Create atlas-preprocessed-code.py

atlas-preprocessed-code.py

@@ -0,0 +1,125 @@
+import json
+import datasets
+import traceback
+import os
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """\
+RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset.
+"""
+
+# Define a list of programming languages for the subsets
+_LANGUAGE_SUBSETS = ["csharp", "cplusplus", "c", "go", "html", "haskell", 
+                     "java", "javascript", "jupyter", "kotlin", "php", "perl",
+                     "python", "ruby", "rust", "shell", "swift", "typescript", "v"]
+
+# Generate URLs for the subsets
+_URL_LISTS = {language: f"https://huggingface.co/datasets/AtlasUnified/atlas-preprocessed-code/blob/main/{language}.jsonl"
+              for language in _LANGUAGE_SUBSETS}
+
+_URL_BASE = 'https://data.together.xyz/redpajama-data-1T/v1.0.0'
+
+_DATA_DIR = os.environ.get('RED_PAJAMA_DATA_DIR', None)
+
+class RedPajama1TConfig(datasets.BuilderConfig):
+    """BuilderConfig for RedPajama sample."""
+
+    def __init__(self, *args, subsets, **kwargs):
+        """BuilderConfig for RedPajama.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(RedPajama1TConfig, self).__init__(**kwargs)
+        self.subsets = subsets
+
+class RedPajama1T(datasets.GeneratorBasedBuilder):
+    """RedPajama: Reproducing the LLaMA training dataset of over 1.2 trillion tokens. Version 1.0.0."""
+
+    # Generate builder configs for each language subset
+    BUILDER_CONFIGS = [RedPajama1TConfig(name=language, 
+                                         subsets=[language], 
+                                         version=datasets.Version("1.0.0", ""), 
+                                         description=f"RedPajama1T {language} subset") 
+                       for language in _LANGUAGE_SUBSETS]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "meta": datasets.Value("string"),
+                    "red_pajama_subset": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        url_lists = dl_manager.download_and_extract({
+            subset: _URL_LISTS[subset] for subset in self.config.subsets
+        })
+
+        urls = {}
+
+        for subset, url_list in url_lists.items():
+            with open(url_list, encoding="utf-8") as f:
+                urls[subset] = [line.strip() for line in f]
+
+        if _DATA_DIR is not None:
+            print(f'Reading data from {_DATA_DIR}')
+            url_prefix_slashes = len(_URL_BASE.split('/'))
+            downloaded_files = {
+                subset: [
+                    os.path.join(_DATA_DIR, *url.split('/')[url_prefix_slashes:])
+                    for url in url_list
+                ]
+                for subset, url_list in urls.items()
+            }
+        else:
+            downloaded_files = dl_manager.download(urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs = {
+                    "files": {
+                        subset: downloaded_files[subset]
+                        for subset in self.config.subsets
+                    }
+                }
+            )
+        ]
+
+    def _generate_examples(self, files):
+        """This function returns the examples in the raw (text) form."""
+        key = 0
+        for subset in files:
+            for path in files[subset]:
+                with open(path, encoding="utf-8") as f:
+                    for i, row in enumerate(f):
+                        try:
+                            data = json.loads(row)
+                            if "meta" not in data:
+                                text = data["text"]
+                                del data["text"]
+                                yield key, {
+                                    "text": text,
+                                    "meta": json.dumps(data),
+                                    "red_pajama_subset": subset,
+                                }
+                            else:
+                                yield key, {
+                                    "text": data["text"],
+                                    "meta": data["meta"],
+                                    "red_pajama_subset": subset,
+                                }
+                            key += 1
+                        except Exception as e:
+                            print(f'Subset: {subset}')
+                            print(f'Path: {path}')
+                            print(f'Row: {row}')
+                            traceback.print_exc()
+
+                            raise e