remove pd->np and metrics from non neg tests

evalml/objectives/standard_metrics.py

@@ -843,12 +843,7 @@ def objective_function(self, y_true, y_predicted, X=None, sample_weight=None):
                 "Mean Absolute Scaled Error cannot be used when "
                 "all training targets contain the value 0.",
             )
-        if isinstance(y_true, pd.Series):
-            y_true = y_true.to_numpy()
-        if isinstance(y_predicted, pd.Series):
-            y_predicted = y_predicted.to_numpy()
-        if isinstance(y_train, pd.Series):
-            y_train = y_train.to_numpy()
+
         mase = MeanAbsoluteScaledError()
         return mase(y_true, y_predicted, y_train=y_train)
 
@@ -911,11 +906,6 @@ def objective_function(self, y_true, y_predicted, X=None, sample_weight=None):
                 "Symmetric Mean Absolute Percentage Error cannot be used when "
                 "true and predicted targets both contain the value 0.",
             )
-        if isinstance(y_true, pd.Series):
-            y_true = y_true.to_numpy()
-        if isinstance(y_predicted, pd.Series):
-            y_predicted = y_predicted.to_numpy()
-
         smape = MeanAbsolutePercentageError(symmetric=True)
         return smape(y_true, y_predicted) * 100
 

evalml/tests/data_checks_tests/test_invalid_target_data_check.py

@@ -16,9 +16,6 @@
 )
 from evalml.exceptions import DataCheckInitError
 from evalml.objectives import (
-    MAPE,
-    MASE,
-    SMAPE,
     MeanSquaredLogError,
     RootMeanSquaredLogError,
 )
@@ -348,7 +345,6 @@ def test_invalid_target_data_check_n_unique(problem_type):
     [
         "Root Mean Squared Log Error",
         "Mean Squared Log Error",
-        "Mean Absolute Percentage Error",
     ],
 )
 def test_invalid_target_data_check_invalid_labels_for_nonnegative_objective_names(
@@ -403,7 +399,7 @@ def test_invalid_target_data_check_invalid_labels_for_nonnegative_objective_name
 
 @pytest.mark.parametrize(
     "objective",
-    [RootMeanSquaredLogError(), MeanSquaredLogError(), MASE(), MAPE(), SMAPE()],
+    [RootMeanSquaredLogError(), MeanSquaredLogError()],
 )
 def test_invalid_target_data_check_invalid_labels_for_nonnegative_objective_instances(
     objective,
@@ -471,7 +467,6 @@ def test_invalid_target_data_check_invalid_labels_for_objectives(
     [
         "Root Mean Squared Log Error",
         "Mean Squared Log Error",
-        "Mean Absolute Percentage Error",
     ],
 )
 def test_invalid_target_data_check_valid_labels_for_nonnegative_objectives(objective):