Remove unused pyre-ignore in TBE tests (pytorch#2162)

Summary:
Pull Request resolved: pytorch#2162

As title

Reviewed By: q10

Differential Revision: D51600941

fbshipit-source-id: 514d6b52cbf2d25c7ed1a87d12390cdd49e5374e

fbgemm_gpu/test/split_table_batched_embeddings_test.py

@@ -4370,14 +4370,9 @@ def execute_nbit_forward_(  # noqa C901
             # Initialize and insert Array index remapping based data structure
             index_remappings_array = []
             for t in range(T):
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 indice_t = (indices.view(T, B, L))[t].long().view(-1).to(current_device)
                 dense_indice_t = (
-                    (dense_indices.view(T, B, L))[t].view(-1)
-                    # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                    #  str]`.
-                    .to(current_device)
+                    (dense_indices.view(T, B, L))[t].view(-1).to(current_device)
                 )
                 index_remappings_array_t = torch.tensor(
                     [-1] * original_E,
@@ -5143,19 +5138,13 @@ def test_pruning(
         index_remappings_array_offsets = torch.empty(
             T + 1,
             dtype=torch.int64,
-            # pyre-fixme[6]: For 3rd param expected `Union[None, str, device]` but
-            #  got `Union[int, str]`.
             device=current_device,
         )
         index_remappings_array_offsets[0] = 0
         for t in range(T):
-            # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int, str]`.
             indice_t = (indices.view(T, B, L))[t].long().view(-1).to(current_device)
             dense_indice_t = (
-                (dense_indices.view(T, B, L))[t].view(-1)
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
-                .to(current_device)
+                (dense_indices.view(T, B, L))[t].view(-1).to(current_device)
             )
             selected_indices = torch.add(indice_t, t * original_E)[:E]
             index_remappings_array[selected_indices] = dense_indice_t
@@ -5174,26 +5163,12 @@ def test_pruning(
                 index_remappings_array,
                 index_remappings_array_offsets,
             ) = (
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 indices.to(current_device),
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 dense_indices.to(current_device),
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 offsets.to(current_device),
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 hash_table.to(current_device),
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 hash_table_offsets.to(current_device),
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 index_remappings_array.to(current_device),
-                # pyre-fixme[6]: For 1st param expected `dtype` but got `Union[int,
-                #  str]`.
                 index_remappings_array_offsets.to(current_device),
             )