Datasets:
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37831c2
1
Parent(s):
5759e63
Upload gdds.py
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gdds.py
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@@ -1,4 +1,6 @@
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import csv
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import json
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import os
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@@ -25,6 +27,7 @@ _HOMEPAGE = ""
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_LICENSE = ""
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# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
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class GDDS(datasets.GeneratorBasedBuilder):
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"""TODO: Short description of my dataset."""
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@@ -84,13 +87,15 @@ class GDDS(datasets.GeneratorBasedBuilder):
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# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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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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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(
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"split": "train",
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},
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),
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@@ -98,7 +103,7 @@ class GDDS(datasets.GeneratorBasedBuilder):
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name=datasets.Split.VALIDATION,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(
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"split": "dev",
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},
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),
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@@ -106,7 +111,7 @@ class GDDS(datasets.GeneratorBasedBuilder):
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(
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"split": "test"
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},
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),
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+
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+
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import csv
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import json
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import os
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_LICENSE = ""
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+
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# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
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class GDDS(datasets.GeneratorBasedBuilder):
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"""TODO: Short description of my dataset."""
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# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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# urls = _URLS[self.config.name]
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data_dir = dl_manager.download_and_extract(self.config.name)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(data_dir, "train.jsonl"),
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"split": "train",
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},
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),
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name=datasets.Split.VALIDATION,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(data_dir, "validate.jsonl"),
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"split": "dev",
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},
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),
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(data_dir, "test.jsonl"),
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"split": "test"
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},
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),
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