[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_fx/test_pipeline/test_topo/test_topo.py

@@ -7,7 +7,7 @@ BATCH_SIZE = 1
 SEQ_LENGHT = 16
 
 
-@pytest.mark.skip('ShapeProp is not compatible with PyTorch 1.11.0')
+@pytest.mark.skip("ShapeProp is not compatible with PyTorch 1.11.0")
 def test_opt():
     MODEL_LIST = [
         MLP,
@@ -15,10 +15,7 @@ def test_opt():
     ]
 
     CONFIGS = [
-        {
-            'dim': 10,
-            'layers': 12
-        },
+        {"dim": 10, "layers": 12},
         transformers.OPTConfig(vocab_size=100, hidden_size=128, num_hidden_layers=4, num_attention_heads=4),
     ]
 
@@ -45,5 +42,5 @@ def test_opt():
         check_topo(top_mod, topo)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     test_opt()

tests/test_fx/test_pipeline/test_topo/topo_utils.py

@@ -6,7 +6,7 @@ from torch.fx import GraphModule
 
 from colossalai.fx import ColoTracer
 from colossalai.fx.passes.adding_split_node_pass import balanced_split_pass, split_with_split_nodes_pass
-from colossalai.legacy.pipeline.middleware import Partition, PartitionInputVal, PartitionOutputVal, Topo
+from colossalai.legacy.pipeline.middleware import Partition, Topo
 from colossalai.legacy.pipeline.middleware.adaptor import get_fx_topology
 
 MANUAL_SEED = 0
@@ -16,11 +16,10 @@ torch.manual_seed(MANUAL_SEED)
 
 
 class MLP(torch.nn.Module):
-
     def __init__(self, config={}):
         super().__init__()
-        dim = config['dim']
-        layers = config['layers']
+        dim = config["dim"]
+        layers = config["layers"]
         self.layers = torch.nn.ModuleList()
 
         for _ in range(layers):
@@ -41,7 +40,7 @@ def split_model_and_get_DAG(model, data_gen):
     # tracing model
     tracer = ColoTracer()
     try:
-        meta_args = {k: v.to('meta') for k, v in kwargs.items()}
+        meta_args = {k: v.to("meta") for k, v in kwargs.items()}
         graph = tracer.trace(root=model, meta_args=meta_args)
     except Exception as e:
         raise RuntimeError(f"Failed to trace {model.__class__.__name__}, error: {e}")
@@ -55,7 +54,7 @@ def split_model_and_get_DAG(model, data_gen):
     topo = get_fx_topology(top_module)
     for submodule in split_submodules:
         if isinstance(submodule, torch.fx.GraphModule):
-            setattr(submodule, '_topo', topo)
+            setattr(submodule, "_topo", topo)
 
     return top_module, split_submodules[0]._topo
 
@@ -64,7 +63,7 @@ def check_input(top_module, input_partition: Partition):
     partition_output = input_partition.get_output_vals()
     arg_pos = 0
     for node in top_module.graph.nodes:
-        if node.op == 'placeholder':
+        if node.op == "placeholder":
             cur_checkee = partition_output[arg_pos]
             to_partition_and_offset = cur_checkee.get()
             assert len(to_partition_and_offset) == len(node.users.keys())
@@ -80,7 +79,7 @@ def check_submod(top_module, part_id, mid_partition: Partition):
     cnt = 1
     cur_node = None
     for node in top_module.graph.nodes:
-        if node.name.startswith('submod'):
+        if node.name.startswith("submod"):
             cnt += 1
         if cnt == part_id:
             cur_node = node