sc_ma commited on
Commit
4e7254f
1 Parent(s): 26d461c

Testing output file error in Spaces.

Browse files
latex_templates/ICLR2022/abstract.tex ADDED
File without changes
latex_templates/ICLR2022/backgrounds.tex ADDED
File without changes
latex_templates/ICLR2022/conclusion.tex ADDED
File without changes
latex_templates/ICLR2022/experiments.tex ADDED
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latex_templates/ICLR2022/introduction.tex ADDED
File without changes
latex_templates/ICLR2022/methodology.tex ADDED
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latex_templates/ICLR2022/related works.tex ADDED
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utils/references.py CHANGED
@@ -133,9 +133,8 @@ class References:
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  paper_ids.append(paper["paper_id"])
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  # Save the generated BibTeX entries to a file
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  with open(path_to_bibtex, "a", encoding="utf-8") as file:
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- for entry in bibtex_entries:
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- file.write(entry)
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- file.write("\n\n")
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  return paper_ids
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  def to_prompts(self):
@@ -149,7 +148,13 @@ class References:
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  if __name__ == "__main__":
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  refs = References()
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- keywords_dict = {"machine learning 1": 10, "machine learning 2":10}
 
 
 
 
 
 
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  refs.collect_papers(keywords_dict)
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  for p in refs.papers:
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  print(p["paper_id"])
 
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  paper_ids.append(paper["paper_id"])
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  # Save the generated BibTeX entries to a file
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  with open(path_to_bibtex, "a", encoding="utf-8") as file:
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+ file.write(bibtex_entry)
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+ file.write("\n\n")
 
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  return paper_ids
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  def to_prompts(self):
 
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  if __name__ == "__main__":
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  refs = References()
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+ keywords_dict = {
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+ "Deep Q-Networks": 5,
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+ "Policy Gradient Methods": 4,
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+ "Actor-Critic Algorithms": 4,
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+ "Model-Based Reinforcement Learning": 3,
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+ "Exploration-Exploitation Trade-off": 2
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+ }
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  refs.collect_papers(keywords_dict)
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  for p in refs.papers:
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  print(p["paper_id"])