Constantly getting this error while training Deep and Wide model. Model is expected to be fed with features: ['feature_user_feature_2', ....

asharib.waheed 1 Reputation point
2022-11-12T08:02:13.527+00:00

Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.PipelineRun = azureml.pipeline.core.run:PipelineRun._from_dto with exception (azure-mgmt-core 1.3.0 (/azureml-envs/azureml_1c52c6e25bd3041eabbd9a52168ae46/lib/python3.8/site-packages), Requirement.parse('azure-mgmt-core<2.0.0,>=1.3.1'), {'azure-mgmt-keyvault'}).
Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.ReusedStepRun = azureml.pipeline.core.run:StepRun._from_reused_dto with exception (azure-mgmt-core 1.3.0 (/azureml-envs/azureml_1c52c6e25bd3041eabbd9a52168ae46/lib/python3.8/site-packages), Requirement.parse('azure-mgmt-core<2.0.0,>=1.3.1'), {'azure-mgmt-keyvault'}).
Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.StepRun = azureml.pipeline.core.run:StepRun._from_dto with exception (azure-mgmt-core 1.3.0 (/azureml-envs/azureml_1c52c6e25bd3041eabbd9a52168ae46/lib/python3.8/site-packages), Requirement.parse('azure-mgmt-core<2.0.0,>=1.3.1'), {'azure-mgmt-keyvault'}).
Failure while loading azureml_run_type_providers. Failed to load entrypoint azureml.scriptrun = azureml.core.script_run:ScriptRun._from_run_dto with exception (azure-mgmt-core 1.3.0 (/azureml-envs/azureml_1c52c6e25bd3041eabbd9a52168ae46/lib/python3.8/site-packages), Requirement.parse('azure-mgmt-core<2.0.0,>=1.3.1'), {'azure-mgmt-keyvault'}).
Session_id = 84c324df-90e3-4d06-963d-c896854583
Invoking module by urldecode_invoker 0.0.8.

Module type: custom module.

Using runpy to invoke module 'azureml.designer.modules.recommendation.dnn.wide_and_deep.train.run'.

2022-11-06 17:12:43.374707: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /azureml-envs/azureml_1c52c6e25bd041eabbd9a52168ae46/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2022-11-06 17:12:43.374762: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2022-11-06 17:12:45,992 studio.common INFO azureml-designer-recommender-modules 0.0.54
2022-11-06 17:12:51,404 studio.core INFO preprocess_transactions - Start:
2022-11-06 17:13:06,585 studio.core INFO preprocess_transactions - End with 15.1769s elapsed.
2022-11-06 17:13:06,589 studio.core INFO preprocess_features - Start:
2022-11-06 17:13:06,607 studio.core INFO preprocess_features - End with 0.0176s elapsed.
2022-11-06 17:13:06,607 studio.core INFO preprocess_features - Start:
2022-11-06 17:13:06,666 studio.core INFO preprocess_features - End with 0.0583s elapsed.
2022-11-06 17:13:12,074 studio.common INFO Get 10 features
2022-11-06 17:13:12,166 studio.common INFO Create feature metas for 10 features
2022-11-06 17:13:14,412 studio.common INFO Get 1 features
/azureml-envs/azureml_1c52c6e25bd3041eabbd9a52168ae46/lib/python3.8/site-packages/pandas/core/generic.py:6245: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
self._update_inplace(new_data)
2022-11-06 17:13:14,466 studio.common INFO Create feature metas for 1 features
2022-11-06 17:13:14,500 studio.common DEBUG Init train input function builder.
2022-11-06 17:13:14,503 studio.common INFO Build 10 features for User ids.
2022-11-06 17:13:17,704 studio.common INFO Process null values for features.
2022-11-06 17:13:17,736 studio.common INFO Build 1 features for Item ids.
2022-11-06 17:13:20,012 studio.common INFO Process null values for features.
2022-11-06 17:13:26,398 studio.module INFO Get 5775792 training instances, and 90247.0 batches per epoch.
2022-11-06 17:13:29,489 studio.module INFO Build model:
Epochs: 15
Batch size: 64
Wide optimizer: OptimizerSelection.Adagrad
Wide learning rate: 0.1
Deep optimizer: OptimizerSelection.Adagrad
Deep learning rate: 0.1
Hidden units: (256, 128)
Activation function: ActivationFnSelection.ReLU
Dropout: 0.8
Batch norm: True
Crossed dimension: 1000
User embedding dimension: 16
Item embedding dimension: 16
Categorical feature embedding dimension: 4
2022-11-06 17:13:29,546 studio.module INFO Model is expected to be fed with features: ['feature_user_feature_2', 'feature_user_feature_8', 'feature_user_feature_3', 'feature_user_feature_9', 'feature_user_feature_4', 'feature_item_feature_0', 'User', 'Item', 'feature_user_feature_5', 'feature_user_feature_1', 'feature_user_feature_6', 'feature_user_feature_0', 'feature_user_feature_7']
2022-11-06 17:13:30,077 tensorflow INFO Using config: {'_model_dir': '/tmp/tmp7lhxl5n0/checkpoints', '_tf_random_seed': 42, '_save_summary_steps': 100, '_save_checkpoints_steps': 1353705.0, '_save_checkpoints_secs': None, '_session_config': allow_soft_placement: true
graph_options {
rewrite_options {
meta_optimizer_iterations: ONE
}
}
, '_keep_checkpoint_max': 1, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 90247.0, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}

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