Merge pull request cgpotts#74 from TianHuaBooks/featurize_func

Add parameter featurize_func

nli.py

@@ -34,7 +34,9 @@ def wordentail_experiment(
         assess_data,
         vector_func,
         vector_combo_func,
-        model):
+        model,
+        featurize_func=word_entail_featurize,
+):
     """Train and evaluation code for the word-level entailment task.
 
     Parameters
@@ -48,6 +50,7 @@ def wordentail_experiment(
         Any function for combining two vectors into a new vector
         of fixed dimensionality.
     model : class with `fit` and `predict` methods
+    featurize_func : function to return feature (X,y) with intended tensor
 
     Prints
     ------
@@ -69,9 +72,9 @@ def wordentail_experiment(
     between these experiments and the bake-off evaluation.
 
     """
-    X_train, y_train = word_entail_featurize(
+    X_train, y_train = featurize_func(
         train_data,  vector_func, vector_combo_func)
-    X_dev, y_dev = word_entail_featurize(
+    X_dev, y_dev = featurize_func(
         assess_data, vector_func, vector_combo_func)
     model.fit(X_train, y_train)
     predictions = model.predict(X_dev)
@@ -87,7 +90,7 @@ def wordentail_experiment(
         'vector_combo_func': vector_combo_func}
 
 
-def bake_off_evaluation(experiment_results, test_data_filename=None):
+def bake_off_evaluation(experiment_results, test_data_filename=None, featurize_func=word_entail_featurize):
     """Function for evaluating a trained model on the bake-off test set.
 
     Parameters
@@ -98,6 +101,7 @@ def bake_off_evaluation(experiment_results, test_data_filename=None):
     test_data_filename : str or None
         Full path to the test data. If `None`, then we assume the file is
         'data/nlidata/nli_wordentail_bakeoff_data-test.json'.
+    featurize_func : function to return feature (X,y) with intended tensor
 
     Prints
     ------
@@ -110,7 +114,7 @@ def bake_off_evaluation(experiment_results, test_data_filename=None):
             'data', 'nlidata', 'nli_wordentail_bakeoff_data-test.json')
     with open(test_data_filename, encoding='utf8') as f:
         wordentail_data = json.load(f)
-    X_test, y_test = word_entail_featurize(
+    X_test, y_test = featurize_func(
         wordentail_data['test'],
         vector_func=experiment_results['vector_func'],
         vector_combo_func=experiment_results['vector_combo_func'])