协作错误：错误：命令错误，退出状态 1：python setup.py Egg_info

Question

我正在运行以下命令!pip install bert-tensorflow natural-questions，它给了我错误：

Collecting bert-tensorflow

  Using cached https://files.pythonhosted.org/packages/20/16/0f9376af49c6adcfbaf2470a8f500105a74dd803aa54ac0110af445837b5/bert_tensorflow-1.0.4-py2.py3-none-any.whl

Collecting natural-questions

  Using cached https://files.pythonhosted.org/packages/d5/d7/020da0200e8129c0ae7a1da998c7ff84dd2f3a4660711b2aa39286c67f85/natural_questions-1.0.4-py2.py3-none-any.whl

Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from bert-tensorflow) (1.15.0)

Requirement already satisfied: tornado in /usr/local/lib/python3.6/dist-packages (from natural-questions) (5.1.1)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.6/dist-packages (from natural-questions) (2.11.2)

Collecting wsgiref

  Using cached https://files.pythonhosted.org/packages/41/9e/309259ce8dff8c596e8c26df86dbc4e848b9249fd36797fd60be456f03fc/wsgiref-0.1.2.zip

ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.

我正在谷歌合作实验室工作。谢谢

Answer 1

sudo pip3 install --upgrade pip setuptools wheel尝试使用这个，它可能会起作用

Answer 2

现在当我跑步时：python -m language.question_answering.bert_joint.prepare_nq_data \  --logtostderr \  --input_jsonl ~/data/nq-train-??.jsonl.gz \  --output_tfrecord ~/output_dir/nq-train.tfrecords-00000-of-00001 \  --max_seq_length=512 \  --include_unknowns=0.02 \  --vocab_file=bert-joint-baseline/vocab-nq.txt它给了我错误：/usr/bin/python3: Error while finding module specification for 'language.question_answering.bert_joint.prepare_nq_data' (ModuleNotFoundError: No module named 'language')在我也运行gsutil cp -R gs://bert-nq/bert-joint-baseline .没有错误之前

Answer 3

问题似乎出在wsgiref，它已经安装但pip尝试重新安装。尝试分别安装 2 个库，如下所示%pip install bert-tensorflow%pip install --no-dependencies natural-questions稍后，如果您对 的任何依赖项有任何问题natural-questions，请尝试手动安装。例如对于稍后的问题使用%pip install language

Answer 4

安装 wsgiref 时出错，但它已经安装在 python3 中。也尝试在 colab 中使用 python2 看看它是否有效