B908 update multi-line asserts in Captum tests (#1655)

Summary:
Pull Request resolved: #1655

See https://fburl.com/quality/qyxh69d0

Reviewed By: craymichael

Differential Revision: D85301839

fbshipit-source-id: 54c5a612260f0f6db23c301558c5f03b0d3d9bee

Author: sarahtranfb

tests/attr/test_approximation_methods.py

@@ -15,9 +15,10 @@ def __init__(self, methodName: str = "runTest") -> None:
         super().__init__(methodName)
 
     def test_riemann_0(self) -> None:
+        step_sizes, alphas = riemann_builders()
         with self.assertRaises(AssertionError):
-            step_sizes, alphas = riemann_builders()
             step_sizes(0)
+        with self.assertRaises(AssertionError):
             alphas(0)
 
     def test_riemann_2(self) -> None:

tests/attr/test_llm_attr.py

@@ -904,16 +904,16 @@ def test_get_logprobs_successful(self) -> None:
 
     def test_get_logprobs_missing_tokenizer(self) -> None:
         """Test get_logprobs with missing tokenizer."""
+        provider = VLLMProvider(api_url=self.api_url, model_name=self.model_name)
         with self.assertRaises(ValueError) as context:
-            provider = VLLMProvider(api_url=self.api_url, model_name=self.model_name)
             provider.get_logprobs(self.input_prompt, self.target_str, None)
 
         self.assertIn("Tokenizer is required", str(context.exception))
 
     def test_get_logprobs_empty_target(self) -> None:
         """Test get_logprobs with empty target string."""
+        provider = VLLMProvider(api_url=self.api_url, model_name=self.model_name)
         with self.assertRaises(ValueError) as context:
-            provider = VLLMProvider(api_url=self.api_url, model_name=self.model_name)
             provider.get_logprobs(self.input_prompt, "", self.tokenizer)
 
         self.assertIn("Target string cannot be empty", str(context.exception))

tests/attr/test_targets.py

@@ -220,15 +220,15 @@ class TestTargets(BaseTest, metaclass=TargetsMeta):
     def test_simple_target_missing_error(self) -> None:
         net = BasicModel_MultiLayer()
         inp = torch.zeros((1, 3))
+        attr = IntegratedGradients(net)
         with self.assertRaises(AssertionError):
-            attr = IntegratedGradients(net)
             attr.attribute(inp)  # type: ignore[has-type]
 
     def test_multi_target_error(self) -> None:
         net = BasicModel_MultiLayer()
         inp = torch.zeros((1, 3))
+        attr = IntegratedGradients(net)
         with self.assertRaises(AssertionError):
-            attr = IntegratedGradients(net)
             attr.attribute(  # type: ignore[has-type]
                 inp, additional_forward_args=(None, True), target=(1, 0)
             )