autokeras/tasks/time_series_forecaster.py
Killed 0 out of 7 mutantsSurvived
Survived mutation testing. These mutants show holes in your test suite.Mutant 268
--- 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 269
--- 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 270
--- 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 271
--- 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 272
--- 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 273
--- 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 274
--- 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.