Add type error suppressions for upcoming upgrade (#1340)

Summary: Pull Request resolved: #1340

Reviewed By: MaggieMoss

Differential Revision: D62387756

tests/attr/test_llm_attr.py

@@ -156,7 +156,9 @@ def device(self) -> torch.device:
 # pyre-fixme[13]: Attribute `device` is never initialized.
 # pyre-fixme[13]: Attribute `use_cached_outputs` is never initialized.
 class TestLLMAttr(BaseTest):
+    # pyre-fixme[13]: Attribute `device` is never initialized.
     device: str
+    # pyre-fixme[13]: Attribute `use_cached_outputs` is never initialized.
     use_cached_outputs: bool
 
     # pyre-fixme[56]: Pyre was not able to infer the type of argument `comprehension
@@ -377,6 +379,7 @@ def test_futures_not_implemented(self) -> None:
 )
 # pyre-fixme[13]: Attribute `device` is never initialized.
 class TestLLMGradAttr(BaseTest):
+    # pyre-fixme[13]: Attribute `device` is never initialized.
     device: str
 
     @parameterized.expand(

tests/attr/test_llm_attr_gpu.py

@@ -149,7 +149,9 @@ def device(self) -> torch._C.device:
 # pyre-fixme[13]: Attribute `use_cached_outputs` is declared in class `TestLlmAttrGpu`
 # to have type `bool` but is never initialized.
 class TestLlmAttrGpu(BaseTest):
+    # pyre-fixme[13]: Attribute `device` is never initialized.
     device: str
+    # pyre-fixme[13]: Attribute `use_cached_outputs` is never initialized.
     use_cached_outputs: bool
 
     @parameterized.expand([(FeatureAblation,), (ShapleyValueSampling,)])
@@ -235,6 +237,7 @@ def test_llm_attr_without_token_gpu(
 # pyre-fixme[13]: Attribute `device` is declared in class `TestLLMGradAttrGPU`
 # to have type `str` but is never initialized.
 class TestLLMGradAttrGPU(BaseTest):
+    # pyre-fixme[13]: Attribute `device` is never initialized.
     device: str
 
     def test_llm_attr(self) -> None:

tests/helpers/basic_models.py

@@ -148,6 +148,7 @@ def __init__(self) -> None:
     # pyre-fixme[2]: Parameter must be annotated.
     def forward(self, input1, input2):
         input = input1 + input2
+        # pyre-fixme[6]: For 1st argument expected `Tensor` but got `int`.
         return 1 - F.relu(1 - input)[:, 1]