refactor: build_model -> build rename

godatadriven · Jan 5, 2021 · 2461bd1 · 2461bd1
1 parent 31544b1
commit 2461bd1
Show file tree

Hide file tree

Showing 4 changed files with 9 additions and 10 deletions.
diff --git a/README.md b/README.md
@@ -53,10 +53,9 @@ model = PivenMlpModel(
         lr=0.0001,
 )
 # Normalize input data
-model.build_model(preprocess=StandardScaler())
+model.build(preprocess=StandardScaler())
 # You can pass any arguments that you would also pass to a keras model
 model.fit(x_train, y_train, model__epochs=200, model__validation_split=.2)
-model.score()
 ```
 
 You can score the model by calling the `score()` method:

diff --git a/src/piven/models/base.py b/src/piven/models/base.py
@@ -104,7 +104,7 @@ def load_model_from_disk(build_fn: Callable, path: str):
         return load_piven_model(build_fn, path)
 
     @abc.abstractmethod
-    def build_model(self, **build_params):
+    def build(self, **build_params):
         pass
 
     @classmethod

diff --git a/src/piven/models/mlp_regressor.py b/src/piven/models/mlp_regressor.py
@@ -71,7 +71,7 @@ def piven_model(
 
 
 class PivenMlpModel(PivenBaseModel):
-    def build_model(self, preprocess: Union[None, Pipeline, TransformerMixin] = None):
+    def build(self, preprocess: Union[None, Pipeline, TransformerMixin] = None):
         # All build params are passed to init and should be checked here
         check_model_params(**self.params)
         model = PivenKerasRegressor(build_fn=piven_model, **self.params)

diff --git a/tests/test_mlp_model.py b/tests/test_mlp_model.py
@@ -53,11 +53,11 @@ def sklearn_preprocessing_pipeline():
 
 class TestPivenMlpExperiment:
     def test_experiment_build_model(self, experiment):
-        experiment.build_model()
+        experiment.build()
 
     def test_experiment_fit_model_no_preprocess(self, mock_data, experiment):
         x_train, x_valid, y_train, y_valid = mock_data
-        experiment.build_model()
+        experiment.build()
         experiment.fit(
             x_train,
             y_train,
@@ -83,7 +83,7 @@ def test_experiment_fit_model_with_preprocess(
             bias_init_high=3.0,
             lr=0.0001,
         )
-        experiment.build_model(preprocess=sklearn_preprocessing_pipeline)
+        experiment.build(preprocess=sklearn_preprocessing_pipeline)
         experiment.fit(
             x,
             y,
@@ -94,7 +94,7 @@ def test_experiment_fit_model_with_preprocess(
 
     def test_experiment_io(self, mock_data, experiment):
         x_train, x_valid, y_train, y_valid = mock_data
-        experiment.build_model()
+        experiment.build()
         experiment.fit(
             x_train,
             y_train,
@@ -108,7 +108,7 @@ def test_experiment_io(self, mock_data, experiment):
 
     def test_experiment_scoring(self, mock_data, experiment):
         x_train, x_valid, y_train, y_valid = mock_data
-        experiment.build_model()
+        experiment.build()
         experiment.fit(x_train, y_train, model__epochs=3)
         y_pred, y_pi_low, y_pi_high = experiment.predict(
             x_valid, return_prediction_intervals=True
@@ -124,7 +124,7 @@ def test_experiment_scoring(self, mock_data, experiment):
 
     def test_experiment_logging(self, mock_data, experiment):
         x_train, x_valid, y_train, y_valid = mock_data
-        experiment.build_model()
+        experiment.build()
         experiment.fit(x_train, y_train, model__epochs=3)
         with tempfile.TemporaryDirectory() as tmpdir:
             experiment.log(x_valid, y_valid, tmpdir, model=True, predictions=True)