autokeras/tasks/time_series_forecaster.py

Survived

Mutant 267

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -38,7 +38,6 @@
         self._target_col_name = None
         self.train_len = 0
 
-    @staticmethod
     def _read_from_csv(x, y):
         df = pd.read_csv(x)
         target = df.pop(y).dropna().to_numpy()

Mutant 268

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -71,7 +71,7 @@
                     validation_data=validation_data,
                     **kwargs)
 
-    def predict(self, x, batch_size=32, **kwargs):
+    def predict(self, x, batch_size=33, **kwargs):
         x = self.read_for_predict(x)
         y_pred = super().predict(x=x,
                                  batch_size=batch_size,

Mutant 269

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -82,7 +82,7 @@
         upper_bound = min(self.train_len + self.predict_until + 1, len(y_pred))
         return y_pred[lower_bound:upper_bound]
 
-    def evaluate(self, x, y=None, batch_size=32, **kwargs):
+    def evaluate(self, x, y=None, batch_size=33, **kwargs):
         """Evaluate the best model for the given data.
 
         # Arguments

Mutant 270

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -241,7 +241,7 @@
                     validation_data=validation_data,
                     **kwargs)
 
-    def predict(self, x=None, batch_size=32, **kwargs):
+    def predict(self, x=None, batch_size=33, **kwargs):
         """Predict the output for a given testing data.
 
         # Arguments

Mutant 271

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -262,7 +262,7 @@
                         y=None,
                         validation_split=0.2,
                         validation_data=None,
-                        batch_size=32,
+                        batch_size=33,
                         **kwargs):
         """Search for the best model and then predict for remaining data points.
 

Mutant 272

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -408,7 +408,7 @@
         """
         raise NotImplementedError
 
-    def predict(self, x=None, batch_size=32, **kwargs):
+    def predict(self, x=None, batch_size=33, **kwargs):
         """Predict the output for a given testing data.
 
         # Arguments

Mutant 273

--- autokeras/tasks/time_series_forecaster.py
+++ autokeras/tasks/time_series_forecaster.py
@@ -431,7 +431,7 @@
                         y=None,
                         validation_split=0.2,
                         validation_data=None,
-                        batch_size=32,
+                        batch_size=33,
                         **kwargs):
         """Search for the best model and then predict for remaining data points.