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Datasets:
tianyang
/
repobench-p

Tasks:
Text Retrieval
Text Generation
Sub-tasks:
document-retrieval
Languages:
code
ArXiv:
Tags:
code
License:
Dataset card Files Community
tianyang commited on
Commit
b4d852c
•
1 Parent(s): 8c87b52

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Browse files
Files changed (1) hide show
  1. repobench-p.py +16 -35
repobench-p.py CHANGED
@@ -70,40 +70,22 @@ class RepoBenchP(datasets.GeneratorBasedBuilder):
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  )
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  ]
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- DEFAULT_SPLIT_NAME = "cff"
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-
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  def _info(self):
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- if self.DEFAULT_SPLIT_NAME == "if":
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- features = datasets.Features(
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- {
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- "repo_name": datasets.Value("string"),
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- "file_path": datasets.Value("string"),
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- "context": datasets.Sequence(feature={
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- "path": datasets.Value("string"),
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- "identifier": datasets.Value("string"),
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- "snippet": datasets.Value("string")
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- }),
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- "import_statement": datasets.Value("string"),
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- "code": datasets.Value("string"),
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- "next_line": datasets.Value("string")
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- }
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- )
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- else:
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- features = datasets.Features(
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- {
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- "repo_name": datasets.Value("string"),
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- "file_path": datasets.Value("string"),
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- "context": datasets.Sequence(feature={
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- "path": datasets.Value("string"),
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- "identifier": datasets.Value("string"),
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- "snippet": datasets.Value("string")
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- }),
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- "import_statement": datasets.Value("string"),
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- "code": datasets.Value("string"),
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- "next_line": datasets.Value("string"),
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- "gold_snippet_index": datasets.Value("int32")
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- }
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- )
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  return datasets.DatasetInfo(
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  description=_DESCRIPTION,
@@ -143,8 +125,7 @@ class RepoBenchP(datasets.GeneratorBasedBuilder):
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  with gzip.open(data_dir[split], "rb") as f:
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  data = pickle.load(f)
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- self.DEFAULT_SPLIT_NAME = split
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-
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  for i, example in enumerate(data):
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  yield i, example
 
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  )
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  ]
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  def _info(self):
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+ features = datasets.Features(
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+ {
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+ "repo_name": datasets.Value("string"),
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+ "file_path": datasets.Value("string"),
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+ "context": datasets.Sequence(feature={
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+ "path": datasets.Value("string"),
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+ "identifier": datasets.Value("string"),
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+ "snippet": datasets.Value("string")
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+ }),
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+ "import_statement": datasets.Value("string"),
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+ "code": datasets.Value("string"),
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+ "next_line": datasets.Value("string"),
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+ "gold_snippet_index": datasets.Value("int32"),
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+ }
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+ )
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  return datasets.DatasetInfo(
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  description=_DESCRIPTION,
 
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  with gzip.open(data_dir[split], "rb") as f:
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  data = pickle.load(f)
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+
 
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  for i, example in enumerate(data):
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  yield i, example