upgrade pyre version in fbcode/torchsnapshot - batch 1

Differential Revision: D60991359

fbshipit-source-id: 99ff5a87c15387c7e7bdc018fd073fff60ab7d40

Author: generatedunixname89002005307016

tests/gpu_tests/test_dtensor_io_preparer.py

@@ -72,7 +72,6 @@ async def test_dtensor_io_preparer(
         """
         Verify the basic behavior of DTensorIOPreparer prepare_write.
         """
-        # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[typing.Any],...
         device_mesh = DeviceMesh("cuda", mesh=mesh)
 
         if len(placements) > device_mesh.ndim:

tests/gpu_tests/test_dtensor_utils.py

@@ -31,7 +31,6 @@ class TestDTensorUtils(DTensorTestBase):
     @skip_if_lt_x_gpu(WORLD_SIZE)
     # pyre-fixme[3]: Return type must be annotated.
     def test_is_sharded_is_replicated(self):
-        # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[typing.Any],...
         mesh = DeviceMesh("cuda", mesh=[[0, 1], [2, 3]])
         placements = [Replicate(), Shard(0)]
         local_tensor = torch.rand((16, 16))

tests/gpu_tests/test_snapshot_dtensor.py

@@ -81,10 +81,6 @@ def _create_model(
             inter_node_pg = mesh_2d.get_group(mesh_dim=0)
             model = FSDP(
                 DummyModel().cuda(),
-                # pyre-fixme[6]: For 2nd argument expected `Union[None,
-                #  Tuple[ProcessGroup, ProcessGroup], ProcessGroup]` but got
-                #  `Tuple[Union[List[ProcessGroup], ProcessGroup],
-                #  Union[List[ProcessGroup], ProcessGroup]]`.
                 process_group=(intra_node_pg, inter_node_pg),
                 sharding_strategy=ShardingStrategy.HYBRID_SHARD,
             )

tests/test_batcher.py

@@ -165,10 +165,8 @@ def dtensor_test_cases(
     dsts = []
     for idx in range(NUM_TENSORS):
         mesh = (
-            # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[typing.A...
             DeviceMesh("cuda", mesh=[0])
             if use_gpu and idx % 2 == 0
-            # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[typing.A...
             else DeviceMesh("cpu", mesh=[0])
         )
         srcs.append(

tests/test_test_utils.py

@@ -123,7 +123,6 @@ def _create_dtensor() -> DTensor:
 
         local_tensor = torch.rand((dim_0, dim_1))
 
-        # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[typing.Any],...
         mesh = DeviceMesh("cpu", mesh=[[0, 1], [2, 3]])
         placements = [Replicate(), Shard(0)]
         dtensor = distribute_tensor(

torchsnapshot/batcher.py

@@ -469,6 +469,7 @@ def batch_read_requests(read_reqs: List[ReadReq]) -> List[ReadReq]:
             path=location,
             buffer_consumer=BatchedBufferConsumer(
                 byte_range_to_buffer_consumer=byte_range_to_buffer_consumer,
+                # pyre-fixme[61]: `byte_range` is undefined, or not always defined.
                 buf_sz_bytes=byte_range[1] - byte_range[0],
             ),
             byte_range=location_to_byte_range[location],

torchsnapshot/snapshot.py

@@ -907,6 +907,7 @@ def _infer_replicated(replicated: List[str], app_state: AppState) -> List[str]:
 
     @staticmethod
     def _coalesce_replicated(global_replicated: List[List[str]]) -> Set[str]:
+        # pyre-fixme[6]: For 1st argument expected `(_T1) -> _S` but got `Type[set]`.
         verified_replicated = set.intersection(*map(set, global_replicated))
         return verified_replicated
 

torchsnapshot/test_utils.py

@@ -317,10 +317,6 @@ def _dtensor_test_case(
     replicated: bool,
 ) -> Tuple[DTensor, Entry, List[WriteReq]]:
     # WORLD_SIZE needs to be at least 4
-    # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[typing.Any],
-    #  _NestedSequence[Union[bool, bytes, complex, float, int, str]],
-    #  _NestedSequence[_SupportsArray[typing.Any]], bool, bytes, complex, float, int,
-    #  str, Tensor]` but got `List[List[int]]`.
     mesh = DeviceMesh("cuda", mesh=[[0, 1], [2, 3]])
     placements = [Replicate(), Shard(0)]
     local_tensor = rand_tensor(shape, dtype=dtype)