在Azure ML designer中利用线性回归算法训练预测模型

2024年12月27日 853点热度 0人点赞 0条评论

scored labels result:

evaluation results:

running logs:

Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.PipelineRun = azureml.pipeline.core.run:PipelineRun._from_dto with exception (azureml-core 1.47.0 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('azureml-core~=1.54.0')).
Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.ReusedStepRun = azureml.pipeline.core.run:StepRun._from_reused_dto with exception (azureml-core 1.47.0 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('azureml-core~=1.54.0')).
Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.StepRun = azureml.pipeline.core.run:StepRun._from_dto with exception (azureml-core 1.47.0 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('azureml-core~=1.54.0')).
Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.scriptrun = azureml.core.script_run:ScriptRun._from_run_dto with exception (cryptography 42.0.4 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('cryptography!=1.9,!=2.0.*,!=2.1.*,!=2.2.*,&lt;41')).
Session_id = 9f298848-ea03-489c-86b5-d39308b98481
Invoking module by urldecode_invoker 0.0.8.

Module type: official module.

Using runpy to invoke module 'azureml.studio.modulehost.module_invoker'.

2024-12-27 09:47:34,900 studio.modulehost    INFO       Reset logging level to DEBUG
2024-12-27 09:47:34,900 studio.modulehost    INFO       Load pyarrow.parquet explicitly: &lt;module 'pyarrow.parquet' from '/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages/pyarrow/parquet/__init__.py'&gt;
2024-12-27 09:47:34,900 studio.core          INFO       execute_with_cli - Start:
2024-12-27 09:47:34,900 studio.modulehost    INFO       |   ALGHOST 0.0.182
RuntimeError: module compiled against API version 0x10 but this version of numpy is 0xf . Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem .
IPython could not be loaded!
2024-12-27 09:47:36,155 studio.modulehost    INFO       |   CLI arguments parsed: {'module_name': 'azureml.studio.modules.ml.train.train_generic_model.train_generic_model', 'OutputPortsInternal': {'Trained model': '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/Trained_model'}, 'InputPortsInternal': {'Untrained model': '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model', 'Dataset': '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset'}, 'ModuleParameters': {'Label column': '%7B%22isFilter%22%3Atrue%2C%22rules%22%3A%5B%7B%22exclude%22%3Afalse%2C%22ruleType%22%3A%22ColumnNames%22%2C%22columns%22%3A%5B%22rentals%22%5D%7D%5D%7D', 'Model explanations': 'False'}}
2024-12-27 09:47:36,357 studio.modulehost    INFO       |   Invoking ModuleEntry(azureml.studio.modules.ml.train.train_generic_model.train_generic_model; TrainModelModule; run)
2024-12-27 09:47:36,357 studio.core          DEBUG      |   Input Ports:
2024-12-27 09:47:36,357 studio.core          DEBUG      |   |   Untrained model = &lt;azureml.studio.modulehost.cli_parser.CliInputValue object at 0x14911d5b93d0&gt;
2024-12-27 09:47:36,357 studio.core          DEBUG      |   |   Dataset = &lt;azureml.studio.modulehost.cli_parser.CliInputValue object at 0x14911d5b9460&gt;
2024-12-27 09:47:36,357 studio.core          DEBUG      |   Output Ports:
2024-12-27 09:47:36,357 studio.core          DEBUG      |   |   Trained model = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/Trained_model
2024-12-27 09:47:36,357 studio.core          DEBUG      |   Parameters:
2024-12-27 09:47:36,357 studio.core          DEBUG      |   |   Label column = %7B%22isFilter%22%3Atrue%2C%22rules%22%3A%5B%7B%22exclude%22%3Afalse%2C%22ruleType%22%3A%22ColumnNames%22%2C%22columns%22%3A%5B%22rentals%22%5D%7D%5D%7D
2024-12-27 09:47:36,357 studio.core          DEBUG      |   |   Model explanations = False
2024-12-27 09:47:36,358 studio.core          DEBUG      |   Environment Variables:
2024-12-27 09:47:36,358 studio.core          DEBUG      |   |   AZUREML_DATAREFERENCE_DATASET = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset
2024-12-27 09:47:36,358 studio.core          DEBUG      |   |   AZUREML_DATAREFERENCE_Dataset = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset
2024-12-27 09:47:36,358 studio.core          DEBUG      |   |   AZUREML_DATAREFERENCE_UNTRAINED_MODEL = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model
2024-12-27 09:47:36,358 studio.core          DEBUG      |   |   AZUREML_DATAREFERENCE_Untrained_model = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model
2024-12-27 09:47:36,358 studio.core          INFO       |   Reflect input ports and parameters - Start:
2024-12-27 09:47:36,358 studio.core          INFO       |   |   Handle input port "Untrained model" - Start:
2024-12-27 09:47:36,358 studio.core          INFO       |   |   |   Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model' - Start:
2024-12-27 09:47:36,358 studio.modulehost    DEBUG      |   |   |   |   Content of directory /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model:
2024-12-27 09:47:36,364 studio.modulehost    DEBUG      |   |   |   |   |   _meta.yaml
2024-12-27 09:47:36,364 studio.modulehost    DEBUG      |   |   |   |   |   data.ilearner
2024-12-27 09:47:36,364 studio.modulehost    DEBUG      |   |   |   |   |   model_spec.yaml
2024-12-27 09:47:36,364 studio.core          INFO       |   |   |   Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model' - End with 0.0061s elapsed.
2024-12-27 09:47:36,369 studio.core          INFO       |   |   |   Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model via meta - Start:
2024-12-27 09:47:36,411 studio.common        INFO       |   |   |   |   Load meta data from directory successfully, data=ModelDirectory(meta={'type': 'ModelDirectory', 'extension': {}, 'model': 'model_spec.yaml'}), type=&lt;class 'azureml.studio.core.io.model_directory.ModelDirectory'&gt;
2024-12-27 09:47:36,411 studio.common        INFO       |   |   |   |   Load ModelDirectory successfully, data=&lt;azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400&gt;
2024-12-27 09:47:36,411 studio.core          INFO       |   |   |   Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model via meta - End with 0.0417s elapsed.
2024-12-27 09:47:36,411 studio.core          INFO       |   |   Handle input port "Untrained model" - End with 0.0531s elapsed.
2024-12-27 09:47:36,411 studio.core          INFO       |   |   Handle input port "Dataset" - Start:
2024-12-27 09:47:36,411 studio.core          INFO       |   |   |   Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset' - Start:
2024-12-27 09:47:36,411 studio.modulehost    DEBUG      |   |   |   |   Content of directory /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset:
2024-12-27 09:47:36,427 studio.modulehost    DEBUG      |   |   |   |   |   _meta.yaml
2024-12-27 09:47:36,427 studio.modulehost    DEBUG      |   |   |   |   |   _samples.json
2024-12-27 09:47:36,427 studio.modulehost    DEBUG      |   |   |   |   |   data.dataset
2024-12-27 09:47:36,427 studio.modulehost    DEBUG      |   |   |   |   |   data.dataset.parquet
2024-12-27 09:47:36,427 studio.modulehost    DEBUG      |   |   |   |   |   data.visualization
2024-12-27 09:47:36,432 studio.modulehost    DEBUG      |   |   |   |   |   schema/_schema.json
2024-12-27 09:47:36,432 studio.core          INFO       |   |   |   Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset' - End with 0.0204s elapsed.
2024-12-27 09:47:36,437 studio.core          INFO       |   |   |   Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset via meta - Start:
2024-12-27 09:47:36,607 studio.common        INFO       |   |   |   |   Load DataTableMeta successfully, path=data.dataset
2024-12-27 09:47:36,609 studio.common        INFO       |   |   |   |   Load meta data from directory successfully, data=DataFrameDirectory(meta={'type': 'DataFrameDirectory', 'visualization': [{'type': 'Visualization', 'path': 'data.visualization'}], 'extension': {'DataTableMeta': 'data.dataset'}, 'format': 'Parquet', 'data': 'data.dataset.parquet', 'samples': '_samples.json', 'schema': 'schema/_schema.json'}), type=&lt;class 'azureml.studio.common.datatable.data_table_directory.DataTableDirectory'&gt;
2024-12-27 09:47:36,627 studio.core          INFO       |   |   |   Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset via meta - End with 0.1898s elapsed.
2024-12-27 09:47:36,627 studio.core          INFO       |   |   Handle input port "Dataset" - End with 0.2160s elapsed.
2024-12-27 09:47:36,628 studio.modulehost    INFO       |   |   Parse ColumnSelection parameter
2024-12-27 09:47:36,628 studio.modulehost    INFO       |   |   Parse bool parameter
2024-12-27 09:47:36,628 studio.core          INFO       |   Reflect input ports and parameters - End with 0.2704s elapsed.
2024-12-27 09:47:36,628 studio.core          INFO       |   TrainModelModule.run - Start:
2024-12-27 09:47:36,628 studio.core          DEBUG      |   |   kwargs:
2024-12-27 09:47:36,628 studio.core          DEBUG      |   |   |   learner = &lt;azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400&gt;
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   training_data = &lt;azureml.studio.common.datatable.data_table.DataTable object at 0x14911d183f40&gt;
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   label_column_index_or_name = &lt;azureml.studio.common.datatable.data_table.DataTableColumnSelection object at 0x14914d44a3a0&gt;
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   model_explanations = False
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   validated_args:
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   learner = &lt;azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400&gt;
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   training_data = &lt;azureml.studio.common.datatable.data_table.DataTable object at 0x14911d183f40&gt;
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   label_column_index_or_name = &lt;azureml.studio.common.datatable.data_table.DataTableColumnSelection object at 0x14914d44a3a0&gt;
2024-12-27 09:47:36,629 studio.core          DEBUG      |   |   |   model_explanations = False
2024-12-27 09:47:36,629 studio.module        INFO       |   |   Validate input data (learner and training data).
2024-12-27 09:47:36,629 studio.core          INFO       |   |   Create deployment handler and inject schema and sample. - Start:
2024-12-27 09:47:36,630 studio.core          INFO       |   |   Create deployment handler and inject schema and sample. - End with 0.0010s elapsed.
2024-12-27 09:47:36,630 studio.core          INFO       |   |   BaseLearner.train - Start:
2024-12-27 09:47:36,630 studio.module        INFO       |   |   |   rentals as Label Column.
2024-12-27 09:47:36,632 studio.core          INFO       |   |   |   Removing instances with illegal label - Start:
2024-12-27 09:47:36,632 studio.module        INFO       |   |   |   |   Remove missing label instances.
2024-12-27 09:47:36,637 studio.core          INFO       |   |   |   Removing instances with illegal label - End with 0.0052s elapsed.
2024-12-27 09:47:36,637 studio.module        INFO       |   |   |   validated training data has 512 Row(s) and 12 Columns.
2024-12-27 09:47:36,637 studio.core          INFO       |   |   |   BaseLearner._normalize_data - Start:
2024-12-27 09:47:36,637 studio.core          INFO       |   |   |   |   BaseLearner._fit_normalize - Start:
2024-12-27 09:47:36,637 studio.core          INFO       |   |   |   |   |   Initialing feature normalizer - Start:
2024-12-27 09:47:36,637 studio.module        INFO       |   |   |   |   |   |   Building Normalizer - found Label column=rentals with encode_label=False
2024-12-27 09:47:36,637 studio.module        INFO       |   |   |   |   |   |   Building normalizer - found 11 feature columns with normalize_number=True
2024-12-27 09:47:36,637 studio.module        DEBUG      |   |   |   |   |   |   Building normalizer - found feature columns: "day,mnth,season,holiday,weekday,workingday,weathersit,temp,atemp,hum,windspeed".
2024-12-27 09:47:36,638 studio.module        INFO       |   |   |   |   |   |   Building normalizer - found 11 numeric feature columns and 0 string feature columns to be encoded
2024-12-27 09:47:36,638 studio.module        DEBUG      |   |   |   |   |   |   Building normalizer - found numeric feature columns to be encoded: "day,mnth,season,holiday,weekday,workingday,weathersit,temp,atemp,hum,windspeed".
2024-12-27 09:47:36,638 studio.module        DEBUG      |   |   |   |   |   |   Building normalizer - found string feature columns to be encoded: "".
2024-12-27 09:47:36,638 studio.core          INFO       |   |   |   |   |   Initialing feature normalizer - End with 0.0010s elapsed.
2024-12-27 09:47:36,638 studio.core          INFO       |   |   |   |   |   Fitting feature normalizer - Start:
2024-12-27 09:47:36,638 studio.core          INFO       |   |   |   |   |   |   Normalizer._fit_numeric_feature_column_encoders - Start:
2024-12-27 09:47:36,647 studio.module        INFO       |   |   |   |   |   |   |   Successfully fit 11 numeric feature column encoders.
2024-12-27 09:47:36,647 studio.core          INFO       |   |   |   |   |   |   Normalizer._fit_numeric_feature_column_encoders - End with 0.0086s elapsed.
2024-12-27 09:47:36,647 studio.core          INFO       |   |   |   |   |   Fitting feature normalizer - End with 0.0087s elapsed.
2024-12-27 09:47:36,647 studio.core          INFO       |   |   |   |   BaseLearner._fit_normalize - End with 0.0098s elapsed.
2024-12-27 09:47:36,647 studio.core          INFO       |   |   |   |   BaseLearner._apply_normalize - Start:
2024-12-27 09:47:36,647 studio.core          INFO       |   |   |   |   |   Applying feature normalization - Start:
2024-12-27 09:47:36,647 studio.module        INFO       |   |   |   |   |   |   Start to execute normalizer.transform with column_list: "day,mnth,season,holiday,weekday,workingday,weathersit,temp,atemp,hum,windspeed,rentals".
2024-12-27 09:47:36,647 studio.module        INFO       |   |   |   |   |   |   Columns of input DataFrame: 12
2024-12-27 09:47:36,647 studio.module        INFO       |   |   |   |   |   |   Columns to be transformed: 12
2024-12-27 09:47:36,647 studio.module        INFO       |   |   |   |   |   |   Columns to be encoded: 11
2024-12-27 09:47:36,647 studio.module        INFO       |   |   |   |   |   |   Transform with label column rentals.
2024-12-27 09:47:36,647 studio.core          INFO       |   |   |   |   |   |   Normalizer._transform_numeric_feature_columns - Start:
2024-12-27 09:47:36,653 studio.module        INFO       |   |   |   |   |   |   |   Successfully encoded 11 numeric feature columns.
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   |   |   |   Normalizer._transform_numeric_feature_columns - End with 0.0063s elapsed.
2024-12-27 09:47:36,654 studio.module        INFO       |   |   |   |   |   |   Construct train set complete.
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   |   |   Applying feature normalization - End with 0.0068s elapsed.
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   |   BaseLearner._apply_normalize - End with 0.0069s elapsed.
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   BaseLearner._normalize_data - End with 0.0168s elapsed.
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   Initializing model - Start:
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   Initializing model - End with 0.0000s elapsed.
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   BaseLearner._train - Start:
2024-12-27 09:47:36,654 studio.core          INFO       |   |   |   |   Training Model - Start:
2024-12-27 09:47:36,656 studio.core          INFO       |   |   |   |   Training Model - End with 0.0016s elapsed.
2024-12-27 09:47:36,656 studio.core          INFO       |   |   |   BaseLearner._train - End with 0.0017s elapsed.
2024-12-27 09:47:36,656 studio.core          INFO       |   |   BaseLearner.train - End with 0.0253s elapsed.
2024-12-27 09:47:36,656 studio.core          DEBUG      |   |   return:
2024-12-27 09:47:36,656 studio.core          DEBUG      |   |   |   [0] = &lt;azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400&gt;
2024-12-27 09:47:36,656 studio.core          INFO       |   TrainModelModule.run - End with 0.0275s elapsed.
2024-12-27 09:47:36,656 studio.core          INFO       |   ModuleReflector._handle_output_ports - Start:
2024-12-27 09:47:36,656 studio.core          INFO       |   |   Handle output port "Trained model" - Start:
2024-12-27 09:47:36,656 studio.modulehost    INFO       |   |   |   Data type: ILearnerDotNet
2024-12-27 09:47:36,656 studio.modulehost    INFO       |   |   |   Create directory: '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/Trained_model'
2024-12-27 09:47:36,656 studio.core          INFO       |   |   |   Dump file data.ilearner - Start:
2024-12-27 09:47:36,656 studio.modulehost    INFO       |   |   |   |   Write learner
2024-12-27 09:47:36,657 studio.core          INFO       |   |   |   Dump file data.ilearner - End with 0.0007s elapsed.
2024-12-27 09:47:37,429 studio.common        INFO       |   |   |   Writing meta successfully, datatype=DataTypes.LEARNER
2024-12-27 09:47:37,429 studio.core          INFO       |   |   Handle output port "Trained model" - End with 0.7732s elapsed.
2024-12-27 09:47:37,429 studio.core          INFO       |   ModuleReflector._handle_output_ports - End with 0.7734s elapsed.
2024-12-27 09:47:37,429 studio.core          INFO       |   ModuleStatistics.save_to_azureml - Start:
2024-12-27 09:47:37,594 studio.core          INFO       |   ModuleStatistics.save_to_azureml - End with 0.1646s elapsed.
2024-12-27 09:47:37,595 studio.core          INFO       execute_with_cli - End with 2.6943s elapsed.
Cleaning up all outstanding Run operations, waiting 300.0 seconds
1 items cleaning up...
Cleanup took 0.04007577896118164 seconds
Traceback (most recent call last):
  File "urldecode_invoker.py", line 130, in &lt;module&gt;
    execute(decoded_args)
  File "urldecode_invoker.py", line 74, in execute
    exit(ret)
  File "/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/_sitebuiltins.py", line 26, in __call__
    raise SystemExit(code)
SystemExit: 0

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Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.PipelineRun = azureml.pipeline.core.run:PipelineRun._from_dto with exception (azureml-core 1.47.0 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('azureml-core~=1.54.0')).

Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.ReusedStepRun = azureml.pipeline.core.run:StepRun._from_reused_dto with exception (azureml-core 1.47.0 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('azureml-core~=1.54.0')).

Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.StepRun = azureml.pipeline.core.run:StepRun._from_dto with exception (azureml-core 1.47.0 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('azureml-core~=1.54.0')).

Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.scriptrun = azureml.core.script_run:ScriptRun._from_run_dto with exception (cryptography 42.0.4 (/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages), Requirement.parse('cryptography!=1.9,!=2.0.*,!=2.1.*,!=2.2.*,<41')).

Session_id = 9f298848-ea03-489c-86b5-d39308b98481

Invoking module by urldecode_invoker 0.0.8.

Module type: official module.

Using runpy to invoke module 'azureml.studio.modulehost.module_invoker'.

2024-12-27 09:47:34,900 studio.modulehost INFO Reset logging level to DEBUG

2024-12-27 09:47:34,900 studio.modulehost INFO Load pyarrow.parquet explicitly: <module 'pyarrow.parquet' from '/azureml-envs/azureml_862fbd3b8df44d2c582aa46cf5a23700/lib/python3.8/site-packages/pyarrow/parquet/__init__.py'>

2024-12-27 09:47:34,900 studio.core INFO execute_with_cli - Start:

2024-12-27 09:47:34,900 studio.modulehost INFO | ALGHOST 0.0.182

RuntimeError: module compiled against API version 0x10 but this version of numpy is 0xf . Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem .

IPython could not be loaded!

2024-12-27 09:47:36,155 studio.modulehost INFO | CLI arguments parsed: {'module_name': 'azureml.studio.modules.ml.train.train_generic_model.train_generic_model', 'OutputPortsInternal': {'Trained model': '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/Trained_model'}, 'InputPortsInternal': {'Untrained model': '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model', 'Dataset': '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset'}, 'ModuleParameters': {'Label column': '%7B%22isFilter%22%3Atrue%2C%22rules%22%3A%5B%7B%22exclude%22%3Afalse%2C%22ruleType%22%3A%22ColumnNames%22%2C%22columns%22%3A%5B%22rentals%22%5D%7D%5D%7D', 'Model explanations': 'False'}}

2024-12-27 09:47:36,357 studio.modulehost INFO | Invoking ModuleEntry(azureml.studio.modules.ml.train.train_generic_model.train_generic_model; TrainModelModule; run)

2024-12-27 09:47:36,357 studio.core DEBUG | Input Ports:

2024-12-27 09:47:36,357 studio.core DEBUG | | Untrained model = <azureml.studio.modulehost.cli_parser.CliInputValue object at 0x14911d5b93d0>

2024-12-27 09:47:36,357 studio.core DEBUG | | Dataset = <azureml.studio.modulehost.cli_parser.CliInputValue object at 0x14911d5b9460>

2024-12-27 09:47:36,357 studio.core DEBUG | Output Ports:

2024-12-27 09:47:36,357 studio.core DEBUG | | Trained model = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/Trained_model

2024-12-27 09:47:36,357 studio.core DEBUG | Parameters:

2024-12-27 09:47:36,357 studio.core DEBUG | | Label column = %7B%22isFilter%22%3Atrue%2C%22rules%22%3A%5B%7B%22exclude%22%3Afalse%2C%22ruleType%22%3A%22ColumnNames%22%2C%22columns%22%3A%5B%22rentals%22%5D%7D%5D%7D

2024-12-27 09:47:36,357 studio.core DEBUG | | Model explanations = False

2024-12-27 09:47:36,358 studio.core DEBUG | Environment Variables:

2024-12-27 09:47:36,358 studio.core DEBUG | | AZUREML_DATAREFERENCE_DATASET = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset

2024-12-27 09:47:36,358 studio.core DEBUG | | AZUREML_DATAREFERENCE_Dataset = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset

2024-12-27 09:47:36,358 studio.core DEBUG | | AZUREML_DATAREFERENCE_UNTRAINED_MODEL = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model

2024-12-27 09:47:36,358 studio.core DEBUG | | AZUREML_DATAREFERENCE_Untrained_model = /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model

2024-12-27 09:47:36,358 studio.core INFO | Reflect input ports and parameters - Start:

2024-12-27 09:47:36,358 studio.core INFO | | Handle input port "Untrained model" - Start:

2024-12-27 09:47:36,358 studio.core INFO | | | Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model' - Start:

2024-12-27 09:47:36,358 studio.modulehost DEBUG | | | | Content of directory /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model:

2024-12-27 09:47:36,364 studio.core INFO | | | Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model' - End with 0.0061s elapsed.

2024-12-27 09:47:36,369 studio.core INFO | | | Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model via meta - Start:

2024-12-27 09:47:36,411 studio.common INFO | | | | Load meta data from directory successfully, data=ModelDirectory(meta={'type': 'ModelDirectory', 'extension': {}, 'model': 'model_spec.yaml'}), type=<class 'azureml.studio.core.io.model_directory.ModelDirectory'>

2024-12-27 09:47:36,411 studio.common INFO | | | | Load ModelDirectory successfully, data=<azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400>

2024-12-27 09:47:36,411 studio.core INFO | | | Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Untrained_model via meta - End with 0.0417s elapsed.

2024-12-27 09:47:36,411 studio.core INFO | | Handle input port "Untrained model" - End with 0.0531s elapsed.

2024-12-27 09:47:36,411 studio.core INFO | | Handle input port "Dataset" - Start:

2024-12-27 09:47:36,411 studio.core INFO | | | Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset' - Start:

2024-12-27 09:47:36,411 studio.modulehost DEBUG | | | | Content of directory /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset:

2024-12-27 09:47:36,432 studio.core INFO | | | Mount/Download dataset to '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset' - End with 0.0204s elapsed.

2024-12-27 09:47:36,437 studio.core INFO | | | Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset via meta - Start:

2024-12-27 09:47:36,607 studio.common INFO | | | | Load DataTableMeta successfully, path=data.dataset

2024-12-27 09:47:36,609 studio.common INFO | | | | Load meta data from directory successfully, data=DataFrameDirectory(meta={'type': 'DataFrameDirectory', 'visualization': [{'type': 'Visualization', 'path': 'data.visualization'}], 'extension': {'DataTableMeta': 'data.dataset'}, 'format': 'Parquet', 'data': 'data.dataset.parquet', 'samples': '_samples.json', 'schema': 'schema/_schema.json'}), type=<class 'azureml.studio.common.datatable.data_table_directory.DataTableDirectory'>

2024-12-27 09:47:36,627 studio.core INFO | | | Try to read from /mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/INPUT_Dataset via meta - End with 0.1898s elapsed.

2024-12-27 09:47:36,627 studio.core INFO | | Handle input port "Dataset" - End with 0.2160s elapsed.

2024-12-27 09:47:36,628 studio.modulehost INFO | | Parse ColumnSelection parameter

2024-12-27 09:47:36,628 studio.modulehost INFO | | Parse bool parameter

2024-12-27 09:47:36,628 studio.core INFO | Reflect input ports and parameters - End with 0.2704s elapsed.

2024-12-27 09:47:36,628 studio.core INFO | TrainModelModule.run - Start:

2024-12-27 09:47:36,628 studio.core DEBUG | | kwargs:

2024-12-27 09:47:36,628 studio.core DEBUG | | | learner = <azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400>

2024-12-27 09:47:36,629 studio.core DEBUG | | | training_data = <azureml.studio.common.datatable.data_table.DataTable object at 0x14911d183f40>

2024-12-27 09:47:36,629 studio.core DEBUG | | | label_column_index_or_name = <azureml.studio.common.datatable.data_table.DataTableColumnSelection object at 0x14914d44a3a0>

2024-12-27 09:47:36,629 studio.core DEBUG | | | model_explanations = False

2024-12-27 09:47:36,629 studio.core DEBUG | | validated_args:

2024-12-27 09:47:36,629 studio.core DEBUG | | | learner = <azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400>

2024-12-27 09:47:36,629 studio.core DEBUG | | | training_data = <azureml.studio.common.datatable.data_table.DataTable object at 0x14911d183f40>

2024-12-27 09:47:36,629 studio.core DEBUG | | | label_column_index_or_name = <azureml.studio.common.datatable.data_table.DataTableColumnSelection object at 0x14914d44a3a0>

2024-12-27 09:47:36,629 studio.core DEBUG | | | model_explanations = False

2024-12-27 09:47:36,629 studio.module INFO | | Validate input data (learner and training data).

2024-12-27 09:47:36,629 studio.core INFO | | Create deployment handler and inject schema and sample. - Start:

2024-12-27 09:47:36,630 studio.core INFO | | Create deployment handler and inject schema and sample. - End with 0.0010s elapsed.

2024-12-27 09:47:36,630 studio.core INFO | | BaseLearner.train - Start:

2024-12-27 09:47:36,630 studio.module INFO | | | rentals as Label Column.

2024-12-27 09:47:36,632 studio.core INFO | | | Removing instances with illegal label - Start:

2024-12-27 09:47:36,632 studio.module INFO | | | | Remove missing label instances.

2024-12-27 09:47:36,637 studio.core INFO | | | Removing instances with illegal label - End with 0.0052s elapsed.

2024-12-27 09:47:36,637 studio.module INFO | | | validated training data has 512 Row(s) and 12 Columns.

2024-12-27 09:47:36,637 studio.core INFO | | | BaseLearner._normalize_data - Start:

2024-12-27 09:47:36,637 studio.core INFO | | | | BaseLearner._fit_normalize - Start:

2024-12-27 09:47:36,637 studio.module INFO | | | | | | Building Normalizer - found Label column=rentals with encode_label=False

2024-12-27 09:47:36,637 studio.module INFO | | | | | | Building normalizer - found 11 feature columns with normalize_number=True

2024-12-27 09:47:36,637 studio.module DEBUG | | | | | | Building normalizer - found feature columns: "day,mnth,season,holiday,weekday,workingday,weathersit,temp,atemp,hum,windspeed".

2024-12-27 09:47:36,638 studio.module INFO | | | | | | Building normalizer - found 11 numeric feature columns and 0 string feature columns to be encoded

2024-12-27 09:47:36,638 studio.module DEBUG | | | | | | Building normalizer - found numeric feature columns to be encoded: "day,mnth,season,holiday,weekday,workingday,weathersit,temp,atemp,hum,windspeed".

2024-12-27 09:47:36,638 studio.module DEBUG | | | | | | Building normalizer - found string feature columns to be encoded: "".

2024-12-27 09:47:36,638 studio.core INFO | | | | | Initialing feature normalizer - End with 0.0010s elapsed.

2024-12-27 09:47:36,638 studio.core INFO | | | | | | Normalizer._fit_numeric_feature_column_encoders - Start:

2024-12-27 09:47:36,647 studio.module INFO | | | | | | | Successfully fit 11 numeric feature column encoders.

2024-12-27 09:47:36,647 studio.core INFO | | | | | | Normalizer._fit_numeric_feature_column_encoders - End with 0.0086s elapsed.

2024-12-27 09:47:36,647 studio.core INFO | | | | | Fitting feature normalizer - End with 0.0087s elapsed.

2024-12-27 09:47:36,647 studio.core INFO | | | | BaseLearner._fit_normalize - End with 0.0098s elapsed.

2024-12-27 09:47:36,647 studio.core INFO | | | | BaseLearner._apply_normalize - Start:

2024-12-27 09:47:36,647 studio.module INFO | | | | | | Start to execute normalizer.transform with column_list: "day,mnth,season,holiday,weekday,workingday,weathersit,temp,atemp,hum,windspeed,rentals".

2024-12-27 09:47:36,647 studio.core INFO | | | | | | Normalizer._transform_numeric_feature_columns - Start:

2024-12-27 09:47:36,653 studio.module INFO | | | | | | | Successfully encoded 11 numeric feature columns.

2024-12-27 09:47:36,654 studio.core INFO | | | | | | Normalizer._transform_numeric_feature_columns - End with 0.0063s elapsed.

2024-12-27 09:47:36,654 studio.core INFO | | | | | Applying feature normalization - End with 0.0068s elapsed.

2024-12-27 09:47:36,654 studio.core INFO | | | | BaseLearner._apply_normalize - End with 0.0069s elapsed.

2024-12-27 09:47:36,654 studio.core INFO | | | BaseLearner._normalize_data - End with 0.0168s elapsed.

2024-12-27 09:47:36,654 studio.core INFO | | | Initializing model - Start:

2024-12-27 09:47:36,654 studio.core INFO | | | Initializing model - End with 0.0000s elapsed.

2024-12-27 09:47:36,654 studio.core INFO | | | BaseLearner._train - Start:

2024-12-27 09:47:36,654 studio.core INFO | | | | Training Model - Start:

2024-12-27 09:47:36,656 studio.core INFO | | | | Training Model - End with 0.0016s elapsed.

2024-12-27 09:47:36,656 studio.core INFO | | | BaseLearner._train - End with 0.0017s elapsed.

2024-12-27 09:47:36,656 studio.core INFO | | BaseLearner.train - End with 0.0253s elapsed.

2024-12-27 09:47:36,656 studio.core DEBUG | | return:

2024-12-27 09:47:36,656 studio.core DEBUG | | | [0] = <azureml.studio.modules.ml.initialize_models.regressor.linear_regressor.linear_regressor.OrdinaryLeastSquaresRegressor object at 0x14911d5b9400>

2024-12-27 09:47:36,656 studio.core INFO | TrainModelModule.run - End with 0.0275s elapsed.

2024-12-27 09:47:36,656 studio.core INFO | ModuleReflector._handle_output_ports - Start:

2024-12-27 09:47:36,656 studio.core INFO | | Handle output port "Trained model" - Start:

2024-12-27 09:47:36,656 studio.modulehost INFO | | | Data type: ILearnerDotNet

2024-12-27 09:47:36,656 studio.modulehost INFO | | | Create directory: '/mnt/azureml/cr/j/238106928513406aada505c2bb655d5b/cap/data-capability/wd/Trained_model'