[misc] update pre-commit and run all files (#4752)

* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format

tests/test_legacy/test_utils/test_activation_checkpointing.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python
 # -*- encoding: utf-8 -*-
 
-import pytest
 import torch
 import torch.nn.functional as F
 
@@ -44,20 +43,19 @@ def forward_inplace(x, weight):
 @parameterize("use_reentrant", [True, False])
 @parameterize("cpu_offload", [True, False])
 def test_activation_checkpointing(cpu_offload, use_reentrant):
-
     # as seed manager is singleton
     # if we don't reset seeds here,
     # other tests might affect this test
     reset_seeds()
 
     # We put initialization here to avoid change cuda rng state below
-    inputs = torch.rand(2, 2, requires_grad=True, device='cuda')
-    weight = torch.rand(2, 4, requires_grad=True, device='cuda')
+    inputs = torch.rand(2, 2, requires_grad=True, device="cuda")
+    weight = torch.rand(2, 4, requires_grad=True, device="cuda")
 
     # Get a copy of input tensors
-    inputs_ = torch.empty(2, 2, requires_grad=True, device='cuda')
+    inputs_ = torch.empty(2, 2, requires_grad=True, device="cuda")
     inputs_.data.copy_(inputs.data)
-    weight_ = torch.empty(2, 4, requires_grad=True, device='cuda')
+    weight_ = torch.empty(2, 4, requires_grad=True, device="cuda")
     weight_.data.copy_(weight.data)
 
     add_seed(ParallelMode.GLOBAL, 1024)
@@ -83,7 +81,7 @@ def test_activation_checkpointing(cpu_offload, use_reentrant):
     loss = out.sum()
     loss.backward()
 
-    assert torch.all(inputs.grad == inputs_.grad), 'Gradient of the input does not match'
+    assert torch.all(inputs.grad == inputs_.grad), "Gradient of the input does not match"
     torch.cuda.empty_cache()
 
     # Extra test for use_reentrant=False
@@ -110,7 +108,7 @@ def test_activation_checkpointing(cpu_offload, use_reentrant):
         loss = out.sum()
         loss.backward()
 
-        assert torch.all(inputs.grad == inputs_.grad), 'Gradient of the input does not match'
+        assert torch.all(inputs.grad == inputs_.grad), "Gradient of the input does not match"
         torch.cuda.empty_cache()
 
     # as seed manager is singleton