Nuke concat option.

streaming/text/c4.py

@@ -7,7 +7,7 @@
 the `Common Crawl <https://commoncrawl.org>`_ dataset.
 """
 
-from typing import Any, Dict, Iterator, Optional
+from typing import Any, Dict, Optional
 
 from transformers.models.auto.tokenization_auto import AutoTokenizer
 
@@ -64,9 +64,8 @@ def __init__(self,
                  shuffle_seed: int = 9176,
                  num_canonical_nodes: Optional[int] = None,
                  batch_size: Optional[int] = None):
-        if group_method not in {'truncate', 'concat'}:
-            raise ValueError(
-                f"group_method='{group_method}' must be one of ['truncate', 'concat'].")
+        if group_method not in {'truncate'}:
+            raise ValueError(f"group_method='{group_method}' must be one of {'truncate'}.")
 
         super().__init__(local, remote, split, shuffle, predownload, keep_zip, download_retry,
                          download_timeout, validate_hash, shuffle_seed, num_canonical_nodes,
@@ -80,8 +79,6 @@ def __init__(self,
         if self.tokenizer.pad_token is None:
             # Some tokenizers (e.g. GPT2 tokenizer) have no padding token which causes bugs
             self.tokenizer.pad_token = self.tokenizer.eos_token
-        # suppress warnings when using group_method='concat' and no truncation
-        self.tokenizer.model_max_length = int(1e30)
 
     def _tokenize(self, text_sample: Dict[str, Any]):
         """Apply the tokenizer to a sample.
@@ -93,10 +90,6 @@ def _tokenize(self, text_sample: Dict[str, Any]):
             truncation = True
             padding = 'max_length'
             max_length = self.max_seq_len
-        elif self.group_method == 'concat':
-            truncation = False
-            padding = False
-            max_length = None
         else:
             raise ValueError(f'Got unknown group_method={self.group_method}.')
         return self.tokenizer(text_sample['text'],
@@ -117,49 +110,3 @@ def __getitem__(self, idx: int) -> Any:
         token_sample = self._tokenize(text_sample)
         # Skip any token grouping, currently only supporting group_method='truncate'
         return token_sample
-
-    def __iter__(self) -> Iterator[Any]:
-        """Iterable over samples.
-
-        Since concatenating samples has a custom behavior, it requires extending the
-        parent iterator class.
-
-        For `group_method = truncate`, simply return the token sample.
-        For `group_method = concat`, keep fetching token samples until it fills up the max_seq_len.
-
-        Yields:
-            Iterator[Any]: Sample iterator
-        """
-        if self.group_method == 'truncate':
-            yield from super().__iter__()
-        elif self.group_method == 'concat':
-            buffer = {}
-            while True:
-                iterator = super().__iter__()
-                for sample in iterator:
-                    for k, v in sample.items():
-                        buffer[k] = buffer.get(k, []) + v
-                    while len(buffer['input_ids']) >= self.max_seq_len:
-                        concat_sample = {}
-                        for k, v in buffer.items():
-                            concat_sample[k] = v[:self.max_seq_len]
-                            buffer[k] = v[self.max_seq_len:]
-                        yield concat_sample
-        else:
-            raise ValueError(f'Got unknown group_method={self.group_method}.')
-
-    def __len__(self) -> Optional[int]:
-        """Number of samples in a dataset.
-
-        For `group_method = truncate`, return the number of samples.
-        For `group_method = concat`, since it repeat forever, it doesn't have any defined length.
-
-        Returns:
-            Optional[int]: Number of samples
-        """
-        if self.group_method == 'truncate':
-            return super().__len__()
-        elif self.group_method == 'concat':
-            return None
-        else:
-            raise ValueError(f'Got unknown group_method={self.group_method}.')