add dedupe flag

RedPajama-Data-V2.py

@@ -23,6 +23,8 @@ import os
 import gzip
 from typing import List
 
+import pyarrow.parquet as pq
+
 logger = datasets.logging.get_logger(__name__)
 
 _DESCRIPTION = """\
@@ -188,13 +190,22 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
             ]
         })
 
+        # fetch ids of duplicates
+        duplicates_ids_files = dl_manager.download({
+            "head_middle": [
+                f"sample/duplicates/{lst}.duplicates.parquet"
+                for lst in listings
+            ]
+        })
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "listings_ids": {"head_middle": listings},
                     "documents_files": documents_files,
-                    "quality_signals_files": quality_signals_files
+                    "quality_signals_files": quality_signals_files,
+                    "duplicates_ids_files": duplicates_ids_files
                 }
             )
         ]
@@ -235,16 +246,21 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                         line.strip() for line in f
                     ])
 
-        # build urls pointing to documents and quality signals
+        # build urls pointing to documents, quality signals and duplicate ids
         document_urls = {}
         quality_signals_urls = {}
+        duplicates_ids_urls = {}
         for part, part_listings_ids in listings_ids.items():
+
             document_urls[part] = []
             quality_signals_urls[part] = []
+            duplicates_ids_urls[part] = []
+
             for lst_id in part_listings_ids:
                 document_urls[part].append(
                     os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
                 )
+
                 if part != "head_middle":
                     continue
 
@@ -254,8 +270,15 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                     )
                 )
 
+                duplicates_ids_urls[part].append(
+                    os.path.join(
+                        _URL_BASE, f"duplicates/{lst_id}.duplicates.parquet"
+                    )
+                )
+
         documents_files = dl_manager.download(document_urls)
         quality_signals_files = dl_manager.download(quality_signals_urls)
+        duplicates_ids_files = dl_manager.download(duplicates_ids_urls)
 
         return [
             datasets.SplitGenerator(
@@ -263,7 +286,8 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "listings_ids": listings_ids,
                     "documents_files": documents_files,
-                    "quality_signals_files": quality_signals_files
+                    "quality_signals_files": quality_signals_files,
+                    "duplicates_ids_files": duplicates_ids_files
                 }
             )
         ]
@@ -275,13 +299,15 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
         return self._split_generators_full(dl_manager)
 
     def _generate_examples(
-            self, listings_ids, documents_files, quality_signals_files
+            self, listings_ids, documents_files, quality_signals_files,
+            duplicates_ids_files
     ):
         key = 0
         for part in documents_files.keys():
             part_docs_files = documents_files[part]
             part_qs_files = quality_signals_files[part]
             part_listings_ids = listings_ids[part]
+            part_duplicates_ids_files = duplicates_ids_files[part]
 
             if len(part_qs_files) == 0:
                 for sample in self._handle_tail_partition(
@@ -292,7 +318,9 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                 continue
 
             for sample in self._handle_head_middle_partition(
-                    part, part_docs_files, part_qs_files, part_listings_ids
+                    part, part_docs_files, part_qs_files,
+                    part_duplicates_ids_files, part_listings_ids
+
             ):
                 yield key, sample
                 key += 1
@@ -303,7 +331,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                 for row, doc in enumerate(df):
                     doc_id = f"{listing_id}.json.gz/{row}"
                     try:
-                        yield self.handle_record(part, doc_id, doc, None)
+                        yield self.handle_record(part, doc_id, doc, None, None)
                     except Exception as e:
                         print(f'doc_file: {doc_file}')
                         print(f'row: {row}')
@@ -311,22 +339,41 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                         raise e
 
     def _handle_head_middle_partition(
-            self, part, docs_files, qs_files, listings_ids
+            self, part, docs_files, qs_files, dupes_files, listings_ids,
     ):
         assert len(docs_files) == len(qs_files)
 
         listings_ids = listings_ids[:len(docs_files)]
 
-        for doc_file, qs_file, listings_id in zip(
-                docs_files, qs_files, listings_ids
+        for doc_file, qs_file, dupe_file, listings_id in zip(
+                docs_files, qs_files, dupes_files, listings_ids
         ):
+            # load duplicates
+            try:
+                with open(dupe_file, "rb") as df:
+                    duplicates = set(pq.read_table(
+                        df, columns=["doc_id"], use_pandas_metadata=False
+                    )["doc_id"].to_pylist())
+            except Exception as e:
+                print(f'failed loading duplicate ids from {dupe_file}.')
+                duplicates = set()
+
             try:
                 with gzip.open(doc_file, "rt", encoding="utf-8") as df:
                     with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
                         for row, (doc, qs) in enumerate(zip(df, qf)):
                             doc_id = f"{listings_id}.json.gz/{row}"
+
+                            if doc_id in duplicates:
+                                is_duplicate = True
+                            else:
+                                is_duplicate = False
+
                             try:
-                                yield self.handle_record(part, doc_id, doc, qs)
+                                yield self.handle_record(
+                                    part, doc_id, doc, qs,
+                                    is_duplicate=is_duplicate
+                                )
                             except Exception as e:
                                 print(f'failed handling row {row} in '
                                       f'{doc_file} ({qs_file})')
@@ -339,7 +386,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
                 continue
 
     @staticmethod
-    def handle_record(part, doc_id, doc, qs):
+    def handle_record(part, doc_id, doc, qs, is_duplicate=None):
         doc = json.loads(doc)
         qs = json.loads(qs) if qs is not None else {}
 
@@ -352,11 +399,12 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
             "digest": doc["digest"],
         }
 
-        quality_signals = json.dumps(qs.get("quality_signals", {}))
+        quality_signals = qs.get("quality_signals", {})
+        quality_signals["is_duplicate"] = is_duplicate
 
         return {
             "raw_content": doc["raw_content"],
             "doc_id": doc_id,
             "meta": json.dumps(meta),
-            "quality_signals": quality_signals,
+            "quality_signals": json.dumps(quality_signals),
         }