AzureML:ResolvePackageNotFound azureml-dataprep
AzureML: ResolvePackageNotFound azureml-dataprep
我的 AML 管道中有一个基本的 ScriptStep,它只是试图读取附加的数据集。当我执行这个简单的示例时,管道失败并在驱动程序日志中显示以下内容:
ImportError: azureml-dataprep is not installed. Dataset cannot be used
without azureml-dataprep. Please make sure
azureml-dataprep[fuse,pandas] is installed by specifying it in the
conda dependencies. pandas is optional and should be only installed if
you intend to create a pandas DataFrame from the dataset.
然后我修改了我的步骤以包含 conda 包,但随后驱动程序失败并显示 "ResolvePackageNotFound: azureml-dataprep"。可以访问整个日志文件 here.
# create a new runconfig object
run_config = RunConfiguration()
run_config.environment.docker.enabled = True
run_config.environment.docker.base_image = DEFAULT_CPU_IMAGE
run_config.environment.python.user_managed_dependencies = False
run_config.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['azureml-dataprep[pandas,fuse]'])
source_directory = './read-step'
print('Source directory for the step is {}.'.format(os.path.realpath(source_directory)))
step2 = PythonScriptStep(name="read_step",
script_name="Read.py",
arguments=["--dataFilePath", dataset.as_named_input('local_ds').as_mount() ],
compute_target=aml_compute,
source_directory=source_directory,
runconfig=run_config,
allow_reuse=False)
我没有想法,非常感谢这里的任何帮助!
azureml-sdk
在 conda 上不可用,您需要使用 pip
安装它。
myenv = Environment(name="myenv")
conda_dep = CondaDependencies().add_pip_package("azureml-dataprep[pandas,fuse]")
myenv.python.conda_dependencies=conda_dep
run_config.environment = myenv
有关此错误的更多信息,日志选项卡有一个名为 20_image_build_log.txt
的日志,它 Docker 构建日志。它包含 conda
failed to failed to find azureml-dataprep
的错误
编辑:
很快,您将不必再指定此依赖项。 Azure Data4ML 团队表示 azureml-dataprep[pandas,fuse]
被添加为 azureml-defaults
的依赖项,它会自动安装在所有图像上。
我的 AML 管道中有一个基本的 ScriptStep,它只是试图读取附加的数据集。当我执行这个简单的示例时,管道失败并在驱动程序日志中显示以下内容:
ImportError: azureml-dataprep is not installed. Dataset cannot be used without azureml-dataprep. Please make sure azureml-dataprep[fuse,pandas] is installed by specifying it in the conda dependencies. pandas is optional and should be only installed if you intend to create a pandas DataFrame from the dataset.
然后我修改了我的步骤以包含 conda 包,但随后驱动程序失败并显示 "ResolvePackageNotFound: azureml-dataprep"。可以访问整个日志文件 here.
# create a new runconfig object
run_config = RunConfiguration()
run_config.environment.docker.enabled = True
run_config.environment.docker.base_image = DEFAULT_CPU_IMAGE
run_config.environment.python.user_managed_dependencies = False
run_config.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['azureml-dataprep[pandas,fuse]'])
source_directory = './read-step'
print('Source directory for the step is {}.'.format(os.path.realpath(source_directory)))
step2 = PythonScriptStep(name="read_step",
script_name="Read.py",
arguments=["--dataFilePath", dataset.as_named_input('local_ds').as_mount() ],
compute_target=aml_compute,
source_directory=source_directory,
runconfig=run_config,
allow_reuse=False)
我没有想法,非常感谢这里的任何帮助!
azureml-sdk
在 conda 上不可用,您需要使用 pip
安装它。
myenv = Environment(name="myenv")
conda_dep = CondaDependencies().add_pip_package("azureml-dataprep[pandas,fuse]")
myenv.python.conda_dependencies=conda_dep
run_config.environment = myenv
有关此错误的更多信息,日志选项卡有一个名为 20_image_build_log.txt
的日志,它 Docker 构建日志。它包含 conda
failed to failed to find azureml-dataprep
编辑:
很快,您将不必再指定此依赖项。 Azure Data4ML 团队表示 azureml-dataprep[pandas,fuse]
被添加为 azureml-defaults
的依赖项,它会自动安装在所有图像上。