renaming the main module from forecasting_sa to mmf_sa

forecasting_sa/AutoEDA.py → mmf_sa/AutoEDA.py

@@ -385,10 +385,10 @@ def add_title_and_describtion(self, html_object: str, title: "", describtion: ""
 
     def report_generation_new(self):
         def load_html():
-            import forecasting_sa.html_templates
+            import mmf_sa.html_templates
 
             html_template = pkg_resources.read_text(
-                sys.modules["forecasting_sa.html_templates"], "eda_template_v2.html"
+                sys.modules["mmf_sa.html_templates"], "eda_template_v2.html"
             )
             return html_template
 

forecasting_sa/Forecaster.py → mmf_sa/Forecaster.py

@@ -28,9 +28,9 @@
     IntegerType,
 )
 from pyspark.sql.functions import lit, avg, min, max, col, posexplode, collect_list, to_date
-from forecasting_sa.models.abstract_model import ForecastingRegressor
-from forecasting_sa.models import ModelRegistry
-from forecasting_sa.data_quality_checks import DataQualityChecks
+from mmf_sa.models.abstract_model import ForecastingRegressor
+from mmf_sa.models import ModelRegistry
+from mmf_sa.data_quality_checks import DataQualityChecks
 _logger = logging.getLogger(__name__)
 os.environ['NIXTLA_ID_AS_COL'] = '1'
 mlflow.set_registry_uri("databricks-uc")

forecasting_sa/__init__.py → mmf_sa/__init__.py

@@ -12,7 +12,7 @@
 from omegaconf.basecontainer import BaseContainer
 from pyspark.sql import SparkSession, DataFrame
 
-from forecasting_sa.Forecaster import Forecaster
+from mmf_sa.Forecaster import Forecaster
 
 
 def run_forecast(

forecasting_sa/jobs/eda_job.py → mmf_sa/jobs/eda_job.py

@@ -1,8 +1,8 @@
 import mlflow
 from mlflow.tracking import MlflowClient
 
-from forecasting_sa.AutoEDA import AutoEDA
-from forecasting_sa.common import Job
+from mmf_sa.AutoEDA import AutoEDA
+from mmf_sa.common import Job
 
 
 class EDAJob(Job):

forecasting_sa/jobs/forecasting_job.py → mmf_sa/jobs/forecasting_job.py

@@ -1,8 +1,8 @@
 import mlflow
 from mlflow.tracking import MlflowClient
 
-from forecasting_sa.Forecaster import Forecaster
-from forecasting_sa.common import Job
+from mmf_sa.Forecaster import Forecaster
+from mmf_sa.common import Job
 
 
 class ForecastingJob(Job):

forecasting_sa/jobs/retraining_evaluation_job.py → mmf_sa/jobs/retraining_evaluation_job.py

@@ -1,8 +1,8 @@
 import mlflow
 from mlflow.tracking import MlflowClient
 
-from forecasting_sa.Forecaster import Forecaster
-from forecasting_sa.common import Job
+from mmf_sa.Forecaster import Forecaster
+from mmf_sa.common import Job
 
 
 class RetrainingEvaluationJob(Job):

forecasting_sa/models/__init__.py → mmf_sa/models/__init__.py

@@ -2,7 +2,7 @@
 import sys
 import importlib.resources as pkg_resources
 from omegaconf import OmegaConf, DictConfig
-from forecasting_sa.models.abstract_model import ForecastingRegressor
+from mmf_sa.models.abstract_model import ForecastingRegressor
 
 
 class ModelRegistry:

forecasting_sa/models/abstract_model.py → mmf_sa/models/abstract_model.py

@@ -25,7 +25,7 @@ def prepare_data(self, df: pd.DataFrame) -> pd.DataFrame:
         return df
 
     @abstractmethod
-    def fit(self, x, y=None, spark=None):
+    def fit(self, x, y=None):
         pass
 
     @abstractmethod

forecasting_sa/models/models_conf.yaml → mmf_sa/models/models_conf.yaml

@@ -19,7 +19,7 @@ promoted_props:
 models:
 
   StatsForecastBaselineWindowAverage:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcBaselineWindowAverage
     framework: StatsForecast
     model_type: local
@@ -28,7 +28,7 @@ models:
       window_size: 7
 
   StatsForecastBaselineSeasonalWindowAverage:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcBaselineSeasonalWindowAverage
     framework: StatsForecast
     model_type: local
@@ -38,14 +38,14 @@ models:
       window_size: 7
 
   StatsForecastBaselineNaive:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcBaselineNaive
     framework: StatsForecast
     model_type: local
     trainable: false
 
   StatsForecastBaselineSeasonalNaive:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcBaselineSeasonalNaive
     framework: StatsForecast
     model_type: local
@@ -54,7 +54,7 @@ models:
       season_length: 7
 
   StatsForecastAutoArima:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcAutoArima
     framework: StatsForecast
     model_type: local
@@ -65,7 +65,7 @@ models:
       level:
 
   StatsForecastAutoETS:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcAutoETS
     framework: StatsForecast
     model_type: local
@@ -75,7 +75,7 @@ models:
       model_type: "ZZZ"
 
   StatsForecastAutoCES:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcAutoCES
     framework: StatsForecast
     model_type: local
@@ -85,7 +85,7 @@ models:
       model_type: "Z"
 
   StatsForecastAutoTheta:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcAutoTheta
     framework: StatsForecast
     model_type: local
@@ -95,7 +95,7 @@ models:
       decomposition_type: "multiplicative"
 
   StatsForecastTSB:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcTSB
     framework: StatsForecast
     model_type: local
@@ -105,47 +105,47 @@ models:
       alpha_p: 0.2
 
   StatsForecastADIDA:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcADIDA
     framework: StatsForecast
     model_type: local
     trainable: false
     model_spec:
 
   StatsForecastIMAPA:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcIMAPA
     framework: StatsForecast
     model_type: local
     trainable: false
     model_spec:
 
   StatsForecastCrostonClassic:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcCrostonClassic
     framework: StatsForecast
     model_type: local
     trainable: false
     model_spec:
 
   StatsForecastCrostonOptimized:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcCrostonOptimized
     framework: StatsForecast
     model_type: local
     trainable: false
     model_spec:
 
   StatsForecastCrostonSBA:
-    module: forecasting_sa.models.statsforecast.StatsFcForecastingPipeline
+    module: mmf_sa.models.statsforecast.StatsFcForecastingPipeline
     model_class: StatsFcCrostonSBA
     framework: StatsForecast
     model_type: local
     trainable: false
     model_spec:
 
   RFableArima:
-    module: forecasting_sa.models.r_fable.RFableForecastingPipeline
+    module: mmf_sa.models.r_fable.RFableForecastingPipeline
     model_class: RFableModel
     framework: RFable
     model_type: local
@@ -154,7 +154,7 @@ models:
       season_length:
 
   RFableETS:
-    module: forecasting_sa.models.r_fable.RFableForecastingPipeline
+    module: mmf_sa.models.r_fable.RFableForecastingPipeline
     model_class: RFableModel
     framework: RFable
     model_type: local
@@ -163,7 +163,7 @@ models:
       season_length:
 
   RFableNNETAR:
-    module: forecasting_sa.models.r_fable.RFableForecastingPipeline
+    module: mmf_sa.models.r_fable.RFableForecastingPipeline
     model_class: RFableModel
     framework: RFable
     model_type: local
@@ -172,14 +172,14 @@ models:
       season_length:
 
   RFableEnsemble:
-    module: forecasting_sa.models.r_fable.RFableForecastingPipeline
+    module: mmf_sa.models.r_fable.RFableForecastingPipeline
     model_class: RFableModel
     framework: RFable
     model_type: local
     trainable: false
 
   RDynamicHarmonicRegression:
-    module: forecasting_sa.models.r_fable.RFableForecastingPipeline
+    module: mmf_sa.models.r_fable.RFableForecastingPipeline
     model_class: RFableModel
     framework: RFable
     model_type: local
@@ -188,7 +188,7 @@ models:
       fourier_terms:
 
   SKTimeLgbmDsDt:
-    module: forecasting_sa.models.sktime.SKTimeForecastingPipeline
+    module: mmf_sa.models.sktime.SKTimeForecastingPipeline
     model_class: SKTimeLgbmDsDt
     framework: SKTime
     model_type: local
@@ -200,7 +200,7 @@ models:
       detrend_poly_degree: 2
 
   SKTimeTBats:
-    module: forecasting_sa.models.sktime.SKTimeForecastingPipeline
+    module: mmf_sa.models.sktime.SKTimeForecastingPipeline
     model_class: SKTimeTBats
     framework: SKTime
     model_type: local
@@ -212,7 +212,7 @@ models:
       season_length: 7
 
   NeuralForecastRNN:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcRNN
     framework: NeuralForecast
     model_type: global
@@ -232,7 +232,7 @@ models:
     decoder_layers: 2
 
   NeuralForecastLSTM:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcLSTM
     framework: NeuralForecast
     model_type: global
@@ -251,7 +251,7 @@ models:
     decoder_layers: 2
 
   NeuralForecastNBEATSx:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcNBEATSx
     framework: NeuralForecast
     model_type: global
@@ -267,7 +267,7 @@ models:
     dropout_prob_theta: 0.0
 
   NeuralForecastNHITS:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcNHITS
     framework: NeuralForecast
     model_type: global
@@ -287,7 +287,7 @@ models:
     pooling_mode: MaxPool1d
 
   NeuralForecastAutoRNN:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcAutoRNN
     framework: NeuralForecast
     model_type: global
@@ -302,7 +302,7 @@ models:
     decoder_hidden_size: [ 64, 128, 256, 512 ]
 
   NeuralForecastAutoLSTM:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcAutoLSTM
     framework: NeuralForecast
     model_type: global
@@ -317,7 +317,7 @@ models:
     decoder_hidden_size: [ 64, 128, 256, 512 ]
 
   NeuralForecastAutoNBEATSx:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcAutoNBEATSx
     framework: NeuralForecast
     model_type: global
@@ -330,7 +330,7 @@ models:
     scaler_type: [ "robust", "standard" ]
 
   NeuralForecastAutoNHITS:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcAutoNHITS
     framework: NeuralForecast
     model_type: global
@@ -345,7 +345,7 @@ models:
     scaler_type: [ "robust", "standard" ]
 
   NeuralForecastAutoTiDE:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcAutoTiDE
     framework: NeuralForecast
     model_type: global
@@ -365,7 +365,7 @@ models:
     layernorm: [ True, False ]
 
   NeuralForecastAutoPatchTST:
-    module: forecasting_sa.models.neuralforecast.NeuralForecastPipeline
+    module: mmf_sa.models.neuralforecast.NeuralForecastPipeline
     model_class: NeuralFcAutoPatchTST
     framework: NeuralForecast
     model_type: global

forecasting_sa/models/neuralforecast/NeuralForecastPipeline.py → mmf_sa/models/neuralforecast/NeuralForecastPipeline.py

@@ -2,7 +2,7 @@
 import numpy as np
 from sktime.performance_metrics.forecasting import mean_absolute_percentage_error
 from neuralforecast import NeuralForecast
-from forecasting_sa.models.abstract_model import ForecastingRegressor
+from mmf_sa.models.abstract_model import ForecastingRegressor
 from neuralforecast.auto import (
     RNN,
     LSTM,

forecasting_sa/models/pytorch_forecasting/PyTorchForecastingPipeline.py → mmf_sa/models/pytorch_forecasting/PyTorchForecastingPipeline.py

@@ -2,13 +2,13 @@
 from sklearn.base import BaseEstimator, TransformerMixin
 from sklearn.pipeline import Pipeline
 
-from forecasting_sa.models.abstract_model import ForecastingSARegressor
-from forecasting_sa.models.pytorch_forecasting.PyTorchForecastingModel import (
+from mmf_sa.models.abstract_model import ForecastingRegressor
+from mmf_sa.models.pytorch_forecasting.PyTorchForecastingModel import (
     PyTorchForecastingRegressor,
 )
 
 
-class PyTorchForecastingPipelineRegressor(ForecastingSARegressor):
+class PyTorchForecastingPipelineRegressor(ForecastingRegressor):
     def __init__(self, params):
         super().__init__(params)
         self.params = params