Upload RedPajama-Data-1T-no-cc-c4.py

RedPajama-Data-1T-no-cc-c4.py

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+# Copyright 2023 Together Computer
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""RedPajama: An Open-Source, Clean-Room 1.2 Trillion Token Dataset."""
+
+
+import json
+
+import datasets
+import traceback
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_DESCRIPTION = """\
+RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset.
+"""
+
+_URL_LISTS = {
+    "arxiv": "urls/arxiv.txt",
+    "book": "urls/book.txt",
+    "github": "urls/github.txt",
+    "stackexchange": "urls/stackexchange.txt",
+    "wikipedia": "urls/wikipedia.txt",
+}
+
+
+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."""
+
+    BUILDER_CONFIGS = [
+        RedPajama1TConfig(
+            subsets = list(_URL_LISTS.keys()),
+            name="plain_text",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text",
+        ),
+    ]
+
+    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][:1]
+
+        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:
+            if subset == "common_crawl":
+                import zstandard as zstd
+
+                for path in files[subset]:
+                    with zstd.open(open(path, "rb"), "rt", encoding="utf-8") as f:
+                        for i, row in enumerate(f):
+                            try:
+                                data = json.loads(row)
+                                text = data["text"]
+                                del data["text"]
+                                yield key, {
+                                    "text": text,
+                                    "meta": json.dumps(data),
+                                    "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
+            else:
+                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