[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

examples/tutorial/sequence_parallel/data/datasets/ict_dataset.py

@@ -2,12 +2,11 @@ import itertools
 import random
 
 import numpy as np
-from torch.utils.data import Dataset
-
-from megatron import get_tokenizer
-from megatron import get_args
+from megatron import get_args, get_tokenizer
 from megatron.data.dataset_utils import get_indexed_dataset_
 from megatron.data.realm_dataset_utils import get_block_samples_mapping
+from torch.utils.data import Dataset
+
 
 def make_attention_mask(source_block, target_block):
     """
@@ -20,16 +19,17 @@ def make_attention_mask(source_block, target_block):
     # (source_length, target_length)
     return mask
 
+
 def get_ict_dataset(use_titles=True, query_in_block_prob=1):
     """Get a dataset which uses block samples mappings to get ICT/block indexing data (via get_block())
     rather than for training, since it is only built with a single epoch sample mapping.
     """
     args = get_args()
-    block_dataset = get_indexed_dataset_(args.data_path, 'mmap', True)
-    titles_dataset = get_indexed_dataset_(args.titles_data_path, 'mmap', True)
+    block_dataset = get_indexed_dataset_(args.data_path, "mmap", True)
+    titles_dataset = get_indexed_dataset_(args.titles_data_path, "mmap", True)
 
     kwargs = dict(
-        name='full',
+        name="full",
         block_dataset=block_dataset,
         title_dataset=titles_dataset,
         data_prefix=args.data_path,
@@ -39,7 +39,7 @@ def get_ict_dataset(use_titles=True, query_in_block_prob=1):
         seed=1,
         query_in_block_prob=query_in_block_prob,
         use_titles=use_titles,
-        use_one_sent_docs=args.use_one_sent_docs
+        use_one_sent_docs=args.use_one_sent_docs,
     )
     dataset = ICTDataset(**kwargs)
     return dataset
@@ -47,9 +47,22 @@ def get_ict_dataset(use_titles=True, query_in_block_prob=1):
 
 class ICTDataset(Dataset):
     """Dataset containing sentences and their blocks for an inverse cloze task."""
-    def __init__(self, name, block_dataset, title_dataset, data_prefix,
-                 num_epochs, max_num_samples, max_seq_length, query_in_block_prob,
-                 seed, use_titles=True, use_one_sent_docs=False, binary_head=False):
+
+    def __init__(
+        self,
+        name,
+        block_dataset,
+        title_dataset,
+        data_prefix,
+        num_epochs,
+        max_num_samples,
+        max_seq_length,
+        query_in_block_prob,
+        seed,
+        use_titles=True,
+        use_one_sent_docs=False,
+        binary_head=False,
+    ):
         self.name = name
         self.seed = seed
         self.max_seq_length = max_seq_length
@@ -61,8 +74,16 @@ class ICTDataset(Dataset):
         self.use_one_sent_docs = use_one_sent_docs
 
         self.samples_mapping = get_block_samples_mapping(
-            block_dataset, title_dataset, data_prefix, num_epochs,
-            max_num_samples, max_seq_length, seed, name, use_one_sent_docs)
+            block_dataset,
+            title_dataset,
+            data_prefix,
+            num_epochs,
+            max_num_samples,
+            max_seq_length,
+            seed,
+            name,
+            use_one_sent_docs,
+        )
         self.tokenizer = get_tokenizer()
         self.vocab_id_list = list(self.tokenizer.inv_vocab.keys())
         self.vocab_id_to_token_list = self.tokenizer.inv_vocab
@@ -99,8 +120,8 @@ class ICTDataset(Dataset):
 
         # still need to truncate because blocks are concluded when
         # the sentence lengths have exceeded max_seq_length.
-        query = query[:self.max_seq_length - 2]
-        block = list(itertools.chain(*block))[:self.max_seq_length - title_pad_offset]
+        query = query[: self.max_seq_length - 2]
+        block = list(itertools.chain(*block))[: self.max_seq_length - title_pad_offset]
 
         query_tokens, query_pad_mask = self.concat_and_pad_tokens(query)
         context_tokens, context_pad_mask = self.concat_and_pad_tokens(block, title)
@@ -111,13 +132,13 @@ class ICTDataset(Dataset):
         block_data = sample_data.as_array()
 
         sample = {
-            'query_tokens': query_tokens,
-            'query_mask': query_mask,
-            'query_pad_mask': query_pad_mask,
-            'context_tokens': context_tokens,
-            'context_mask': context_mask,
-            'context_pad_mask': context_pad_mask,
-            'block_data': block_data,
+            "query_tokens": query_tokens,
+            "query_mask": query_mask,
+            "query_pad_mask": query_pad_mask,
+            "context_tokens": context_tokens,
+            "context_mask": context_mask,
+            "context_pad_mask": context_pad_mask,
+            "block_data": block_data,
         }
 
         return sample
@@ -127,7 +148,7 @@ class ICTDataset(Dataset):
         block = [self.block_dataset[i] for i in range(start_idx, end_idx)]
         title = self.title_dataset[int(doc_idx)]
 
-        block = list(itertools.chain(*block))[:self.max_seq_length - (3 + len(title))]
+        block = list(itertools.chain(*block))[: self.max_seq_length - (3 + len(title))]
         block_tokens, block_pad_mask = self.concat_and_pad_tokens(block, title)
 
         return block_tokens, block_pad_mask