Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.scriptrun = azureml.core.script_run:ScriptRun._from_run_dto with exception (urllib3 1.26.12 (/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages), Requirement.parse('urllib3<=1.26.9,>=1.23')). Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.PipelineRun = azureml.pipeline.core.run:PipelineRun._from_dto with exception (urllib3 1.26.12 (/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages), Requirement.parse('urllib3<=1.26.9,>=1.23'), {'azureml-core'}). Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.ReusedStepRun = azureml.pipeline.core.run:StepRun._from_reused_dto with exception (urllib3 1.26.12 (/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages), Requirement.parse('urllib3<=1.26.9,>=1.23'), {'azureml-core'}). Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.StepRun = azureml.pipeline.core.run:StepRun._from_dto with exception (urllib3 1.26.12 (/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages), Requirement.parse('urllib3<=1.26.9,>=1.23'), {'azureml-core'}). Session_id = 57df1d63-87f9-44aa-b323-1d6c31be0648 Invoking module by urldecode_invoker 0.0.8. Module type: official module. Using runpy to invoke module 'azureml.studio.modulehost.module_invoker'. 2023-06-28 13:52:18,481 studio.modulehost INFO Reset logging level to DEBUG 2023-06-28 13:52:18,481 studio.modulehost INFO Load pyarrow.parquet explicitly: 2023-06-28 13:52:18,482 studio.core INFO execute_with_cli - Start: 2023-06-28 13:52:18,482 studio.modulehost INFO | ALGHOST 0.0.177 2023-06-28 13:52:18,484 studio.modulehost INFO | CLI arguments parsed: {'module_name': 'azureml.studio.modules.python_language_modules.execute_python_script', 'OutputPortsInternal': {'Result Dataset': '/mnt/azureml/cr/j/29f0cc1ae2b44965bbf79e892fb9c147/cap/data-capability/wd/Result_Dataset', 'Python Device': '/mnt/azureml/cr/j/29f0cc1ae2b44965bbf79e892fb9c147/cap/data-capability/wd/Python_Device'}, 'InputPortsInternal': {'Dataset1': '$AZUREML_DATAREFERENCE_Dataset1'}, 'ModuleParameters': {'Python Script': "import pandas as pd\n\ndef azureml_main(dataframe1 = None, dataframe2 = None):\n\n scored_results = dataframe1[['Scored Labels', 'Scored Probabilities']]\n scored_results.rename(columns={'Scored Labels':'DiabetesPrediction',\n 'Scored Probabilities':'Probability'},\n inplace=True)\n return scored_results"}} 2023-06-28 13:52:18,659 studio.modulehost INFO | Invoking ModuleEntry(azureml.studio.modules.python_language_modules.execute_python_script; ExecutePythonScriptModule; run) 2023-06-28 13:52:18,659 studio.core DEBUG | Input Ports: 2023-06-28 13:52:18,659 studio.core DEBUG | | Dataset1 = 2023-06-28 13:52:18,659 studio.core DEBUG | Output Ports: 2023-06-28 13:52:18,659 studio.core DEBUG | | Result Dataset = /mnt/azureml/cr/j/29f0cc1ae2b44965bbf79e892fb9c147/cap/data-capability/wd/Result_Dataset 2023-06-28 13:52:18,659 studio.core DEBUG | | Python Device = /mnt/azureml/cr/j/29f0cc1ae2b44965bbf79e892fb9c147/cap/data-capability/wd/Python_Device 2023-06-28 13:52:18,659 studio.core DEBUG | Parameters: 2023-06-28 13:52:18,659 studio.core DEBUG | | Python Script = import pandas as pd def azureml_main(dataframe1 = None, dataframe2 = None): ... (omitted 4 lines) ... inplace=True) return scored_results 2023-06-28 13:52:18,659 studio.core DEBUG | Environment Variables: 2023-06-28 13:52:18,659 studio.core DEBUG | | (empty) 2023-06-28 13:52:18,659 studio.core INFO | Reflect input ports and parameters - Start: 2023-06-28 13:52:18,659 studio.core INFO | | Handle input port "Dataset1" - Start: 2023-06-28 13:52:18,659 studio.core INFO | | | Mount/Download dataset to '$AZUREML_DATAREFERENCE_Dataset1' - Start: 2023-06-28 13:52:18,659 studio.modulehost DEBUG | | | | Content of directory $AZUREML_DATAREFERENCE_Dataset1: 2023-06-28 13:52:18,659 studio.core INFO | | | Mount/Download dataset to '$AZUREML_DATAREFERENCE_Dataset1' - End with 0.0001s elapsed. 2023-06-28 13:52:18,660 studio.core INFO | | Handle input port "Dataset1" - End with 0.0003s elapsed. 2023-06-28 13:52:18,660 studio.core INFO | Reflect input ports and parameters - End with 0.0005s elapsed. 2023-06-28 13:52:18,660 studio.modulehost INFO | Set error info in module statistics 2023-06-28 13:52:18,660 studio.core INFO | Logging exception information of module execution - Start: 2023-06-28 13:52:18,660 studio.modulehost INFO | | Session_id = 57df1d63-87f9-44aa-b323-1d6c31be0648 2023-06-28 13:52:18,660 studio.core INFO | | ModuleStatistics.log_stack_trace_telemetry - Start: 2023-06-28 13:52:18,800 studio.core INFO | | ModuleStatistics.log_stack_trace_telemetry - End with 0.1404s elapsed. 2023-06-28 13:52:18,801 studio.modulehost ERROR | | Get ModuleError when invoking ModuleEntry(azureml.studio.modules.python_language_modules.execute_python_script; ExecutePythonScriptModule; run) Traceback (most recent call last): File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_reflector.py", line 371, in exec reflected_input_ports = self._reflect_input_ports(input_ports) > input_ports = {'Dataset1': } > self = File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_reflector.py", line 418, in _reflect_input_ports value = self._env.handle_input_port(annotation, input_value) > annotation = > input_value = > self = File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/env.py", line 73, in handle_input_port ErrorMapping.throw(InvalidDatasetError( File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/common/error.py", line 835, in throw raise err > err = InvalidDatasetError('Dataset1 is not valid, reason: input path does not exist. There are several possible causes: 1. Your input is a registered dataset but the dataset is invalid; 2. Your input is the output of a reused module, but the output of the module is removed;') InvalidDatasetError: Dataset1 is not valid, reason: input path does not exist. There are several possible causes: 1. Your input is a registered dataset but the dataset is invalid; 2. Your input is the output of a reused module, but the output of the module is removed; 2023-06-28 13:52:18,801 studio.core INFO | Logging exception information of module execution - End with 0.1414s elapsed. 2023-06-28 13:52:18,801 studio.core INFO | ModuleStatistics.save_to_azureml - Start: 2023-06-28 13:52:18,982 studio.core INFO | ModuleStatistics.save_to_azureml - End with 0.1805s elapsed. 2023-06-28 13:52:18,982 studio.core INFO execute_with_cli - End with 0.5005s elapsed. Cleaning up all outstanding Run operations, waiting 300.0 seconds 2 items cleaning up... Cleanup took 0.13982081413269043 seconds Traceback (most recent call last): File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_invoker.py", line 7, in execute(sys.argv) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_host_executor.py", line 41, in execute return execute_with_cli(original_args) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/core/logger.py", line 214, in wrapper ret = func(*args, **kwargs) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_host_executor.py", line 52, in execute_with_cli do_execute_with_env(parser, FolderRuntimeEnv()) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_host_executor.py", line 63, in do_execute_with_env ModuleReflector(parser.module_entry, env).exec( File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_reflector.py", line 397, in exec self._handle_exception(bex) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_reflector.py", line 471, in _handle_exception raise exception File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_reflector.py", line 371, in exec reflected_input_ports = self._reflect_input_ports(input_ports) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/module_reflector.py", line 418, in _reflect_input_ports value = self._env.handle_input_port(annotation, input_value) File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/modulehost/env.py", line 73, in handle_input_port ErrorMapping.throw(InvalidDatasetError( File "/azureml-envs/azureml_8f317849db35f281450cf74333640b98/lib/python3.8/site-packages/azureml/studio/common/error.py", line 835, in throw raise err azureml.studio.common.error.InvalidDatasetError: Dataset1 is not valid, reason: input path does not exist. There are several possible causes: 1. Your input is a registered dataset but the dataset is invalid; 2. Your input is the output of a reused module, but the output of the module is removed;