解压缩 | validation | error | d2l, tensorflow, download, archive, zip, tar, assertion |
| NotImplementedError | exception | error | d2l, tensorflow, encoder-decoder, abstract-class, notimplementederror |
| train_loss < 0.5 | validation | error | d2l, paddle, training, softmax-regression, assertion, hyperparameters |
| train_acc <= 1 and train_acc > 0.7 | validation | error | d2l, paddle, training, accuracy, assertion |
| test_acc <= 1 and test_acc > 0.7 | validation | error | d2l, paddle, training, evaluation, assertion |
| f"{name} 不存在于 {DATA_HUB}" | validation | error | d2l, paddle, download, data-hub, kaggle, assertion |
| 只有zip/tar文件可以被解压缩 | validation | error | d2l, paddle, download, archive, zip, tar, assertion |
| NotImplementedError | exception | error | d2l, paddle, encoder-decoder, abstract-class, notimplementederror |
| X.shape[0] == y.shape[0] | validation | error | d2l, paddle, multi-gpu, data-loading, assertion, batching |
| len(centers) == len(contexts) == len(negatives) | validation | error | assertion, data-validation, word2vec, nlp, paddlepaddle |
| Only zip/tar files can be extracted | validation | error | file-format, download, pretrained-embeddings, assertion, mxnet-gluon |