Datasets:
Maurice Weber
commited on
Commit
•
eee2123
1
Parent(s):
2cae54f
Revert "add dedupe flag"
Browse filesThis reverts commit 2cae54f422505166bf6529ab2d2835fe2e1723b1.
- RedPajama-Data-V2.py +13 -61
RedPajama-Data-V2.py
CHANGED
@@ -23,8 +23,6 @@ import os
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import gzip
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from typing import List
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-
import pyarrow.parquet as pq
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-
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """\
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@@ -190,22 +188,13 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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]
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})
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-
# fetch ids of duplicates
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duplicates_ids_files = dl_manager.download({
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"head_middle": [
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f"sample/duplicates/{lst}.duplicates.parquet"
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for lst in listings
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]
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})
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-
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"listings_ids": {"head_middle": listings},
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"documents_files": documents_files,
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-
"quality_signals_files": quality_signals_files
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"duplicates_ids_files": duplicates_ids_files
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}
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)
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]
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@@ -246,21 +235,16 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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line.strip() for line in f
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])
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-
# build urls pointing to documents
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document_urls = {}
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quality_signals_urls = {}
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duplicates_ids_urls = {}
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for part, part_listings_ids in listings_ids.items():
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-
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document_urls[part] = []
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quality_signals_urls[part] = []
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duplicates_ids_urls[part] = []
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-
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for lst_id in part_listings_ids:
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document_urls[part].append(
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os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
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)
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-
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if part != "head_middle":
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continue
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@@ -270,15 +254,8 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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)
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)
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duplicates_ids_urls[part].append(
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os.path.join(
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_URL_BASE, f"duplicates/{lst_id}.duplicates.parquet"
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)
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)
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-
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documents_files = dl_manager.download(document_urls)
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quality_signals_files = dl_manager.download(quality_signals_urls)
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duplicates_ids_files = dl_manager.download(duplicates_ids_urls)
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return [
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datasets.SplitGenerator(
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@@ -286,8 +263,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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gen_kwargs={
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"listings_ids": listings_ids,
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"documents_files": documents_files,
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-
"quality_signals_files": quality_signals_files
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-
"duplicates_ids_files": duplicates_ids_files
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}
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)
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]
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@@ -299,15 +275,13 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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return self._split_generators_full(dl_manager)
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def _generate_examples(
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self, listings_ids, documents_files, quality_signals_files
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duplicates_ids_files
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):
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key = 0
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for part in documents_files.keys():
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part_docs_files = documents_files[part]
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part_qs_files = quality_signals_files[part]
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part_listings_ids = listings_ids[part]
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part_duplicates_ids_files = duplicates_ids_files[part]
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if len(part_qs_files) == 0:
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for sample in self._handle_tail_partition(
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@@ -318,9 +292,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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continue
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for sample in self._handle_head_middle_partition(
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part, part_docs_files, part_qs_files,
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part_duplicates_ids_files, part_listings_ids
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-
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):
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yield key, sample
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key += 1
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@@ -331,7 +303,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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for row, doc in enumerate(df):
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doc_id = f"{listing_id}.json.gz/{row}"
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try:
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yield self.handle_record(part, doc_id, doc, None
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except Exception as e:
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print(f'doc_file: {doc_file}')
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print(f'row: {row}')
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@@ -339,41 +311,22 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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raise e
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def _handle_head_middle_partition(
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self, part, docs_files, qs_files,
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):
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assert len(docs_files) == len(qs_files)
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listings_ids = listings_ids[:len(docs_files)]
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for doc_file, qs_file,
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docs_files, qs_files,
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):
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# load duplicates
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try:
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with open(dupe_file, "rb") as df:
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duplicates = set(pq.read_table(
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df, columns=["doc_id"], use_pandas_metadata=False
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)["doc_id"].to_pylist())
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except Exception as e:
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print(f'failed loading duplicate ids from {dupe_file}.')
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duplicates = set()
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-
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try:
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with gzip.open(doc_file, "rt", encoding="utf-8") as df:
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with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
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for row, (doc, qs) in enumerate(zip(df, qf)):
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doc_id = f"{listings_id}.json.gz/{row}"
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-
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if doc_id in duplicates:
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is_duplicate = True
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else:
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is_duplicate = False
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-
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try:
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yield self.handle_record(
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part, doc_id, doc, qs,
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is_duplicate=is_duplicate
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)
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except Exception as e:
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print(f'failed handling row {row} in '
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f'{doc_file} ({qs_file})')
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@@ -386,7 +339,7 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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continue
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@staticmethod
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def handle_record(part, doc_id, doc, qs
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doc = json.loads(doc)
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qs = json.loads(qs) if qs is not None else {}
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@@ -399,12 +352,11 @@ class RedPajamaV2(datasets.GeneratorBasedBuilder):
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"digest": doc["digest"],
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}
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quality_signals = qs.get("quality_signals", {})
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quality_signals["is_duplicate"] = is_duplicate
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return {
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"raw_content": doc["raw_content"],
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"doc_id": doc_id,
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"meta": json.dumps(meta),
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"quality_signals":
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}
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import gzip
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from typing import List
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """\
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]
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})
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"listings_ids": {"head_middle": listings},
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"documents_files": documents_files,
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+
"quality_signals_files": quality_signals_files
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}
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)
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]
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line.strip() for line in f
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])
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+
# build urls pointing to documents and quality signals
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document_urls = {}
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quality_signals_urls = {}
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for part, part_listings_ids in listings_ids.items():
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document_urls[part] = []
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quality_signals_urls[part] = []
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for lst_id in part_listings_ids:
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document_urls[part].append(
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os.path.join(_URL_BASE, f"documents/{lst_id}.json.gz")
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)
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if part != "head_middle":
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continue
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)
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)
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documents_files = dl_manager.download(document_urls)
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quality_signals_files = dl_manager.download(quality_signals_urls)
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return [
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datasets.SplitGenerator(
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gen_kwargs={
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"listings_ids": listings_ids,
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"documents_files": documents_files,
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+
"quality_signals_files": quality_signals_files
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}
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)
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]
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return self._split_generators_full(dl_manager)
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def _generate_examples(
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+
self, listings_ids, documents_files, quality_signals_files
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):
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key = 0
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for part in documents_files.keys():
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part_docs_files = documents_files[part]
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part_qs_files = quality_signals_files[part]
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part_listings_ids = listings_ids[part]
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if len(part_qs_files) == 0:
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for sample in self._handle_tail_partition(
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continue
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for sample in self._handle_head_middle_partition(
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part, part_docs_files, part_qs_files, part_listings_ids
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):
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yield key, sample
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key += 1
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for row, doc in enumerate(df):
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doc_id = f"{listing_id}.json.gz/{row}"
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try:
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yield self.handle_record(part, doc_id, doc, None)
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except Exception as e:
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print(f'doc_file: {doc_file}')
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print(f'row: {row}')
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raise e
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def _handle_head_middle_partition(
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self, part, docs_files, qs_files, listings_ids
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):
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assert len(docs_files) == len(qs_files)
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listings_ids = listings_ids[:len(docs_files)]
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+
for doc_file, qs_file, listings_id in zip(
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+
docs_files, qs_files, listings_ids
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):
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try:
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with gzip.open(doc_file, "rt", encoding="utf-8") as df:
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with gzip.open(qs_file, "rt", encoding="utf-8") as qf:
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for row, (doc, qs) in enumerate(zip(df, qf)):
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doc_id = f"{listings_id}.json.gz/{row}"
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try:
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+
yield self.handle_record(part, doc_id, doc, qs)
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except Exception as e:
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print(f'failed handling row {row} in '
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f'{doc_file} ({qs_file})')
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continue
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@staticmethod
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+
def handle_record(part, doc_id, doc, qs):
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doc = json.loads(doc)
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qs = json.loads(qs) if qs is not None else {}
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"digest": doc["digest"],
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}
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+
quality_signals = json.dumps(qs.get("quality_signals", {}))
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return {
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"raw_content": doc["raw_content"],
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"doc_id": doc_id,
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"meta": json.dumps(meta),
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+
"quality_signals": quality_signals,
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}
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