albertvillanova HF staff commited on
Commit
98d425e
1 Parent(s): 8e45719

Support streaming (#4)

Browse files

- Host data file (4696d9fc2f7f678cd27880718b9f102cefe74496)
- Update and refactor code (46790a05ffbb5a4277937ec95f08970c396398b7)

Files changed (2) hide show
  1. data.zip +3 -0
  2. sofc_materials_articles.py +12 -28
data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:5430c7563887db6067e75bcfbad99dfa83b02b38834dbf5cfd355919d84554ec
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+ size 3627968
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 = "https://github.com/boschresearch/sofc-exp_textmining_resources/archive/master.zip"
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  class SOFCMaterialsArticles(datasets.GeneratorBasedBuilder):
@@ -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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-
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- my_urls = _URL
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- data_dir = dl_manager.download_and_extract(my_urls)
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-
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- data_dir = os.path.join(data_dir, "sofc-exp_textmining_resources-master/sofc-exp-corpus")
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-
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- metadata = pd.read_csv(os.path.join(data_dir, "SOFC-Exp-Metadata.csv"), sep="\t")
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-
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- text_base_path = os.path.join(data_dir, "texts")
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-
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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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-
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- metadata = metadata[metadata["name"].map(lambda x: x in text_files_available)]
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-
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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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  },
@@ -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={"names": names["test"], "data_dir": data_dir, "split": "test"},
 
 
 
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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": "validation",
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  },
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  ),
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  ]
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- def _generate_examples(self, names, data_dir, split):
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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")
@@ -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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-
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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()
@@ -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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-
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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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+
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  # The dataset consists of the original article text as well as annotations
271
  textfile_base_path = os.path.join(data_dir, "texts")
272
  annotations_base_path = os.path.join(data_dir, "annotations")
 
294
  # For each text file, we'll load all of the
295
  # associated annotation files
296
  for id_, name in enumerate(sorted(names)):
 
297
  # Load the main source text
298
  textfile_path = os.path.join(textfile_base_path, name + ".txt")
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  text = open(textfile_path, encoding="utf-8").read()
 
368
  # Iterate through the spans data
369
  spans = []
370
  for span in spans_raw:
 
371
  # 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")
373