dataloader

proof-pile-2.py

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+import json
+import os
+
+import datasets
+
+_CITATION="""\
+@article{azerbayev2023llemma,
+    title={Llemma: an open language model for mathematics},
+    author={Zhangir Azerbayev and Hailey Schoelkopf and Keiran Paster and Marco Dos Santos and Stephen McAleer and Albert Q. Jiang and Jia Deng and Stella Biderman and Sean Welleck},
+    eprint={xyz.xyz},
+    archivePrefix={arXiv}
+    year={2023}
+}
+"""
+
+_DESCRIPTION = """\
+A dataset of high quality mathematical text. """
+_HOMEPAGE = "https://github.com/EleutherAI/math-lm"
+
+
+SPLITS = ("train", "validation", "test")
+
+_DATA_PATHS = {
+        "redpajama-arxiv": {
+            {split: [f'redpajama-arxiv/{split}/arXiv_{str(i).zfill(3)}.jsonl.gz' for i in range(100)]}
+            for split in SPLITS        
+        },
+        "open-web-math": {
+            {split: [f'open-web-math/{split}/shard-{str(i).zfill(4)}.jsonl.gz' for i in range(63)]}
+            for split in SPLITS
+        },
+        "algebraic-stack": {
+            {
+                split: [
+                    os.path.join(f"algebraic-stack/{split}", filename)
+                    for filename in os.listdir(f"algebraic-stack/{split}")
+                ]
+            }
+            for split in SPLITS
+        }
+}
+
+class ProofPile2Config(datasets.BuilderConfig):
+    """BuilderConfig for RedPajama sample."""
+
+    def __init__(self, *args, subsets, **kwargs):
+        """BuilderConfig for ProofPile2.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ProofPile2Config, self).__init__(**kwargs)
+        self.subsets = subsets
+
+
+class ProofPile2(datasets.GeneratorBasedBuilder):
+    """A large dataset of mathematical text."""
+    VERSION = datasets.Version("1.0.0")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name='default',
+            subsets=list(_DATA_PATHS.keys()),
+            version=VERSION,
+            description="All subsets"
+        ),
+        datasets.BuilderConfig(
+            name='redpajama-arxiv',
+            subsets=["redpajama-arxiv"],
+            version=VERSION,
+            description="ArXiv subset"
+        ),
+        datasets.BuilderConfig(
+            name='open-web-math',
+            subsets=['open-web-math'],
+            version=VERSION,
+            description="OpenWebMath"
+        ),
+        datasets.BuilderConfig(
+            name='algebraic-stack',
+            subsets=['algebraic-stack'],
+            version=VERSION,
+            description="Code subset"
+        ),
+    ]
+
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+                "meta": datasets.Value("string")
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        return [ 
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "data_files": map(dl_manager.download_and_extract, [*_DATA_PATHS[subset]["train"] for subset in self.config.subsets]),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, 
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "data_files": map(dl_manager.download_and_extract, [*_DATA_PATHS[subset]["validation"] for subset in self.config.subsets]),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, 
+                gen_kwargs={
+                    "data_files": map(dl_manager.download_and_extract, [*_DATA_PATHS[subset]["test"] for subset in self.config.subsets]),
+                }, 
+            ), 
+        ]
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, data_files):
+        key = 0 
+        for name in data_files: 
+            with open(name) as f: 
+                instances = [json.loads(x) for x in f.readlines() if x]
+            for instance in instances: 
+                yield key, {"text": instance["text"], "meta": json.dumps(instance["meta"])}
+                key += 1 

test_dataloader.py

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+from datasets import load_dataset
+import tqdm
+import time
+
+def main():
+    for subset in ["algebraic-stack"]:
+        data = load_dataset(".", subset)
+        print(data)
+
+        start = time.time()
+        for x in tqdm(data):
+            pass
+        total = time.time() - start
+
+        print(f"Traversed {subset} in {total} seconds")
+
+if __name__=="__main__":
+    main()