Commit
•
46790a0
1
Parent(s):
4696d9f
Update and refactor code
Browse files- sofc_materials_articles.py +12 -28
sofc_materials_articles.py
CHANGED
@@ -45,7 +45,7 @@ _HOMEPAGE = "https://arxiv.org/abs/2006.03039"
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_LICENSE = ""
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_URL = "
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class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
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@@ -232,33 +232,14 @@ class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_dir = dl_manager.download_and_extract(my_urls)
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data_dir = os.path.join(data_dir, "sofc-exp_textmining_resources-master/sofc-exp-corpus")
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metadata = pd.read_csv(os.path.join(data_dir, "SOFC-Exp-Metadata.csv"), sep="\t")
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text_base_path = os.path.join(data_dir, "texts")
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text_files_available = [
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os.path.split(i.rstrip(".txt"))[-1] for i in glob.glob(os.path.join(text_base_path, "*.txt"))
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]
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metadata = metadata[metadata["name"].map(lambda x: x in text_files_available)]
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names = {}
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splits = ["train", "test", "dev"]
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for split in splits:
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names[split] = metadata[metadata["set"] == split]["name"].tolist()
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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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"names": names["train"],
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"data_dir": data_dir,
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"split": "train",
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},
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@@ -266,21 +247,26 @@ class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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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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),
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datasets.SplitGenerator(
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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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"names": names["dev"],
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"data_dir": data_dir,
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"split": "
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},
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),
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]
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def _generate_examples(self,
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"""Yields examples."""
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# The dataset consists of the original article text as well as annotations
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textfile_base_path = os.path.join(data_dir, "texts")
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annotations_base_path = os.path.join(data_dir, "annotations")
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@@ -308,7 +294,6 @@ class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
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# For each text file, we'll load all of the
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# associated annotation files
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for id_, name in enumerate(sorted(names)):
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# Load the main source text
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textfile_path = os.path.join(textfile_base_path, name + ".txt")
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text = open(textfile_path, encoding="utf-8").read()
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@@ -383,7 +368,6 @@ class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
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# Iterate through the spans data
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spans = []
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for span in spans_raw:
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# Split out the elements in each tab-delimited line
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_, span_id, entity_label_or_exp, sentence_id, begin_char_offset, end_char_offset = span.split("\t")
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_LICENSE = ""
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_URL = "data.zip"
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class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_dir = dl_manager.download_and_extract(_URL)
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data_dir = os.path.join(data_dir, "sofc-exp-corpus")
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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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"data_dir": data_dir,
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"split": "train",
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},
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datasets.SplitGenerator(
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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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"data_dir": data_dir,
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"split": "test",
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},
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),
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datasets.SplitGenerator(
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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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"data_dir": data_dir,
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"split": "dev",
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},
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),
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]
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def _generate_examples(self, data_dir, split):
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"""Yields examples."""
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metadata = pd.read_csv(os.path.join(data_dir, "SOFC-Exp-Metadata.csv"), sep="\t")
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names = metadata[metadata["set"] == split]["name"].tolist()
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# The dataset consists of the original article text as well as annotations
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textfile_base_path = os.path.join(data_dir, "texts")
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annotations_base_path = os.path.join(data_dir, "annotations")
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# For each text file, we'll load all of the
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# associated annotation files
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for id_, name in enumerate(sorted(names)):
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# Load the main source text
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textfile_path = os.path.join(textfile_base_path, name + ".txt")
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text = open(textfile_path, encoding="utf-8").read()
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# Iterate through the spans data
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spans = []
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for span in spans_raw:
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# Split out the elements in each tab-delimited line
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_, span_id, entity_label_or_exp, sentence_id, begin_char_offset, end_char_offset = span.split("\t")
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