diff --git a/mlops/unit_2_training/custom/dashboard_data_source.py b/mlops/unit_2_training/custom/dashboard_data_source.py index 46954395a..48d219b37 100644 --- a/mlops/unit_2_training/custom/dashboard_data_source.py +++ b/mlops/unit_2_training/custom/dashboard_data_source.py @@ -2,6 +2,7 @@ from pandas import Series from scipy.sparse import csr_matrix +from sklearn.base import BaseEstimator from xgboost import Booster if 'custom' not in globals(): @@ -10,7 +11,7 @@ @custom def source( - model: Booster, + training_results: Tuple[Booster, BaseEstimator], settings: Tuple[ Dict[str, Union[bool, float, int, str]], csr_matrix, @@ -18,6 +19,7 @@ def source( ], **kwargs, ) -> Tuple[Booster, csr_matrix, csr_matrix]: + model, _ = training_results _, X_train, y_train = settings return model, X_train, y_train diff --git a/mlops/unit_3_observability/custom/dashboard_data_source.py b/mlops/unit_3_observability/custom/dashboard_data_source.py index 46954395a..48d219b37 100644 --- a/mlops/unit_3_observability/custom/dashboard_data_source.py +++ b/mlops/unit_3_observability/custom/dashboard_data_source.py @@ -2,6 +2,7 @@ from pandas import Series from scipy.sparse import csr_matrix +from sklearn.base import BaseEstimator from xgboost import Booster if 'custom' not in globals(): @@ -10,7 +11,7 @@ @custom def source( - model: Booster, + training_results: Tuple[Booster, BaseEstimator], settings: Tuple[ Dict[str, Union[bool, float, int, str]], csr_matrix, @@ -18,6 +19,7 @@ def source( ], **kwargs, ) -> Tuple[Booster, csr_matrix, csr_matrix]: + model, _ = training_results _, X_train, y_train = settings return model, X_train, y_train diff --git a/mlops/unit_4_triggering/custom/dashboard_data_source.py b/mlops/unit_4_triggering/custom/dashboard_data_source.py index e24839641..48d219b37 100644 --- a/mlops/unit_4_triggering/custom/dashboard_data_source.py +++ b/mlops/unit_4_triggering/custom/dashboard_data_source.py @@ -2,6 +2,7 @@ from pandas import Series from scipy.sparse import csr_matrix +from sklearn.base import BaseEstimator from xgboost import Booster if 'custom' not in globals(): @@ -10,7 +11,7 @@ @custom def source( - model: Booster, + training_results: Tuple[Booster, BaseEstimator], settings: Tuple[ Dict[str, Union[bool, float, int, str]], csr_matrix, @@ -18,6 +19,7 @@ def source( ], **kwargs, ) -> Tuple[Booster, csr_matrix, csr_matrix]: + model, _ = training_results _, X_train, y_train = settings - return model, X_train, y_train + return model, X_train, y_train diff --git a/mlops/unit_4_triggering/pipelines/xgboost_training/metadata.yaml b/mlops/unit_4_triggering/pipelines/xgboost_training/metadata.yaml index 8019e454e..eac434ca5 100755 --- a/mlops/unit_4_triggering/pipelines/xgboost_training/metadata.yaml +++ b/mlops/unit_4_triggering/pipelines/xgboost_training/metadata.yaml @@ -1,92 +1,92 @@ blocks: - - all_upstream_blocks_executed: true - color: null - configuration: - global_data_product: - uuid: training_set - downstream_blocks: - - xgboost - executor_config: null - executor_type: local_python - has_callback: false - language: python - name: Training set - retry_config: null - status: executed - timeout: null - type: global_data_product - upstream_blocks: [] - uuid: training_set - - all_upstream_blocks_executed: true - color: null - configuration: - file_path: transformers/hyperparameter_tuning/xgboost.py - file_source: - path: unit_2_training/transformers/hyperparameter_tuning/xgboost.py - downstream_blocks: - - xgboost - - dashboard_data_source - executor_config: null - executor_type: local_python - has_callback: false - language: python - name: xgboost Hyperparameter tuning - retry_config: null - status: executed - timeout: null - type: transformer - upstream_blocks: - - training_set - uuid: hyperparameter_tuning/xgboost - - all_upstream_blocks_executed: true - color: null - configuration: - file_path: data_exporters/xgboost.py - file_source: - path: unit_2_training/data_exporters/xgboost.py - downstream_blocks: - - dashboard_data_source - executor_config: null - executor_type: local_python - has_callback: false - language: python - name: XGBoost - retry_config: null - status: updated - timeout: null - type: data_exporter - upstream_blocks: - - training_set - - hyperparameter_tuning/xgboost - uuid: xgboost - - all_upstream_blocks_executed: false - color: pink - configuration: - file_path: custom/dashboard_data_source.py - file_source: - path: unit_2_training/custom/dashboard_data_source.py - downstream_blocks: [] - executor_config: null - executor_type: local_python - has_callback: false - language: python - name: Dashboard data source - retry_config: null - status: executed - timeout: null - type: custom - upstream_blocks: - - xgboost - - hyperparameter_tuning/xgboost - uuid: dashboard_data_source +- all_upstream_blocks_executed: true + color: null + configuration: + global_data_product: + uuid: training_set + downstream_blocks: + - xgboost + executor_config: null + executor_type: local_python + has_callback: false + language: python + name: Training set + retry_config: null + status: executed + timeout: null + type: global_data_product + upstream_blocks: [] + uuid: training_set +- all_upstream_blocks_executed: true + color: null + configuration: + file_path: transformers/hyperparameter_tuning/xgboost.py + file_source: + path: unit_2_training/transformers/hyperparameter_tuning/xgboost.py + downstream_blocks: + - xgboost + - dashboard_data_source + executor_config: null + executor_type: local_python + has_callback: false + language: python + name: xgboost Hyperparameter tuning + retry_config: null + status: executed + timeout: null + type: transformer + upstream_blocks: + - training_set + uuid: hyperparameter_tuning/xgboost +- all_upstream_blocks_executed: true + color: null + configuration: + file_path: data_exporters/xgboost.py + file_source: + path: unit_2_training/data_exporters/xgboost.py + downstream_blocks: + - dashboard_data_source + executor_config: null + executor_type: local_python + has_callback: false + language: python + name: XGBoost + retry_config: null + status: updated + timeout: null + type: data_exporter + upstream_blocks: + - training_set + - hyperparameter_tuning/xgboost + uuid: xgboost +- all_upstream_blocks_executed: false + color: pink + configuration: + file_path: custom/dashboard_data_source.py + file_source: + path: unit_2_training/custom/dashboard_data_source.py + downstream_blocks: [] + executor_config: null + executor_type: local_python + has_callback: false + language: python + name: Dashboard data source + retry_config: null + status: executed + timeout: null + type: custom + upstream_blocks: + - xgboost + - hyperparameter_tuning/xgboost + uuid: dashboard_data_source cache_block_output_in_memory: false callbacks: [] concurrency_config: {} conditionals: [] -created_at: "2024-05-07 18:27:34.902705+00:00" +created_at: '2024-05-07 18:27:34.902705+00:00' data_integration: null -description: "XGBoost is a scalable and efficient implementation of gradient boosted - decision trees, a powerful ensemble machine learning technique. " +description: 'XGBoost is a scalable and efficient implementation of gradient boosted + decision trees, a powerful ensemble machine learning technique. ' executor_config: {} executor_count: 1 executor_type: null @@ -106,4 +106,5 @@ variables: early_stopping_rounds: 1 max_depth: 1 max_evaluations: 1 +variables_dir: /root/.mage_data/unit_4_triggering widgets: []