update for new AllenNlpTestCase

requirements.txt

@@ -1,4 +1,4 @@
-git+https://github.com/allenai/allennlp.git@master
+git+https://github.com/epwalsh/allennlp.git@test-case
 
 # For RC models
 word2number>=1.1

setup.py

@@ -31,7 +31,7 @@ def requirement_is_allennlp(req: str) -> bool:
             return True
         if re.match(r"^allennlp[>=<]", req):
             return True
-        if re.match(r"^(git\+)?(https|ssh)://(git@)?github\.com/allenai/allennlp\.git", req):
+        if re.match(r"^(git\+)?(https|ssh)://(git@)?github\.com/.*/allennlp\.git", req):
             return True
         return False
 

tests/coref/coref_model_test.py

@@ -6,8 +6,8 @@
 
 
 class CorefTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "coref" / "experiment.json",
             FIXTURES_ROOT / "coref" / "coref.gold_conll",
@@ -31,7 +31,7 @@ def _test_coref_model_can_train_save_and_load(
         # fmt: on
         self.ensure_model_can_train_save_and_load(self.param_file, overrides=overrides)
         self.tearDown()
-        self.setUp()
+        self.setup_method()
 
     def test_coref_bert_model_can_train_save_and_load(self):
         self.set_up_model(

tests/lm/bidirectional_lm_test.py

@@ -6,8 +6,8 @@
 
 
 class TestBidirectionalLanguageModel(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
 
         self.expected_embedding_shape = (2, 8, 14)
 
@@ -47,8 +47,8 @@ def test_forward_pass_runs_correctly(self):
 
 
 class TestBidirectionalLanguageModelUnsampled(TestBidirectionalLanguageModel):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "lm" / "language_model" / "experiment_bidirectional_unsampled.jsonnet",
             FIXTURES_ROOT / "lm" / "language_model" / "sentences.txt",

tests/lm/bidirectional_lm_token_embedder_test.py

@@ -3,8 +3,8 @@
 
 
 class TestBidirectionalLanguageModelTokenEmbedder(TestLanguageModelTokenEmbedder):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT
             / "lm"
@@ -15,8 +15,8 @@ def setUp(self):
 
 
 class TestBidirectionalLanguageModelTokenEmbedderWithoutBosEos(TestLanguageModelTokenEmbedder):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT
             / "lm"

tests/lm/composed_seq2seq_test.py

@@ -6,8 +6,8 @@
 
 
 class ComposedSeq2SeqTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "seq2seq" / "composed" / "experiment.json",
             FIXTURES_ROOT / "seq2seq" / "seq2seq_copy.tsv",

tests/lm/copynet_seq2seq_test.py

@@ -8,8 +8,8 @@
 
 
 class CopyNetTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "seq2seq" / "copynet" / "experiment.json",
             FIXTURES_ROOT / "seq2seq" / "copynet" / "data" / "copyover.tsv",

tests/lm/language_model_test.py

@@ -10,8 +10,8 @@
 
 
 class TestUnidirectionalLanguageModel(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
 
         self.expected_embedding_shape = (2, 8, 7)
         self.bidirectional = False
@@ -70,17 +70,17 @@ def test_language_model_forward_on_instances(self):
 
 
 class TestUnidirectionalLanguageModelUnsampled(TestUnidirectionalLanguageModel):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "lm" / "language_model" / "experiment_unidirectional_unsampled.jsonnet",
             FIXTURES_ROOT / "lm" / "language_model" / "sentences.txt",
         )
 
 
 class TestUnidirectionalLanguageModelTransformer(TestUnidirectionalLanguageModel):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
 
         self.expected_embedding_shape = (2, 8, 16)
 
@@ -105,8 +105,8 @@ def test_unidirectional_language_model_can_train_save_and_load(self):
 
 
 class TestBidirectionalLanguageModel(TestUnidirectionalLanguageModel):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
 
         self.expected_embedding_shape = (2, 8, 14)
         self.bidirectional = True
@@ -119,17 +119,17 @@ def setUp(self):
 
 
 class TestBidirectionalLanguageModelUnsampled(TestBidirectionalLanguageModel):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "lm" / "language_model" / "experiment_unsampled.jsonnet",
             FIXTURES_ROOT / "lm" / "language_model" / "sentences.txt",
         )
 
 
 class TestBidirectionalLanguageModelTransformer(TestBidirectionalLanguageModel):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
 
         self.expected_embedding_shape = (2, 8, 32)
 

tests/lm/language_model_token_embedder_test.py

@@ -5,8 +5,8 @@
 
 
 class TestLanguageModelTokenEmbedder(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "lm" / "language_model" / "characters_token_embedder.json",
             FIXTURES_ROOT / "lm" / "conll2003.txt",
@@ -31,8 +31,8 @@ def test_tagger_with_language_model_token_embedder_forward_pass_runs_correctly(s
 
 
 class TestLanguageModelTokenEmbedderWithoutBosEos(TestLanguageModelTokenEmbedder):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT
             / "lm"

tests/lm/masked_language_model_test.py

@@ -5,8 +5,8 @@
 
 
 class TestMaskedLanguageModel(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "lm" / "masked_language_model" / "experiment.json",
             FIXTURES_ROOT / "lm" / "language_model" / "sentences.txt",

tests/lm/next_token_lm_test.py

@@ -5,8 +5,8 @@
 
 
 class TestNextTokenLanguageModel(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "lm" / "next_token_lm" / "experiment.json",
             FIXTURES_ROOT / "lm" / "language_model" / "sentences.txt",

tests/lm/simple_language_modeling_reader_test.py

@@ -16,7 +16,7 @@ def test_text_to_instance(self):
 
         instance = dataset.text_to_instance("The only sentence.")
         text = [t.text for t in cast(TextField, instance.fields["source"]).tokens]
-        self.assertEqual(text, ["<S>", "The", "only", "sentence", ".", "</S>"])
+        assert text == ["<S>", "The", "only", "sentence", ".", "</S>"]
 
     def test_read_single_sentence(self):
         prefix = os.path.join(self.FIXTURES, "single_sentence.txt")
@@ -27,19 +27,17 @@ def test_read_single_sentence(self):
         batch = None
         for batch in dataset.read(prefix):
             break
-        self.assertEqual(
-            sorted(list(expected_batch.fields.keys())), sorted(list(batch.fields.keys()))
-        )
+        assert sorted(list(expected_batch.fields.keys())) == sorted(list(batch.fields.keys()))
         for k in expected_batch.fields.keys():
-            self.assertTrue(str(expected_batch.fields[k]) == str(batch.fields[k]))
+            assert str(expected_batch.fields[k]) == str(batch.fields[k])
 
     def test_read_multiple_sentences(self):
         prefix = os.path.join(self.FIXTURES, "shards/shard0")
         dataset = SimpleLanguageModelingDatasetReader()
         k = -1
         for k, _ in enumerate(dataset.read(prefix)):
             pass
-        self.assertEqual(k, 99)
+        assert k == 99
 
     def test_max_sequence_length(self):
         prefix = os.path.join(self.FIXTURES, "shards/shard0")
@@ -49,4 +47,4 @@ def test_max_sequence_length(self):
         k = -1
         for k, _ in enumerate(dataset.read(prefix)):
             pass
-        self.assertEqual(k, 7)
+        assert k == 7

tests/lm/simple_seq2seq_test.py

@@ -11,8 +11,8 @@
 
 
 class SimpleSeq2SeqTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "seq2seq" / "simple" / "experiment.json",
             FIXTURES_ROOT / "seq2seq" / "seq2seq_copy.tsv",

tests/ner/ccgbank_reader_test.py

@@ -135,7 +135,10 @@ def test_vocab_from_instances_namespaces(self):
         instances = ensure_list(reader.read(FIXTURES_ROOT / "ner" / "ccgbank.txt"))
         # check that we didn't clobber the labels namespace
         vocab = Vocabulary.from_instances(instances)
-        self.assertSetEqual(
-            set(vocab._token_to_index.keys()),
-            {"tokens", "labels", "modified_pos_tags", "original_pos_tags", "predicate_arg_tags"},
-        )
+        assert set(vocab._token_to_index.keys()) == {
+            "tokens",
+            "labels",
+            "modified_pos_tags",
+            "original_pos_tags",
+            "predicate_arg_tags",
+        }

tests/ner/crf_tagger_test.py

@@ -10,8 +10,8 @@
 
 
 class CrfTaggerTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "ner" / "crf_tagger" / "experiment.json",
             FIXTURES_ROOT / "ner" / "conll2003.txt",

tests/nli/bimpm_model_test.py

@@ -4,8 +4,8 @@
 
 
 class TestBiMPM(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "nli" / "bimpm" / "experiment.json",
             FIXTURES_ROOT / "nli" / "quora_paraphrase.tsv",

tests/nli/decomposable_attention_model_test.py

@@ -13,8 +13,8 @@
 
 
 class TestDecomposableAttention(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "nli" / "decomposable_attention" / "experiment.json",
             FIXTURES_ROOT / "nli" / "snli.jsonl",

tests/nli/esim_model_test.py

@@ -7,8 +7,8 @@
 
 
 class TestESIM(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "nli" / "esim" / "experiment.json",
             FIXTURES_ROOT / "nli" / "snli.jsonl",

tests/rc/bidaf/bidaf_ensemble_test.py

@@ -11,8 +11,8 @@
 
 
 class BidafEnsembleTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "rc" / "bidaf" / "experiment.json", FIXTURES_ROOT / "rc" / "squad.json"
         )

tests/rc/bidaf/bidaf_test.py

@@ -16,8 +16,8 @@
 
 
 class BidirectionalAttentionFlowTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "rc" / "bidaf" / "experiment.json", FIXTURES_ROOT / "rc" / "squad.json"
         )

tests/rc/dialog_qa/dialog_qa_model_test.py

@@ -7,8 +7,8 @@
 
 
 class DialogQATest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "rc" / "dialog_qa" / "experiment.json",
             FIXTURES_ROOT / "rc" / "dialog_qa" / "quac_sample.json",

tests/rc/qanet/naqanet_model_test.py

@@ -8,8 +8,8 @@
 
 
 class NumericallyAugmentedQaNetTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "rc" / "naqanet" / "experiment.json", FIXTURES_ROOT / "rc" / "drop.json"
         )

tests/rc/qanet/qanet_model_test.py

@@ -16,8 +16,8 @@
 
 
 class QaNetTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "rc" / "qanet" / "experiment.json", FIXTURES_ROOT / "rc" / "squad.json"
         )

tests/rc/transformer_qa/transformer_qa_model_test.py

@@ -9,8 +9,8 @@
 
 
 class TransformerQaTest(ModelTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.set_up_model(
             FIXTURES_ROOT / "rc" / "transformer_qa" / "experiment.jsonnet",
             FIXTURES_ROOT / "rc" / "squad.json",

tests/rc/transformer_qa/transformer_qa_predictor_test.py

@@ -7,8 +7,8 @@
 
 
 class TestTransformerQAPredictor(AllenNlpTestCase):
-    def setUp(self):
-        super().setUp()
+    def setup_method(self):
+        super().setup_method()
         self.reader = TransformerSquadReader(length_limit=50, stride=10)
         self.vocab = Vocabulary()
         self.model = TransformerQA(self.vocab)