Test fixes

tests/rc/models/bidaf_test.py

@@ -20,8 +20,15 @@ class BidirectionalAttentionFlowTest(ModelTestCase):
  def setup_method(self):
  super().setup_method()
  self.set_up_model(
- FIXTURES_ROOT / "rc" / "bidaf" / "experiment.json", FIXTURES_ROOT / "rc" / "squad.json"
+ FIXTURES_ROOT / "rc" / "bidaf" / "experiment.json",
+ FIXTURES_ROOT / "rc" / "squad.json",
+ seed=27,
  )
+ torch.use_deterministic_algorithms(True)
+
+ def teardown_method(self):
+ super().teardown_method()
+ torch.use_deterministic_algorithms(False)
 
  @flaky
  def test_forward_pass_runs_correctly(self):
@@ -53,7 +60,11 @@ def test_forward_pass_runs_correctly(self):
  # `masked_softmax`...) have made this _very_ flaky...
  @flaky(max_runs=5)
  def test_model_can_train_save_and_load(self):
- self.ensure_model_can_train_save_and_load(self.param_file, tolerance=1e-4)
+ self.ensure_model_can_train_save_and_load(
+ self.param_file,
+ tolerance=1e-4,
+ gradients_to_ignore={"_span_start_predictor._module.bias"},
+ )
 
  @flaky
  def test_batch_predictions_are_consistent(self):

tests/rc/models/dialog_qa_test.py

@@ -1,9 +1,9 @@
 from allennlp.common.testing import ModelTestCase
 from allennlp.data import Batch
-
-from tests import FIXTURES_ROOT
+import torch
 
 import allennlp_models.rc
+from tests import FIXTURES_ROOT
 
 
 class DialogQATest(ModelTestCase):
@@ -12,9 +12,15 @@ def setup_method(self):
  self.set_up_model(
  FIXTURES_ROOT / "rc" / "dialog_qa" / "experiment.json",
  FIXTURES_ROOT / "rc" / "dialog_qa" / "quac_sample.json",
+ seed=42,
  )
  self.batch = Batch(self.instances)
  self.batch.index_instances(self.vocab)
+ torch.use_deterministic_algorithms(True)
+
+ def teardown_method(self):
+ super().teardown_method()
+ torch.use_deterministic_algorithms(False)
 
  def test_forward_pass_runs_correctly(self):
  training_tensors = self.batch.as_tensor_dict()
@@ -23,7 +29,9 @@ def test_forward_pass_runs_correctly(self):
  assert "followup" in output_dict and "yesno" in output_dict
 
  def test_model_can_train_save_and_load(self):
- self.ensure_model_can_train_save_and_load(self.param_file, tolerance=1e-4)
+ self.ensure_model_can_train_save_and_load(
+ self.param_file, tolerance=1e-4, gradients_to_ignore={"_matrix_attention._bias"}
+ )
 
  def test_batch_predictions_are_consistent(self):
  self.ensure_batch_predictions_are_consistent()