fix

mage-ai · May 14, 2024 · 9b2e2ec · 9b2e2ec
1 parent a61bead
commit 9b2e2ec
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Showing 4 changed files with 94 additions and 87 deletions.
diff --git 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():
@@ -10,14 +11,15 @@
 
 @custom
 def source(
-    model: Booster,
+    training_results: Tuple[Booster, BaseEstimator],
     settings: Tuple[
         Dict[str, Union[bool, float, int, str]],
         csr_matrix,
         Series,
     ],
     **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
@@ -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():
@@ -10,14 +11,15 @@
 
 @custom
 def source(
-    model: Booster,
+    training_results: Tuple[Booster, BaseEstimator],
     settings: Tuple[
         Dict[str, Union[bool, float, int, str]],
         csr_matrix,
         Series,
     ],
     **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
@@ -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():
@@ -10,14 +11,15 @@
 
 @custom
 def source(
-    model: Booster, 
+    training_results: Tuple[Booster, BaseEstimator],
     settings: Tuple[
         Dict[str, Union[bool, float, int, str]],
         csr_matrix,
         Series,
     ],
     **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
@@ -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: []