Failure when trying to Create new Packages via Pipeline

[Anandhavalli_A]

I have seen the Failre log and pastng for reference.

2022-07-06 00:58:49,757 - uipath_core.trainer_run:main:73 - INFO: Starting training job…
2022-07-06 00:58:53,178 - matplotlib:_get_config_or_cache_dir:484 - WARNING: Matplotlib created a temporary config/cache directory at /tmp/matplotlib-_2c0rldt because the default path (/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
2022-07-06 00:58:54,001 - matplotlib.font_manager:_load_fontmanager:1443 - INFO: generated new fontManager
2022-07-06 00:58:56,783 - uipath_core.storage.azure_storage_client:download:112 - INFO: Dataset from bucket folder training-49aa85ea-2b71-479f-aae1-db1d6c2f3371/9877f90d-d8f6-4f8b-95b6-872d6e8ef9b7/ca150876-0c82-455d-81d1-9e082800ce2b/export/invoice_healthcare_1_22-07-05T212300 with size 44 downloaded successfully
2022-07-06 00:58:56,783 - uipath_core.training_plugin:train_model:114 - INFO: Start model training…
2022-07-06 00:58:56,783 - uipath_core.training_plugin:initialize_model:108 - INFO: Start model initialization…
2022-07-06 00:58:56,785 - root:initialize_package:145 - INFO: Using package type provided by runtime argument with value: invoices
2022-07-06 00:58:56,785 - root:initialize_package:154 - INFO: Initializing invoices package options …
2022-07-06 00:58:56,787 - root:configure_options:158 - INFO: Document type invoices language: en
2022-07-06 00:58:56,787 - root:initialize_tokenizer:49 - INFO: Loading cached BERT tokenizer at /workspace/model/microservice/bert-base-multilingual-uncased_tokenizer
2022-07-06 00:58:56,872 - root:initialize_package:159 - INFO: System-Level Configuration:
2022-07-06 00:58:56,872 - root:initialize_package:160 - INFO: ATen/Parallel:
at::get_num_threads() : 3
at::get_num_interop_threads() : 2
OpenMP 201511 (a.k.a. OpenMP 4.5)
omp_get_max_threads() : 3
Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
mkl_get_max_threads() : 3
Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
std::hardware_concurrency() : 4
Environment variables:
OMP_NUM_THREADS : 3
MKL_NUM_THREADS : [not set]
ATen parallel backend: OpenMP

2022-07-06 00:58:56,873 - root:configure_options:158 - INFO: Document type invoices language: en
2022-07-06 00:58:56,873 - uipath_core.training_plugin:initialize_model:111 - INFO: Model initialized successfully
2022-07-06 00:58:56,873 - root:log_data_version_info:13 - INFO: =========Data version information=========
2022-07-06 00:58:56,886 - root:log_data_version_info:17 - WARNING: Unknown data version:
2022-07-06 00:58:56,887 - root:log_data_version_info:17 - INFO: ==========================================
2022-07-06 00:58:56,888 - root:preprocess_data:603 - INFO: Creating dataset for document type invoices…
2022-07-06 00:58:57,146 - root:preprocess_data:605 - INFO: Doctype invoices Statistics:
2022-07-06 00:58:57,146 - root:preprocess_data:608 - INFO:
Extraction fields:
tag = 9129
tag[billing-name] = 50
tag[invoice-no] = 10
tag[total] = 10
tag[due-date] = 10

Subsets:
subset[TEST] = 10

2022-07-06 00:59:12,167 - root:preprocess_data:676 - INFO: train: (0, 15) pages
2022-07-06 00:59:12,167 - root:preprocess_data:677 - INFO: test: (0, 15) pages
2022-07-06 00:59:12,168 - root:preprocess_dataset:49 - ERROR: Dataset preprocess Failed
Traceback (most recent call last):
File “”, line 48, in preprocess_dataset
File “”, line 143, in init
File “”, line 31, in init
File “”, line 678, in preprocess_data
AssertionError: Training and / or validation set is empty, verify that training / validation split is correctly set
2022-07-06 00:59:12,171 - uipath_core.training_plugin:model_run:150 - ERROR: Training failed for pipeline type: TRAIN_ONLY, error: Dataset preprocess Failed
2022-07-06 00:59:12,176 - uipath_core.trainer_run:main:90 - ERROR: Training Job failed, error: Dataset preprocess Failed
Traceback (most recent call last):
File “”, line 48, in preprocess_dataset
File “”, line 143, in init
File “”, line 31, in init
File “”, line 678, in preprocess_data
AssertionError: Training and / or validation set is empty, verify that training / validation split is correctly set

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File “/model/bin/uipath_core/trainer_run.py”, line 85, in main
wrapper.run()
File “/workspace/model/microservice/training_wrapper.py”, line 64, in run
return self.training_plugin.model_run()
File “/model/bin/uipath_core/training_plugin.py”, line 151, in model_run
raise e
File “/model/bin/uipath_core/training_plugin.py”, line 143, in model_run
self.run_train_only()
File “/model/bin/uipath_core/training_plugin.py”, line 212, in run_train_only
self.train_model(self.local_dataset_directory)
File “/model/bin/uipath_core/training_plugin.py”, line 116, in train_model
self.model.train(directory)
File “/workspace/model/microservice/train.py”, line 36, in train
self.process_data()
File “/workspace/model/microservice/train.py”, line 69, in process_data
self.trainer.preprocess_dataset()
File “”, line 49, in preprocess_dataset
Exception: Dataset preprocess Failed
2022-07-06 00:59:47,362 - uipath_core.trainer_run:main:73 - INFO: Starting training job…
2022-07-06 00:59:50,793 - matplotlib:_get_config_or_cache_dir:484 - WARNING: Matplotlib created a temporary config/cache directory at /tmp/matplotlib-2d6j2p4z because the default path (/.config/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.
2022-07-06 00:59:51,569 - matplotlib.font_manager:_load_fontmanager:1443 - INFO: generated new fontManager
2022-07-06 00:59:52,830 - uipath_core.logs.upload_log_service:upload_logs_file:87 - INFO: Retry Training Triggered:
2022-07-06 00:59:53,952 - uipath_core.storage.azure_storage_client:download:112 - INFO: Dataset from bucket folder training-49aa85ea-2b71-479f-aae1-db1d6c2f3371/9877f90d-d8f6-4f8b-95b6-872d6e8ef9b7/ca150876-0c82-455d-81d1-9e082800ce2b/export/invoice_healthcare_1_22-07-05T212300 with size 44 downloaded successfully
2022-07-06 00:59:53,953 - uipath_core.training_plugin:train_model:114 - INFO: Start model training…
2022-07-06 00:59:53,953 - uipath_core.training_plugin:initialize_model:108 - INFO: Start model initialization…
2022-07-06 00:59:53,954 - root:initialize_package:145 - INFO: Using package type provided by runtime argument with value: invoices
2022-07-06 00:59:53,954 - root:initialize_package:154 - INFO: Initializing invoices package options …
2022-07-06 00:59:53,955 - root:configure_options:158 - INFO: Document type invoices language: en
2022-07-06 00:59:53,955 - root:initialize_tokenizer:49 - INFO: Loading cached BERT tokenizer at /workspace/model/microservice/bert-base-multilingual-uncased_tokenizer
2022-07-06 00:59:54,028 - root:initialize_package:159 - INFO: System-Level Configuration:
2022-07-06 00:59:54,029 - root:initialize_package:160 - INFO: ATen/Parallel:
at::get_num_threads() : 3
at::get_num_interop_threads() : 2
OpenMP 201511 (a.k.a. OpenMP 4.5)
omp_get_max_threads() : 3
Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
mkl_get_max_threads() : 3
Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
std::hardware_concurrency() : 4
Environment variables:
OMP_NUM_THREADS : 3
MKL_NUM_THREADS : [not set]
ATen parallel backend: OpenMP

2022-07-06 00:59:54,030 - root:configure_options:158 - INFO: Document type invoices language: en
2022-07-06 00:59:54,030 - uipath_core.training_plugin:initialize_model:111 - INFO: Model initialized successfully
2022-07-06 00:59:54,030 - root:log_data_version_info:13 - INFO: =========Data version information=========
2022-07-06 00:59:54,044 - root:log_data_version_info:17 - WARNING: Unknown data version:
2022-07-06 00:59:54,044 - root:log_data_version_info:17 - INFO: ==========================================
2022-07-06 00:59:54,045 - root:preprocess_data:603 - INFO: Creating dataset for document type invoices…
2022-07-06 00:59:54,277 - root:preprocess_data:605 - INFO: Doctype invoices Statistics:
2022-07-06 00:59:54,277 - root:preprocess_data:608 - INFO:
Extraction fields:
tag = 9129
tag[billing-name] = 50
tag[invoice-no] = 10
tag[total] = 10
tag[due-date] = 10

Subsets:
subset[TEST] = 10

2022-07-06 01:00:09,418 - root:preprocess_data:676 - INFO: train: (0, 15) pages
2022-07-06 01:00:09,418 - root:preprocess_data:677 - INFO: test: (0, 15) pages
2022-07-06 01:00:09,418 - root:preprocess_dataset:49 - ERROR: Dataset preprocess Failed
Traceback (most recent call last):
File “”, line 48, in preprocess_dataset
File “”, line 143, in init
File “”, line 31, in init
File “”, line 678, in preprocess_data
AssertionError: Training and / or validation set is empty, verify that training / validation split is correctly set
2022-07-06 01:00:09,422 - uipath_core.training_plugin:model_run:150 - ERROR: Training failed for pipeline type: TRAIN_ONLY, error: Dataset preprocess Failed
2022-07-06 01:00:09,427 - uipath_core.trainer_run:main:90 - ERROR: Training Job failed, error: Dataset preprocess Failed
Traceback (most recent call last):
File “”, line 48, in preprocess_dataset
File “”, line 143, in init
File “”, line 31, in init
File “”, line 678, in preprocess_data
AssertionError: Training and / or validation set is empty, verify that training / validation split is correctly set

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File “/model/bin/uipath_core/trainer_run.py”, line 85, in main
wrapper.run()
File “/workspace/model/microservice/training_wrapper.py”, line 64, in run
return self.training_plugin.model_run()
File “/model/bin/uipath_core/training_plugin.py”, line 151, in model_run
raise e
File “/model/bin/uipath_core/training_plugin.py”, line 143, in model_run
self.run_train_only()
File “/model/bin/uipath_core/training_plugin.py”, line 212, in run_train_only
self.train_model(self.local_dataset_directory)
File “/model/bin/uipath_core/training_plugin.py”, line 116, in train_model
self.model.train(directory)
File “/workspace/model/microservice/train.py”, line 36, in train
self.process_data()
File “/workspace/model/microservice/train.py”, line 69, in process_data
self.trainer.preprocess_dataset()
File “”, line 49, in preprocess_dataset
Exception: Dataset preprocess Failed

Please let me know how to fix it

[system]

Hello @Anandhavalli_A!

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[SrenivasanKanna (Srenivasan kannan)]

AI Center - ML Skill Failed / Kubernetes operation failed to create deployment

Hi, We do not select the option (Make this an Evaluation Set) while importing your documents if you want to run your pipeline as Train run. [image] Make Sure that, the pipeline will be run based on the Data set Import. If you Choose as Evaluation set, The pipeline will get success only if you choose Evaluation run. The Suggested way is - to use Train run to improve your ML Skill and the evaluation run does not improve your ML Skill. Error Occurred : Resolved ML Skill Failed / Kubernete…

[Anandhavalli_A]

This worked ! Thank you @SrenivasanKanna