利用conda install TensorFlow-gpu在win7上conda3.7版本上安装tensorflow后,测试时出现下面的问题

在测试import TensorFlow as tf
print('hello'),出现下列问题,请问这是什么原因造成的,如何改?

Traceback (most recent call last):
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import
    module = self._system_import(name, *args, **kwargs)
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "D:\ProgramData\Anaconda3\lib\imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "D:\ProgramData\Anaconda3\lib\imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: DLL load failed: 找不到指定的程序。
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
  File "D:\ProgramData\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3296, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-d1ce02c95f3b>", line 1, in <module>
    runfile('C:/Users/jianjiu17/Desktop/deep-learning-from-scratch-master/uittle.py', wdir='C:/Users/jianjiu17/Desktop/deep-learning-from-scratch-master')
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_bundle\pydev_umd.py", line 197, in runfile
    pydev_imports.execfile(filename, global_vars, local_vars)  # execute the script
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "C:/Users/jianjiu17/Desktop/deep-learning-from-scratch-master/uittle.py", line 1, in <module>
    import tensorflow as tf
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import
    module = self._system_import(name, *args, **kwargs)
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\__init__.py", line 24, in <module>
    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import
    module = self._system_import(name, *args, **kwargs)
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\__init__.py", line 49, in <module>
    from tensorflow.python import pywrap_tensorflow
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import
    module = self._system_import(name, *args, **kwargs)
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 74, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "D:\Program Files\JetBrains\PyCharm 2019.1.3\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import
    module = self._system_import(name, *args, **kwargs)
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "D:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "D:\ProgramData\Anaconda3\lib\imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "D:\ProgramData\Anaconda3\lib\imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: DLL load failed: 找不到指定的程序。
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

1个回答

jianjiu7
jianjiu17 感谢你的回答,但是我想应该不是cuda的版本问题,我不是采用这种一个一个模块单独安装,而是采用conda来安装tf,这种方法会自动安装匹配的cuda和cudann,我之前在台式机是可以的,现在在笔记本安装有问题
5 个月之前 回复
Csdn user default icon
上传中...
上传图片
插入图片
抄袭、复制答案,以达到刷声望分或其他目的的行为,在CSDN问答是严格禁止的,一经发现立刻封号。是时候展现真正的技术了!
其他相关推荐
conda安装librosa报错LinkError: post-link script failed for package conda-forge::qt?
(tensorflow-gpu) C:\Users\AnnJune>conda install -c conda-forge librosa Collecting package metadata: done Solving environment: \ The environment is inconsistent, please check the package plan carefully The following packages are causing the inconsistency: - conda-forge/noarch::librosa==0.6.3=py_0 - conda-forge/win-64::matplotlib==3.1.0=py36_1 - conda-forge/win-64::matplotlib-base==3.1.0=py36h2852a4a_1 - defaults/win-64::numba==0.39.0=py36h830ac7b_0 - conda-forge/win-64::pyqt==5.6.0=py36h764d66f_1008 - conda-forge/noarch::resampy==0.2.1=py_1 - conda-forge/win-64::scikit-learn==0.21.2=py36h0ff8352_0 - defaults/win-64::scipy==1.2.1=py36h29ff71c_0 done ## Package Plan ## environment location: C:\Users\AnnJune\Anaconda3\envs\tensorflow-gpu added / updated specs: - librosa The following packages will be downloaded: package | build ---------------------------|----------------- certifi-2019.3.9 | py36_0 149 KB conda-forge icu-58.1 | vc14_0 11.3 MB conda-forge llvmlite-0.28.0 | py36_0 12.5 MB conda-forge numba-0.43.1 | py36hf9181ef_0 2.8 MB defaults openssl-1.1.1b | hfa6e2cd_2 4.8 MB conda-forge pyqt-5.9.2 | py36h6538335_0 4.3 MB conda-forge qt-5.9.7 | hc6833c9_1 91.1 MB conda-forge sip-4.19.8 |py36h6538335_1000 281 KB conda-forge ------------------------------------------------------------ Total: 127.1 MB The following NEW packages will be INSTALLED: audioread conda-forge/win-64::audioread-2.1.6-py36_0 blas pkgs/main/win-64::blas-1.0-mkl ca-certificates conda-forge/win-64::ca-certificates-2019.3.9-hecc5488_0 cycler conda-forge/noarch::cycler-0.10.0-py_1 decorator conda-forge/noarch::decorator-4.4.0-py_0 freetype conda-forge/win-64::freetype-2.10.0-h5db478b_0 icc_rt pkgs/main/win-64::icc_rt-2019.0.0-h0cc432a_1 icu conda-forge/win-64::icu-58.1-vc14_0 intel-openmp pkgs/main/win-64::intel-openmp-2019.3-203 joblib conda-forge/noarch::joblib-0.13.2-py_0 jpeg conda-forge/win-64::jpeg-9c-hfa6e2cd_1001 kiwisolver conda-forge/win-64::kiwisolver-1.1.0-py36he980bc4_0 libblas conda-forge/win-64::libblas-3.8.0-10_mkl libcblas conda-forge/win-64::libcblas-3.8.0-10_mkl liblapack conda-forge/win-64::liblapack-3.8.0-10_mkl libpng conda-forge/win-64::libpng-1.6.37-h7602738_0 llvmlite conda-forge/win-64::llvmlite-0.28.0-py36_0 mkl pkgs/main/win-64::mkl-2019.3-203 numpy conda-forge/win-64::numpy-1.16.3-py36h873a0b8_0 openssl conda-forge/win-64::openssl-1.1.1b-hfa6e2cd_2 pyparsing conda-forge/noarch::pyparsing-2.4.0-py_0 python-dateutil conda-forge/noarch::python-dateutil-2.8.0-py_0 qt conda-forge/win-64::qt-5.9.7-hc6833c9_1 sip conda-forge/win-64::sip-4.19.8-py36h6538335_1000 six conda-forge/win-64::six-1.12.0-py36_1000 tornado conda-forge/win-64::tornado-6.0.2-py36hfa6e2cd_0 zlib conda-forge/win-64::zlib-1.2.11-h2fa13f4_1004 The following packages will be UPDATED: numba 0.39.0-py36h830ac7b_0 --> 0.43.1-py36hf9181ef_0 pyqt 5.6.0-py36h764d66f_1008 --> 5.9.2-py36h6538335_0 The following packages will be SUPERSEDED by a higher-priority channel: certifi pkgs/main --> conda-forge Proceed ([y]/n)? y Downloading and Extracting Packages openssl-1.1.1b | 4.8 MB | ############################################################################ | 100% numba-0.43.1 | 2.8 MB | ############################################################################ | 100% pyqt-5.9.2 | 4.3 MB | ############################################################################ | 100% llvmlite-0.28.0 | 12.5 MB | ############################################################################ | 100% qt-5.9.7 | 91.1 MB | ############################################################################ | 100% certifi-2019.3.9 | 149 KB | ############################################################################ | 100% icu-58.1 | 11.3 MB | ############################################################################ | 100% sip-4.19.8 | 281 KB | ############################################################################ | 100% Preparing transaction: done Verifying transaction: done Executing transaction: \ ERROR conda.core.link:_execute_post_link_actions(658): An error occurred while installing package 'conda-forge::qt-5.9.7-hc6833c9_1'. LinkError: post-link script failed for package conda-forge::qt-5.9.7-hc6833c9_1 running your command again with `-v` will provide additional information location of failed script: C:\Users\AnnJune\Anaconda3\envs\tensorflow-gpu\Scripts\.qt-post-link.bat ==> script messages <== <None> Attempting to roll back. failed ERROR conda.core.link:_execute(568): An error occurred while installing package 'conda-forge::qt-5.9.7-hc6833c9_1'. LinkError: post-link script failed for package conda-forge::qt-5.9.7-hc6833c9_1 running your command again with `-v` will provide additional information location of failed script: C:\Users\AnnJune\Anaconda3\envs\tensorflow-gpu\Scripts\.qt-post-link.bat ==> script messages <== <None> Attempting to roll back. Rolling back transaction: done LinkError: post-link script failed for package conda-forge::qt-5.9.7-hc6833c9_1 running your command again with `-v` will provide additional information location of failed script: C:\Users\AnnJune\Anaconda3\envs\tensorflow-gpu\Scripts\.qt-post-link.bat ==> script messages <== <None>
更新conda update scikit-learn的问题
各位,我想请教下,我在更新conda update scikit-learn的时候出错了: ERROR conda.core.link:_execute_actions(337): An error occurred while installing package 'defaults::tqdm-4.40.0-py_0'. CondaError: Cannot link a source that does not exist. C:\Users\86186\Anaconda3\Scripts\conda.exe Running `conda clean --packages` may resolve your problem. Attempting to roll back. CondaError: Cannot link a source that does not exist. C:\Users\86186\Anaconda3\Scripts\conda.exe Running `conda clean --packages` may resolve your problem. 请问如何解决呢,感谢!感谢!
conda update --all 失败
我想升级numpy,原先先后尝试conda update --all 以及conda update numpy,是可以的,但都因为网络还是什么原因中断了,两个命令都尝试了两次,都中断了。 后来过了一会,我再尝试conda update --all 以及conda update numpy,失败了,报错,报错原因都差不多,以下是conda update --all的报错代码,请各位大佬救救我,小白我万分感谢 ``` (base) C:\Users\RZW>conda update --all # >>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<< Traceback (most recent call last): File "D:\Program files\Anaconda\lib\site-packages\libarchive\ffi.py", line 55, in <module> libarchive = ctypes.cdll.LoadLibrary(libarchive_path) File "D:\Program files\Anaconda\lib\ctypes\__init__.py", line 434, in LoadLibrary return self._dlltype(name) File "D:\Program files\Anaconda\lib\ctypes\__init__.py", line 356, in __init__ self._handle = _dlopen(self._name, mode) OSError: [WinError 126] 找不到指定的模块。 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "D:\Program files\Anaconda\lib\site-packages\conda\exceptions.py", line 1062, in __call__ return func(*args, **kwargs) File "D:\Program files\Anaconda\lib\site-packages\conda\cli\main.py", line 84, in _main exit_code = do_call(args, p) File "D:\Program files\Anaconda\lib\site-packages\conda\cli\conda_argparse.py", line 82, in do_call exit_code = getattr(module, func_name)(args, parser) File "D:\Program files\Anaconda\lib\site-packages\conda\cli\main_update.py", line 20, in execute install(args, parser, 'update') File "D:\Program files\Anaconda\lib\site-packages\conda\cli\install.py", line 116, in install if context.use_only_tar_bz2: File "D:\Program files\Anaconda\lib\site-packages\conda\base\context.py", line 664, in use_only_tar_bz2 import conda_package_handling.api File "D:\Program files\Anaconda\lib\site-packages\conda_package_handling\api.py", line 3, in <module> from libarchive.exception import ArchiveError as _LibarchiveArchiveError File "D:\Program files\Anaconda\lib\site-packages\libarchive\__init__.py", line 1, in <module> from .entry import ArchiveEntry File "D:\Program files\Anaconda\lib\site-packages\libarchive\entry.py", line 6, in <module> from . import ffi File "D:\Program files\Anaconda\lib\site-packages\libarchive\ffi.py", line 57, in <module> raise ImportError("Failed to load libarchive library from %s - are any dependencies missing?" ImportError: Failed to load libarchive library from %s - are any dependencies missing?Is your environment activated? `$ D:\Program files\Anaconda\Scripts\conda-script.py update --all` environment variables: CIO_TEST=<not set> CONDA_DEFAULT_ENV=base CONDA_EXE=D:\Program files\Anaconda\condabin\..\Scripts\conda.exe CONDA_EXES="D:\Program files\Anaconda\condabin\..\Scripts\conda.exe" CONDA_PREFIX=D:\Program files\Anaconda CONDA_PROMPT_MODIFIER=(base) CONDA_PYTHON_EXE=D:\Program files\Anaconda\python.exe CONDA_ROOT=D:\Program files\Anaconda CONDA_SHLVL=1 HOMEPATH=\Users\RZW MOZ_PLUGIN_PATH=D:\Program files\Zeon\Gaaiho\Gaaiho Reader\Bin PATH=D:\Program files\Anaconda\Library\bin;D:\Program files\Anaconda;D:\Program files\Anaconda\Library\mingw-w64\bin;D:\Program files\Anaconda\Library\usr\bin;D:\Program files\Anaconda\Library\bin;D:\Program files\Anaconda\Scripts;D:\Program files\Anaconda\bin;D:\Program files\Anaconda;D:\Program files\Anaconda\Library\mingw-w64\bin;D:\Program files\Anaconda\Library\usr\bin;D:\Program files\Anaconda\Library\bin;D:\Program files\Anaconda\Scripts;D:\Program files\Anaconda\bin;D:\Program files\ Anaconda\condabin;C:\Windows\system32;C:\Windows;C:\Windows\System32\W bem;C:\Windows\System32\WindowsPowerShell\v1.0\锛汥:\Program files\Anaconda锛汥:\Program files\Anaconda\Scripts锛汥:\Program files\Anaconda\envs\tensorflow\Lib\site-packages;D:\Program files\Anaconda\Library\bin;D:\Program files\Anaconda;D:\Program files\Anaconda\Library\mingw-w64\bin;D:\Program files\Anaconda\Library\usr\bin;D:\Program files\Anaconda\Library\bin;D:\Program files\Anaconda\Scripts;D:\Program files PSMODULEPATH=C:\Windows\system32\WindowsPowerShell\v1.0\Modules\ REQUESTS_CA_BUNDLE=<not set> SSL_CERT_FILE=<not set> active environment : base active env location : D:\Program files\Anaconda shell level : 1 user config file : C:\Users\RZW\.condarc populated config files : C:\Users\RZW\.condarc conda version : 4.7.11 conda-build version : 3.18.8 python version : 3.7.3.final.0 virtual packages : base environment : D:\Program files\Anaconda (writable) channel URLs : https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/win-64 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/noarch https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/win-64 https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/noarch https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/win-64 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/noarch https://repo.anaconda.com/pkgs/main/win-64 https://repo.anaconda.com/pkgs/main/noarch https://repo.anaconda.com/pkgs/r/win-64 https://repo.anaconda.com/pkgs/r/noarch https://repo.anaconda.com/pkgs/msys2/win-64 https://repo.anaconda.com/pkgs/msys2/noarch package cache : D:\Program files\Anaconda\pkgs C:\Users\RZW\.conda\pkgs C:\Users\RZW\AppData\Local\conda\conda\pkgs envs directories : D:\Program files\Anaconda\envs C:\Users\RZW\.conda\envs C:\Users\RZW\AppData\Local\conda\conda\envs platform : win-64 user-agent : conda/4.7.11 requests/2.22.0 CPython/3.7.3 Windows/10 Windows/10.0.10240 administrator : False netrc file : None offline mode : False An unexpected error has occurred. Conda has prepared the above report. If submitted, this report will be used by core maintainers to improve future releases of conda. Would you like conda to send this report to the core maintainers? [y/N]: ```
用conda安装pytorch时出现以下错误,该怎么改吖
Collecting package metadata (current_repodata.json): done Solving environment: / The environment is inconsistent, please check the package plan carefully The following packages are causing the inconsistency: - defaults/win-64::tensorflow==1.14.0=gpu_py37h5512b17_0 - defaults/noarch::tensorflow-estimator==1.14.0=py_0 - defaults/win-64::tensorflow-gpu==1.14.0=h0d30ee6_0 failed with initial frozen solve. Retrying with flexible solve. Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
conda安装python-graphviz报错:
用conda安装python-graphviz时报错:CondaError: Cannot link a source that does not exist. C:\ProgramData\Anaconda3\Scripts\conda.exe 代码片段如下 ``` pip-19.1.1-py3 100% |###############################| Time: 0:00:03 590.55 kB/s ERROR conda.core.link:_execute_actions(337): An error occurred while installing package 'defaults::tqdm-4.32.1-py_0'. CondaError: Cannot link a source that does not exist. C:\ProgramData\Anaconda3\Scripts\conda.exe Attempting to roll back. CondaError: Cannot link a source that does not exist. C:\ProgramData\Anaconda3\Scripts\conda.exe ``` 求助如何解决
pip / conda install 报 SSLError
# 我想安装 pycurl 库一直报ssl的错 **安装其他库也报这个错 我python 和 anacoda 卸载重装还是这样** ![图片说明](https://img-ask.csdn.net/upload/201912/29/1577603682_113807.png) ![图片说明](https://img-ask.csdn.net/upload/201912/29/1577603787_388466.png) **网上查到说添加环境变量 添加了但还是不行** anacoda 安装文件夹是anacode (新建文件夹的时候打错了) Python 3.7.6 windows 10 系统 大佬们知道什么原因吗? ``` 错误文本: pip install pycurl WARNING: pip is configured with locations that require TLS/SSL, however the ssl module in Python is not available. Requirement already satisfied: pycurl in d:\anacode\lib\site-packages (7.43.0.3) WARNING: pip is configured with locations that require TLS/SSL, however the ssl module in Python is not available. Could not fetch URL https://pypi.org/simple/pip/: There was a problem confirming the ssl certificate: HTTPSConnectionPool(host='pypi.org', port=443): Max retries exceeded with url: /simple/pip/ (Caused by SSLError("Can't connect to HTTPS URL because the SSL module is not available.")) - skipping C:\Users\Enz>conda install scrapy Collecting package metadata (current_repodata.json): failed CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://repo.anaconda.com/pkgs/main/win-64/current_repodata.json> Elapsed: - An HTTP error occurred when trying to retrieve this URL. HTTP errors are often intermittent, and a simple retry will get you on your way. If your current network has https://www.anaconda.com blocked, please file a support request with your network engineering team. SSLError(MaxRetryError('HTTPSConnectionPool(host=\'repo.anaconda.com\', port=443): Max retries exceeded with url: /pkgs/main/win-64/current_repodata.json (Caused by SSLError("Can\'t connect to HTTPS URL because the SSL module is not available."))')) ```
anaconda 安装已经下载好的包 如何安装
anaconda 安装已经下载好的包 如何安装? conda install --user-local jdk-7u79-linux-x64.tar.gz 提示找不到包
ubuntu系统,pip install conda后报错
1.在ubuntu系统下,安装了anaconda,然后在ubuntu系统下打开命令窗,输入conda,一切正常。 2.但是打开anaconda平台,进入其中一个环境(environment),右键打开terminal,输入conda,报错:The install method you used for conda--probably either `pip install conda` or `easy_install conda`--is not compatible with using conda as an application.
Tensorflow测试训练styleGAN时报错 No OpKernel was registered to support Op 'NcclAllReduce' with these attrs.
在测试官方StyleGAN。 运行官方与训练模型pretrained_example.py generate_figures.py 没有问题。GPU工作正常。 运行train.py时报错 尝试只用单个GPU训练时没有报错。 NcclAllReduce应该跟多GPU通信有关,不太了解。 InvalidArgumentError (see above for traceback): No OpKernel was registered to support Op 'NcclAllReduce' with these attrs. Registered devices: [CPU,GPU], Registered kernels: <no registered kernels> [[Node: TrainD/SumAcrossGPUs/NcclAllReduce = NcclAllReduce[T=DT_FLOAT, num_devices=2, reduction="sum", shared_name="c112", _device="/device:GPU:0"](GPU0/TrainD_grad/gradients/AddN_160)]] 经过多番google 尝试过 重启 conda install keras-gpu 重新安装tensorflow-gpu==1.10.0(跟官方版本保持一致) ``` …… Building TensorFlow graph... Setting up snapshot image grid... Setting up run dir... Training... Traceback (most recent call last): File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 1278, in _do_call return fn(*args) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 1263, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _call_tf_sessionrun run_metadata) tensorflow.python.framework.errors_impl.InvalidArgumentError: No OpKernel was registered to support Op 'NcclAllReduce' with these attrs. Registered devices: [CPU,GPU], Registered kernels: <no registered kernels> [[Node: TrainD/SumAcrossGPUs/NcclAllReduce = NcclAllReduce[T=DT_FLOAT, num_devices=2, reduction="sum", shared_name="c112", _device="/device:GPU:0"](GPU0/TrainD_grad/gradients/AddN_160)]] During handling of the above exception, another exception occurred: Traceback (most recent call last): File "train.py", line 191, in <module> main() File "train.py", line 186, in main dnnlib.submit_run(**kwargs) File "E:\MachineLearning\stylegan-master\dnnlib\submission\submit.py", line 290, in submit_run run_wrapper(submit_config) File "E:\MachineLearning\stylegan-master\dnnlib\submission\submit.py", line 242, in run_wrapper util.call_func_by_name(func_name=submit_config.run_func_name, submit_config=submit_config, **submit_config.run_func_kwargs) File "E:\MachineLearning\stylegan-master\dnnlib\util.py", line 257, in call_func_by_name return func_obj(*args, **kwargs) File "E:\MachineLearning\stylegan-master\training\training_loop.py", line 230, in training_loop tflib.run([D_train_op, Gs_update_op], {lod_in: sched.lod, lrate_in: sched.D_lrate, minibatch_in: sched.minibatch}) File "E:\MachineLearning\stylegan-master\dnnlib\tflib\tfutil.py", line 26, in run return tf.get_default_session().run(*args, **kwargs) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 877, in run run_metadata_ptr) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 1100, in _run feed_dict_tensor, options, run_metadata) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 1272, in _do_run run_metadata) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\client\session.py", line 1291, in _do_call raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InvalidArgumentError: No OpKernel was registered to support Op 'NcclAllReduce' with these attrs. Registered devices: [CPU,GPU], Registered kernels: <no registered kernels> [[Node: TrainD/SumAcrossGPUs/NcclAllReduce = NcclAllReduce[T=DT_FLOAT, num_devices=2, reduction="sum", shared_name="c112", _device="/device:GPU:0"](GPU0/TrainD_grad/gradients/AddN_160)]] Caused by op 'TrainD/SumAcrossGPUs/NcclAllReduce', defined at: File "train.py", line 191, in <module> main() File "train.py", line 186, in main dnnlib.submit_run(**kwargs) File "E:\MachineLearning\stylegan-master\dnnlib\submission\submit.py", line 290, in submit_run run_wrapper(submit_config) File "E:\MachineLearning\stylegan-master\dnnlib\submission\submit.py", line 242, in run_wrapper util.call_func_by_name(func_name=submit_config.run_func_name, submit_config=submit_config, **submit_config.run_func_kwargs) File "E:\MachineLearning\stylegan-master\dnnlib\util.py", line 257, in call_func_by_name return func_obj(*args, **kwargs) File "E:\MachineLearning\stylegan-master\training\training_loop.py", line 185, in training_loop D_train_op = D_opt.apply_updates() File "E:\MachineLearning\stylegan-master\dnnlib\tflib\optimizer.py", line 135, in apply_updates g = nccl_ops.all_sum(g) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\contrib\nccl\python\ops\nccl_ops.py", line 49, in all_sum return _apply_all_reduce('sum', tensors) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\contrib\nccl\python\ops\nccl_ops.py", line 230, in _apply_all_reduce shared_name=shared_name)) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\contrib\nccl\ops\gen_nccl_ops.py", line 59, in nccl_all_reduce num_devices=num_devices, shared_name=shared_name, name=name) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\util\deprecation.py", line 454, in new_func return func(*args, **kwargs) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\framework\ops.py", line 3156, in create_op op_def=op_def) File "d:\Users\admin\Anaconda3\envs\tfenv\lib\site-packages\tensorflow\python\framework\ops.py", line 1718, in __init__ self._traceback = tf_stack.extract_stack() InvalidArgumentError (see above for traceback): No OpKernel was registered to support Op 'NcclAllReduce' with these attrs. Registered devices: [CPU,GPU], Registered kernels: <no registered kernels> [[Node: TrainD/SumAcrossGPUs/NcclAllReduce = NcclAllReduce[T=DT_FLOAT, num_devices=2, reduction="sum", shared_name="c112", _device="/device:GPU:0"](GPU0/TrainD_grad/gradients/AddN_160)]] ``` ``` #conda list: # Name Version Build Channel _tflow_select 2.1.0 gpu absl-py 0.8.1 pypi_0 pypi alabaster 0.7.12 py36_0 asn1crypto 1.2.0 py36_0 astor 0.8.0 pypi_0 pypi astroid 2.3.2 py36_0 attrs 19.3.0 py_0 babel 2.7.0 py_0 backcall 0.1.0 py36_0 blas 1.0 mkl bleach 3.1.0 py36_0 ca-certificates 2019.10.16 0 certifi 2019.9.11 py36_0 cffi 1.13.1 py36h7a1dbc1_0 chardet 3.0.4 py36_1003 cloudpickle 1.2.2 py_0 colorama 0.4.1 py36_0 cryptography 2.8 py36h7a1dbc1_0 cudatoolkit 9.0 1 cudnn 7.6.4 cuda9.0_0 decorator 4.4.1 py_0 defusedxml 0.6.0 py_0 django 2.2.7 pypi_0 pypi docutils 0.15.2 py36_0 entrypoints 0.3 py36_0 gast 0.3.2 py_0 grpcio 1.25.0 pypi_0 pypi h5py 2.9.0 py36h5e291fa_0 hdf5 1.10.4 h7ebc959_0 icc_rt 2019.0.0 h0cc432a_1 icu 58.2 ha66f8fd_1 idna 2.8 pypi_0 pypi image 1.5.27 pypi_0 pypi imagesize 1.1.0 py36_0 importlib_metadata 0.23 py36_0 intel-openmp 2019.4 245 ipykernel 5.1.3 py36h39e3cac_0 ipython 7.9.0 py36h39e3cac_0 ipython_genutils 0.2.0 py36h3c5d0ee_0 isort 4.3.21 py36_0 jedi 0.15.1 py36_0 jinja2 2.10.3 py_0 jpeg 9b hb83a4c4_2 jsonschema 3.1.1 py36_0 jupyter_client 5.3.4 py36_0 jupyter_core 4.6.1 py36_0 keras-applications 1.0.8 py_0 keras-base 2.2.4 py36_0 keras-gpu 2.2.4 0 keras-preprocessing 1.1.0 py_1 keyring 18.0.0 py36_0 lazy-object-proxy 1.4.3 py36he774522_0 libpng 1.6.37 h2a8f88b_0 libprotobuf 3.9.2 h7bd577a_0 libsodium 1.0.16 h9d3ae62_0 markdown 3.1.1 py36_0 markupsafe 1.1.1 py36he774522_0 mccabe 0.6.1 py36_1 mistune 0.8.4 py36he774522_0 mkl 2019.4 245 mkl-service 2.3.0 py36hb782905_0 mkl_fft 1.0.15 py36h14836fe_0 mkl_random 1.1.0 py36h675688f_0 more-itertools 7.2.0 py36_0 nbconvert 5.6.1 py36_0 nbformat 4.4.0 py36h3a5bc1b_0 numpy 1.17.3 py36h4ceb530_0 numpy-base 1.17.3 py36hc3f5095_0 numpydoc 0.9.1 py_0 openssl 1.1.1d he774522_3 packaging 19.2 py_0 pandoc 2.2.3.2 0 pandocfilters 1.4.2 py36_1 parso 0.5.1 py_0 pickleshare 0.7.5 py36_0 pillow 6.2.1 pypi_0 pypi pip 19.3.1 py36_0 prompt_toolkit 2.0.10 py_0 protobuf 3.10.0 pypi_0 pypi psutil 5.6.3 py36he774522_0 pycodestyle 2.5.0 py36_0 pycparser 2.19 py36_0 pyflakes 2.1.1 py36_0 pygments 2.4.2 py_0 pylint 2.4.3 py36_0 pyopenssl 19.0.0 py36_0 pyparsing 2.4.2 py_0 pyqt 5.9.2 py36h6538335_2 pyreadline 2.1 py36_1 pyrsistent 0.15.4 py36he774522_0 pysocks 1.7.1 py36_0 python 3.6.9 h5500b2f_0 python-dateutil 2.8.1 py_0 pytz 2019.3 py_0 pywin32 223 py36hfa6e2cd_1 pyyaml 5.1.2 py36he774522_0 pyzmq 18.1.0 py36ha925a31_0 qt 5.9.7 vc14h73c81de_0 qtawesome 0.6.0 py_0 qtconsole 4.5.5 py_0 qtpy 1.9.0 py_0 requests 2.22.0 py36_0 rope 0.14.0 py_0 scipy 1.3.1 py36h29ff71c_0 setuptools 39.1.0 pypi_0 pypi sip 4.19.8 py36h6538335_0 six 1.13.0 pypi_0 pypi snowballstemmer 2.0.0 py_0 sphinx 2.2.1 py_0 sphinxcontrib-applehelp 1.0.1 py_0 sphinxcontrib-devhelp 1.0.1 py_0 sphinxcontrib-htmlhelp 1.0.2 py_0 sphinxcontrib-jsmath 1.0.1 py_0 sphinxcontrib-qthelp 1.0.2 py_0 sphinxcontrib-serializinghtml 1.1.3 py_0 spyder 3.3.6 py36_0 spyder-kernels 0.5.2 py36_0 sqlite 3.30.1 he774522_0 sqlparse 0.3.0 pypi_0 pypi tensorboard 1.10.0 py36he025d50_0 tensorflow 1.10.0 gpu_py36h3514669_0 tensorflow-base 1.10.0 gpu_py36h6e53903_0 tensorflow-gpu 1.10.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi testpath 0.4.2 py36_0 tornado 6.0.3 py36he774522_0 traitlets 4.3.3 py36_0 typed-ast 1.4.0 py36he774522_0 urllib3 1.25.6 pypi_0 pypi vc 14.1 h0510ff6_4 vs2015_runtime 14.16.27012 hf0eaf9b_0 wcwidth 0.1.7 py36h3d5aa90_0 webencodings 0.5.1 py36_1 werkzeug 0.16.0 py_0 wheel 0.33.6 py36_0 win_inet_pton 1.1.0 py36_0 wincertstore 0.2 py36h7fe50ca_0 wrapt 1.11.2 py36he774522_0 yaml 0.1.7 hc54c509_2 zeromq 4.3.1 h33f27b4_3 zipp 0.6.0 py_0 zlib 1.2.11 h62dcd97_3 ``` 2*RTX2080Ti driver 4.19.67
如图 运行conda create -n py27 python=2.7 报错 该如何解决呢
Traceback (most recent call last): File "E:\Anaconda3\lib\site-packages\conda\exceptions.py", line 1074, in __call__ return func(*args, **kwargs) File "E:\Anaconda3\lib\site-packages\conda\cli\main.py", line 84, in _main exit_code = do_call(args, p) File "E:\Anaconda3\lib\site-packages\conda\cli\conda_argparse.py", line 82, in do_call exit_code = getattr(module, func_name)(args, parser) File "E:\Anaconda3\lib\site-packages\conda\cli\main_create.py", line 37, in execute install(args, parser, 'create') File "E:\Anaconda3\lib\site-packages\conda\cli\install.py", line 116, in install if context.use_only_tar_bz2: File "E:\Anaconda3\lib\site-packages\conda\base\context.py", line 666, in use_only_tar_bz2 import conda_package_handling.api File "E:\Anaconda3\lib\site-packages\conda_package_handling\api.py", line 3, in <module> from libarchive.exception import ArchiveError as _LibarchiveArchiveError File "E:\Anaconda3\lib\site-packages\libarchive\__init__.py", line 1, in <module> from .entry import ArchiveEntry File "E:\Anaconda3\lib\site-packages\libarchive\entry.py", line 6, in <module> from . import ffi File "E:\Anaconda3\lib\site-packages\libarchive\ffi.py", line 48, in <module> libarchive = ctypes.cdll.LoadLibrary(libarchive_path) File "E:\Anaconda3\lib\ctypes\__init__.py", line 434, in LoadLibrary return self._dlltype(name) File "E:\Anaconda3\lib\ctypes\__init__.py", line 356, in __init__ self._handle = _dlopen(self._name, mode) OSError: [WinError 126] 找不到指定的模块。
在训练Tensorflow模型(object_detection)时,训练在第一次评估后退出,怎么使训练继续下去?
当我进行ssd模型训练时,训练进行了10分钟,然后进入评估阶段,评估之后程序就自动退出了,没有看到误和警告,这是为什么,怎么让程序一直训练下去? 训练命令: ``` python object_detection/model_main.py --pipeline_config_path=D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/pipeline.config --model_dir=D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/saved_model --num_train_steps=50000 --alsologtostderr ``` 配置文件: ``` training exit after the first evaluation(only one evaluation) in Tensorflow model(object_detection) without error and waring System information What is the top-level directory of the model you are using:models/research/object_detection/ Have I written custom code (as opposed to using a stock example script provided in TensorFlow):NO OS Platform and Distribution (e.g., Linux Ubuntu 16.04):Windows-10(64bit) TensorFlow installed from (source or binary):conda install tensorflow-gpu TensorFlow version (use command below):1.13.1 Bazel version (if compiling from source):N/A CUDA/cuDNN version:cudnn-7.6.0 GPU model and memory:GeForce GTX 1060 6GB Exact command to reproduce:See below my command for training : python object_detection/model_main.py --pipeline_config_path=D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/pipeline.config --model_dir=D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/saved_model --num_train_steps=50000 --alsologtostderr This is my config : train_config { batch_size: 24 data_augmentation_options { random_horizontal_flip { } } data_augmentation_options { ssd_random_crop { } } optimizer { rms_prop_optimizer { learning_rate { exponential_decay_learning_rate { initial_learning_rate: 0.00400000018999 decay_steps: 800720 decay_factor: 0.949999988079 } } momentum_optimizer_value: 0.899999976158 decay: 0.899999976158 epsilon: 1.0 } } fine_tune_checkpoint: "D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/model.ckpt" from_detection_checkpoint: true num_steps: 200000 train_input_reader { label_map_path: "D:/gitcode/models/research/object_detection/idol/tf_label_map.pbtxt" tf_record_input_reader { input_path: "D:/gitcode/models/research/object_detection/idol/train/Iframe_??????.tfrecord" } } eval_config { num_examples: 8000 max_evals: 10 use_moving_averages: false } eval_input_reader { label_map_path: "D:/gitcode/models/research/object_detection/idol/tf_label_map.pbtxt" shuffle: false num_readers: 1 tf_record_input_reader { input_path: "D:/gitcode/models/research/object_detection/idol/eval/Iframe_??????.tfrecord" } ``` 窗口输出: (default) D:\gitcode\models\research>python object_detection/model_main.py --pipeline_config_path=D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/pipeline.config --model_dir=D:/gitcode/models/research/object_detection/ssd_mobilenet_v1_coco_2018_01_28/saved_model --num_train_steps=50000 --alsologtostderr WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0. For more information, please see: https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md https://github.com/tensorflow/addons If you depend on functionality not listed there, please file an issue. WARNING:tensorflow:Forced number of epochs for all eval validations to be 1. WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered eval_on_train_input_config.num_epochs = 0. Overwriting num_epochs to 1. WARNING:tensorflow:Estimator's model_fn (<function create_model_fn..model_fn at 0x0000027CBAB7BB70>) includes params argument, but params are not passed to Estimator. WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\tensorflow\python\framework\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version. Instructions for updating: Colocations handled automatically by placer. WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\builders\dataset_builder.py:86: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.data.experimental.parallel_interleave(...). WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\core\preprocessor.py:196: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: seed2 arg is deprecated.Use sample_distorted_bounding_box_v2 instead. WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\builders\dataset_builder.py:158: batch_and_drop_remainder (from tensorflow.contrib.data.python.ops.batching) is deprecated and will be removed in a future version. Instructions for updating: Use tf.data.Dataset.batch(..., drop_remainder=True). WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\tensorflow\python\ops\losses\losses_impl.py:448: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.cast instead. WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\tensorflow\python\ops\array_grad.py:425: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.cast instead. 2019-08-14 16:29:31.607841: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties: name: GeForce GTX 1060 6GB major: 6 minor: 1 memoryClockRate(GHz): 1.7845 pciBusID: 0000:04:00.0 totalMemory: 6.00GiB freeMemory: 4.97GiB 2019-08-14 16:29:31.621836: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0 2019-08-14 16:29:32.275712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix: 2019-08-14 16:29:32.283072: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0 2019-08-14 16:29:32.288675: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N 2019-08-14 16:29:32.293514: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4714 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:04:00.0, compute capability: 6.1) WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\eval_util.py:796: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.cast instead. WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\object_detection-0.1-py3.7.egg\object_detection\utils\visualization_utils.py:498: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version. Instructions for updating: tf.py_func is deprecated in TF V2. Instead, use tf.py_function, which takes a python function which manipulates tf eager tensors instead of numpy arrays. It's easy to convert a tf eager tensor to an ndarray (just call tensor.numpy()) but having access to eager tensors means tf.py_functions can use accelerators such as GPUs as well as being differentiable using a gradient tape. 2019-08-14 16:41:44.736212: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0 2019-08-14 16:41:44.741242: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix: 2019-08-14 16:41:44.747522: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0 2019-08-14 16:41:44.751256: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N 2019-08-14 16:41:44.755548: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4714 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:04:00.0, compute capability: 6.1) WARNING:tensorflow:From C:\Users\qian\Anaconda3\envs\default\lib\site-packages\tensorflow\python\training\saver.py:1266: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version. Instructions for updating: Use standard file APIs to check for files with this prefix. creating index... index created! creating index... index created! Running per image evaluation... Evaluate annotation type bbox DONE (t=2.43s). Accumulating evaluation results... DONE (t=0.14s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.287 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.529 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.278 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.031 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.312 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.162 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.356 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.356 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.061 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.384 (default) D:\gitcode\models\research>
win10 Anaconda python 中 SSL模块无法正常使用
在Anaconda python 中 SSL模块无法正常使用</br> </br> 执行</br> conda create -n tensorflow-gpu python=3.7</br> 出错 </br></br> 该语句需要访问 https 的连接 需要SSL的支持 但Anaconda python 的SSL模块无法使</br></br> 但使用系统中的python可以正常调用ssl模块,</br> 想在anaconda python 下,</br> 用 pip install ssl 语句 安装ssl,但因ssl模块无法使用,pip 也无法正常运行,</br></br> 网上也未找到相关的问题,请大佬解答 ![图片说明](https://img-ask.csdn.net/upload/201901/12/1547303110_258132.png)![图片说明](https://img-ask.csdn.net/upload/201901/12/1547303136_473175.png)
python conda install xxx 报错 找不到指定模块
(HelloWorld) C:\Users\justin>conda install cv2 # >>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<< Traceback (most recent call last): File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda\exceptions.py", line 1062, in __call__ return func(*args, **kwargs) File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda\cli\main.py", line 84, in _main exit_code = do_call(args, p) File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda\cli\conda_argparse.py", line 82, in do_call exit_code = getattr(module, func_name)(args, parser) File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda\cli\main_install.py", line 20, in execute install(args, parser, 'install') File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda\cli\install.py", line 116, in install if context.use_only_tar_bz2: File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda\base\context.py", line 664, in use_only_tar_bz2 import conda_package_handling.api File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda_package_handling\api.py", line 12, in <module> from .tarball import CondaTarBZ2 as _CondaTarBZ2, libarchive_enabled File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\conda_package_handling\tarball.py", line 11, in <module> import libarchive File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\libarchive\__init__.py", line 1, in <module> from .entry import ArchiveEntry File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\libarchive\entry.py", line 6, in <module> from . import ffi File "F:\Miniconda3\envs\HelloWorld\lib\site-packages\libarchive\ffi.py", line 27, in <module> libarchive = ctypes.cdll.LoadLibrary(libarchive_path) File "F:\Miniconda3\envs\HelloWorld\lib\ctypes\__init__.py", line 442, in LoadLibrary return self._dlltype(name) File "F:\Miniconda3\envs\HelloWorld\lib\ctypes\__init__.py", line 364, in __init__ self._handle = _dlopen(self._name, mode) OSError: [WinError 126] 找不到指定的模块。 `$ F:\Miniconda3\envs\HelloWorld\Scripts\conda-script.py install cv2` ``` ```
如何从conda-forge清单中安装的指定Python扩展?
我想用 conda 命令安装 numpy, 首先我搜一下版本列表: ``` conda search numpy -c conda-forge ``` 然后我想安装这个列表中的: ``` numpy 1.15.4 py36_blas_openblash442142e_1000 conda-forge ``` 用这个命令: ``` conda install numpy=1.15.4 -c conda-forge ``` 是可以的 但是我想安装这个带OpenBLAS的, 请问指令如何写?
请问下pycharm中import MySQLdb安装失败的问题。。。
使用的是anaconda3.6 paycharm安装MySQLdb安装失败 后来在命令行中输入conda install pymysql和conda install mysql-python安装之后还是不能import 直接conda install MySQLdb 也显示安装不了![图片说明](https://img-ask.csdn.net/upload/201710/06/1507280829_210511.png)
安装pytorch后使用conda出现报错不知怎么解决
安装了pytorch在一个新建环境后conda不知怎么就崩了 ![图片说明](https://img-ask.csdn.net/upload/202001/18/1579314770_106086.png) 一直是这个样子输入conda命令就这样 打开anaconda prompt也报这个错
求助,在R语言搭建conda环境时出现了很令人无语的问题
之前从来没有出现过这种问题的……今天尝试的时候就莫名其妙出现了这种 网络问题,试了有几百次了还没解决,尝试了各种方法还是出现同样的问题, 我用自己手机开热点都试过了,照样没用,想问下大家有什么解决方法吗…… ``` >install_tensorflow() Creating r-tensorflow conda environment for TensorFlow installation... WARNING: The conda.compat module is deprecated and will be removed in a future release. Collecting package metadata: ...working... failed CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://repo.anaconda.com/pkgs/main/noarch/repodata.json.bz2> Elapsed: - An HTTP error occurred when trying to retrieve this URL. HTTP errors are often intermittent, and a simple retry will get you on your way. If your current network has https://www.anaconda.com blocked, please file a support request with your network engineering team. SSLError(MaxRetryError('HTTPSConnectionPool(host=\'repo.anaconda.com\', port=443): Max retries exceeded with url: /pkgs/main/noarch/repodata.json.bz2 (Caused by SSLError("Can\'t connect to HTTPS URL because the SSL module is not available."))')) Error: Error 1 occurred creating conda environment r-tensorflow ```
安装anaconda后输入conda info 报错求解
想问下这个administrator : false; offline mode : false是什么问题怎么解决. 并且输入python后显示是环境变量但未激活。并且安装后桌面找不到anaconda的图标。望大神救救我!!! active environment : base active env location : D:\anaconda shell level : 1 user config file : C:\Users\Katharine\.condarc populated config files : conda version : 4.7.10 conda-build version : 3.18.8 python version : 3.7.3.final.0 virtual packages : __cuda=10.0 base environment : D:\anaconda (writable) channel URLs : https://repo.anaconda.com/pkgs/main/win-64 https://repo.anaconda.com/pkgs/main/noarch https://repo.anaconda.com/pkgs/r/win-64 https://repo.anaconda.com/pkgs/r/noarch https://repo.anaconda.com/pkgs/msys2/win-64 https://repo.anaconda.com/pkgs/msys2/noarch package cache : D:\anaconda\pkgs C:\Users\Katharine\.conda\pkgs C:\Users\Katharine\AppData\Local\conda\conda\pkgs envs directories : D:\anaconda\envs C:\Users\Katharine\.conda\envs C:\Users\Katharine\AppData\Local\conda\conda\envs platform : win-64 user-agent : conda/4.7.10 requests/2.22.0 CPython/3.7.3 Windows/10 Windows/10.0.17134 administrator : False netrc file : None offline mode : False
如何在anconda show +package name 的结果中选择安装包的版本?
我最近想学习hmm,在安装hmmlearn包时,我使用了anaconda show conda-forge/hmmlearn 得到它的下载途径,见下图 ![图片说明](https://img-ask.csdn.net/upload/201906/25/1561430116_882949.jpg) 下面的提示说,只要把run下面的语句: ``` conda install --channel https://conda.anaconda.org/conda-forge hmmlearn ```运行即可,但它安装完之后的hmmlearn版本是0.2.1的。我想安装0.2.0版本的,需要怎么改写这条语句呢?
Java学习的正确打开方式
在博主认为,对于入门级学习java的最佳学习方法莫过于视频+博客+书籍+总结,前三者博主将淋漓尽致地挥毫于这篇博客文章中,至于总结在于个人,实际上越到后面你会发现学习的最好方式就是阅读参考官方文档其次就是国内的书籍,博客次之,这又是一个层次了,这里暂时不提后面再谈。博主将为各位入门java保驾护航,各位只管冲鸭!!!上天是公平的,只要不辜负时间,时间自然不会辜负你。 何谓学习?博主所理解的学习,它是一个过程,是一个不断累积、不断沉淀、不断总结、善于传达自己的个人见解以及乐于分享的过程。
程序员必须掌握的核心算法有哪些?
由于我之前一直强调数据结构以及算法学习的重要性,所以就有一些读者经常问我,数据结构与算法应该要学习到哪个程度呢?,说实话,这个问题我不知道要怎么回答你,主要取决于你想学习到哪些程度,不过针对这个问题,我稍微总结一下我学过的算法知识点,以及我觉得值得学习的算法。这些算法与数据结构的学习大多数是零散的,并没有一本把他们全部覆盖的书籍。下面是我觉得值得学习的一些算法以及数据结构,当然,我也会整理一些看过...
有哪些让程序员受益终生的建议
从业五年多,辗转两个大厂,出过书,创过业,从技术小白成长为基层管理,联合几个业内大牛回答下这个问题,希望能帮到大家,记得帮我点赞哦。 敲黑板!!!读了这篇文章,你将知道如何才能进大厂,如何实现财务自由,如何在工作中游刃有余,这篇文章很长,但绝对是精品,记得帮我点赞哦!!!! 一腔肺腑之言,能看进去多少,就看你自己了!!! 目录: 在校生篇: 为什么要尽量进大厂? 如何选择语言及方...
大学四年自学走来,这些私藏的实用工具/学习网站我贡献出来了
大学四年,看课本是不可能一直看课本的了,对于学习,特别是自学,善于搜索网上的一些资源来辅助,还是非常有必要的,下面我就把这几年私藏的各种资源,网站贡献出来给你们。主要有:电子书搜索、实用工具、在线视频学习网站、非视频学习网站、软件下载、面试/求职必备网站。 注意:文中提到的所有资源,文末我都给你整理好了,你们只管拿去,如果觉得不错,转发、分享就是最大的支持了。 一、电子书搜索 对于大部分程序员...
linux系列之常用运维命令整理笔录
本博客记录工作中需要的linux运维命令,大学时候开始接触linux,会一些基本操作,可是都没有整理起来,加上是做开发,不做运维,有些命令忘记了,所以现在整理成博客,当然vi,文件操作等就不介绍了,慢慢积累一些其它拓展的命令,博客不定时更新 free -m 其中:m表示兆,也可以用g,注意都要小写 Men:表示物理内存统计 total:表示物理内存总数(total=used+free) use...
比特币原理详解
一、什么是比特币 比特币是一种电子货币,是一种基于密码学的货币,在2008年11月1日由中本聪发表比特币白皮书,文中提出了一种去中心化的电子记账系统,我们平时的电子现金是银行来记账,因为银行的背后是国家信用。去中心化电子记账系统是参与者共同记账。比特币可以防止主权危机、信用风险。其好处不多做赘述,这一层面介绍的文章很多,本文主要从更深层的技术原理角度进行介绍。 二、问题引入 假设现有4个人...
程序员接私活怎样防止做完了不给钱?
首先跟大家说明一点,我们做 IT 类的外包开发,是非标品开发,所以很有可能在开发过程中会有这样那样的需求修改,而这种需求修改很容易造成扯皮,进而影响到费用支付,甚至出现做完了项目收不到钱的情况。 那么,怎么保证自己的薪酬安全呢? 我们在开工前,一定要做好一些证据方面的准备(也就是“讨薪”的理论依据),这其中最重要的就是需求文档和验收标准。一定要让需求方提供这两个文档资料作为开发的基础。之后开发...
网页实现一个简单的音乐播放器(大佬别看。(⊙﹏⊙))
今天闲着无事,就想写点东西。然后听了下歌,就打算写个播放器。 于是乎用h5 audio的加上js简单的播放器完工了。 演示地点演示 html代码如下` music 这个年纪 七月的风 音乐 ` 然后就是css`*{ margin: 0; padding: 0; text-decoration: none; list-...
Python十大装B语法
Python 是一种代表简单思想的语言,其语法相对简单,很容易上手。不过,如果就此小视 Python 语法的精妙和深邃,那就大错特错了。本文精心筛选了最能展现 Python 语法之精妙的十个知识点,并附上详细的实例代码。如能在实战中融会贯通、灵活使用,必将使代码更为精炼、高效,同时也会极大提升代码B格,使之看上去更老练,读起来更优雅。
数据库优化 - SQL优化
以实际SQL入手,带你一步一步走上SQL优化之路!
2019年11月中国大陆编程语言排行榜
2019年11月2日,我统计了某招聘网站,获得有效程序员招聘数据9万条。针对招聘信息,提取编程语言关键字,并统计如下: 编程语言比例 rank pl_ percentage 1 java 33.62% 2 cpp 16.42% 3 c_sharp 12.82% 4 javascript 12.31% 5 python 7.93% 6 go 7.25% 7 p...
通俗易懂地给女朋友讲:线程池的内部原理
餐盘在灯光的照耀下格外晶莹洁白,女朋友拿起红酒杯轻轻地抿了一小口,对我说:“经常听你说线程池,到底线程池到底是个什么原理?”
《奇巧淫技》系列-python!!每天早上八点自动发送天气预报邮件到QQ邮箱
将代码部署服务器,每日早上定时获取到天气数据,并发送到邮箱。 也可以说是一个小型人工智障。 知识可以运用在不同地方,不一定非是天气预报。
经典算法(5)杨辉三角
杨辉三角 是经典算法,这篇博客对它的算法思想进行了讲解,并有完整的代码实现。
英特尔不为人知的 B 面
从 PC 时代至今,众人只知在 CPU、GPU、XPU、制程、工艺等战场中,英特尔在与同行硬件芯片制造商们的竞争中杀出重围,且在不断的成长进化中,成为全球知名的半导体公司。殊不知,在「刚硬」的背后,英特尔「柔性」的软件早已经做到了全方位的支持与支撑,并持续发挥独特的生态价值,推动产业合作共赢。 而对于这一不知人知的 B 面,很多人将其称之为英特尔隐形的翅膀,虽低调,但是影响力却不容小觑。 那么,在...
腾讯算法面试题:64匹马8个跑道需要多少轮才能选出最快的四匹?
昨天,有网友私信我,说去阿里面试,彻底的被打击到了。问了为什么网上大量使用ThreadLocal的源码都会加上private static?他被难住了,因为他从来都没有考虑过这个问题。无独有偶,今天笔者又发现有网友吐槽了一道腾讯的面试题,我们一起来看看。 腾讯算法面试题:64匹马8个跑道需要多少轮才能选出最快的四匹? 在互联网职场论坛,一名程序员发帖求助到。二面腾讯,其中一个算法题:64匹...
面试官:你连RESTful都不知道我怎么敢要你?
干货,2019 RESTful最贱实践
为啥国人偏爱Mybatis,而老外喜欢Hibernate/JPA呢?
关于SQL和ORM的争论,永远都不会终止,我也一直在思考这个问题。昨天又跟群里的小伙伴进行了一番讨论,感触还是有一些,于是就有了今天这篇文。 声明:本文不会下关于Mybatis和JPA两个持久层框架哪个更好这样的结论。只是摆事实,讲道理,所以,请各位看官勿喷。 一、事件起因 关于Mybatis和JPA孰优孰劣的问题,争论已经很多年了。一直也没有结论,毕竟每个人的喜好和习惯是大不相同的。我也看...
白话阿里巴巴Java开发手册高级篇
不久前,阿里巴巴发布了《阿里巴巴Java开发手册》,总结了阿里巴巴内部实际项目开发过程中开发人员应该遵守的研发流程规范,这些流程规范在一定程度上能够保证最终的项目交付质量,通过在时间中总结模式,并推广给广大开发人员,来避免研发人员在实践中容易犯的错误,确保最终在大规模协作的项目中达成既定目标。 无独有偶,笔者去年在公司里负责升级和制定研发流程、设计模板、设计标准、代码标准等规范,并在实际工作中进行...
SQL-小白最佳入门sql查询一
不要偷偷的查询我的个人资料,即使你再喜欢我,也不要这样,真的不好;
redis分布式锁,面试官请随便问,我都会
文章有点长并且绕,先来个图片缓冲下! 前言 现在的业务场景越来越复杂,使用的架构也就越来越复杂,分布式、高并发已经是业务要求的常态。像腾讯系的不少服务,还有CDN优化、异地多备份等处理。 说到分布式,就必然涉及到分布式锁的概念,如何保证不同机器不同线程的分布式锁同步呢? 实现要点 互斥性,同一时刻,智能有一个客户端持有锁。 防止死锁发生,如果持有锁的客户端崩溃没有主动释放锁,也要保证锁可以正常释...
项目中的if else太多了,该怎么重构?
介绍 最近跟着公司的大佬开发了一款IM系统,类似QQ和微信哈,就是聊天软件。我们有一部分业务逻辑是这样的 if (msgType = "文本") { // dosomething } else if(msgType = "图片") { // doshomething } else if(msgType = "视频") { // doshomething } else { // doshom...
Nginx 原理和架构
Nginx 是一个免费的,开源的,高性能的 HTTP 服务器和反向代理,以及 IMAP / POP3 代理服务器。Nginx 以其高性能,稳定性,丰富的功能,简单的配置和低资源消耗而闻名。 Nginx 的整体架构 Nginx 里有一个 master 进程和多个 worker 进程。master 进程并不处理网络请求,主要负责调度工作进程:加载配置、启动工作进程及非停升级。worker 进程负责处...
Python 编程开发 实用经验和技巧
Python是一门很灵活的语言,也有很多实用的方法,有时候实现一个功能可以用多种方法实现,我这里总结了一些常用的方法和技巧,包括小数保留指定位小数、判断变量的数据类型、类方法@classmethod、制表符中文对齐、遍历字典、datetime.timedelta的使用等,会持续更新......
YouTube排名第一的励志英文演讲《Dream(梦想)》
Idon’t know what that dream is that you have, I don't care how disappointing it might have been as you've been working toward that dream,but that dream that you’re holding in your mind, that it’s po...
“狗屁不通文章生成器”登顶GitHub热榜,分分钟写出万字形式主义大作
一、垃圾文字生成器介绍 最近在浏览GitHub的时候,发现了这样一个骨骼清奇的雷人项目,而且热度还特别高。 项目中文名:狗屁不通文章生成器 项目英文名:BullshitGenerator 根据作者的介绍,他是偶尔需要一些中文文字用于GUI开发时测试文本渲染,因此开发了这个废话生成器。但由于生成的废话实在是太过富于哲理,所以最近已经被小伙伴们给玩坏了。 他的文风可能是这样的: 你发现,...
程序员:我终于知道post和get的区别
是一个老生常谈的话题,然而随着不断的学习,对于以前的认识有很多误区,所以还是需要不断地总结的,学而时习之,不亦说乎
《程序人生》系列-这个程序员只用了20行代码就拿了冠军
你知道的越多,你不知道的越多 点赞再看,养成习惯GitHub上已经开源https://github.com/JavaFamily,有一线大厂面试点脑图,欢迎Star和完善 前言 这一期不算《吊打面试官》系列的,所有没前言我直接开始。 絮叨 本来应该是没有这期的,看过我上期的小伙伴应该是知道的嘛,双十一比较忙嘛,要值班又要去帮忙拍摄年会的视频素材,还得搞个程序员一天的Vlog,还要写BU...
加快推动区块链技术和产业创新发展,2019可信区块链峰会在京召开
11月8日,由中国信息通信研究院、中国通信标准化协会、中国互联网协会、可信区块链推进计划联合主办,科技行者协办的2019可信区块链峰会将在北京悠唐皇冠假日酒店开幕。   区块链技术被认为是继蒸汽机、电力、互联网之后,下一代颠覆性的核心技术。如果说蒸汽机释放了人类的生产力,电力解决了人类基本的生活需求,互联网彻底改变了信息传递的方式,区块链作为构造信任的技术有重要的价值。   1...
Java世界最常用的工具类库
Apache Commons Apache Commons有很多子项目 Google Guava 参考博客
相关热词 c# 输入ip c# 乱码 报表 c#选择结构应用基本算法 c# 收到udp包后回包 c#oracle 头文件 c# 序列化对象 自定义 c# tcp 心跳 c# ice连接服务端 c# md5 解密 c# 文字导航控件
立即提问