fix tests movie model, the lime output is now slightly different as well

tests/methods/test_lime_text.py

@@ -31,11 +31,11 @@ def test_lime_text(self):
     def test_lime_text_special_chars(self):
         """Tests exact expected output given a text with special characters and model for Lime."""
         review = 'such a bad movie "!?\'"'
-        expected_words = ['bad', '?', '!', 'movie', 'such', 'a', "'", '"', '"']
-        expected_word_indices = [2, 6, 5, 3, 0, 1, 7, 4, 8]
+        expected_words = ['bad', 'movie', '?', 'such', '!', "'", '"', 'a', '"']
+        expected_word_indices = [2, 3, 6, 0, 5, 7, 8, 1, 4]
         expected_scores = [
-            0.50032869, 0.06458735, -0.05793979, 0.01413776, -0.01246357,
-            -0.00528022, 0.00305347, 0.00185159, -0.00165128
+            0.51140699, 0.02827488, 0.02657974, -0.02208464, -0.02140743,
+            0.00962419, 0.00746798, -0.00743376, -0.0012061
         ]
 
         explanation = dianna.explain_text(self.runner,
@@ -44,7 +44,7 @@ def test_lime_text_special_chars(self):
                                           labels=[0],
                                           method='LIME',
                                           random_state=42)[0]
-
+        print(explanation)
         assert_explanation_satisfies_expectations(explanation, expected_scores,
                                                   expected_word_indices,
                                                   expected_words)

tests/utils.py

@@ -1,4 +1,5 @@
 import numpy as np
+import onnxruntime as ort
 import spacy
 from scipy.special import expit as sigmoid
 from torchtext.vocab import Vectors
@@ -84,6 +85,10 @@ def __call__(self, sentences):
         if isinstance(sentences, str):
             sentences = [sentences]
 
+        sess = ort.InferenceSession(self.filename)
+        input_name = sess.get_inputs()[0].name
+        output_name = sess.get_outputs()[0].name
+
         output = []
         for sentence in sentences:
             # tokenize and pad to minimum length
@@ -99,7 +104,9 @@ def __call__(self, sentences):
             ]
 
             # run the model, applying a sigmoid because the model outputs logits, remove any remaining batch axis
-            pred = float(sigmoid(self.run_model([tokens_numerical])))
+            onnx_input = {input_name: [tokens_numerical]}
+            logits = sess.run([output_name], onnx_input)[0]
+            pred = float(sigmoid(logits))
             output.append(pred)
 
         # output two classes