Datasets:
Size:
1M<n<10M
ArXiv:
Tags:
programming-language
code
program-synthesis
automatic-code-repair
code-retrieval
code-translation
License:
Add file_name feature
Browse files- xCodeEval.py +10 -0
xCodeEval.py
CHANGED
@@ -209,6 +209,7 @@ _PROB_DESC_TEXT_FEATURES = {
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_TEXT_FEATURES = {
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"apr": {
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"similarity_score",
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"equal_cnt",
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"replace_cnt",
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@@ -230,6 +231,7 @@ _TEXT_FEATURES = {
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"lang_cluster",
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},
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"code_translation": {
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"lang",
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"source_code",
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"code_uid",
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@@ -238,6 +240,7 @@ _TEXT_FEATURES = {
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"exec_outcome",
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},
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"program_synthesis": {
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"lang",
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"source_code",
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"tags",
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@@ -248,22 +251,26 @@ _TEXT_FEATURES = {
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"exec_outcome"
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},
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"retrieval_code_code": {
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"positive_code",
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"negative_code",
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"src_uid",
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"source_code",
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},
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"retrieval_nl_code": {
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"nl",
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"positive_code",
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"negative_code",
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"src_uid",
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},
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"retrieval_corpus": {
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"idx",
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"source_code",
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},
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"code_compilation": {
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"lang",
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"source_code",
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"compilation_error",
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@@ -272,6 +279,7 @@ _TEXT_FEATURES = {
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"difficulty",
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},
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"tag_classification": {
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"lang",
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"source_code",
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"tags",
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@@ -2060,9 +2068,11 @@ class xCodeEval(datasets.GeneratorBasedBuilder):
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idx = 0
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for filepath in filepaths:
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with open(filepath) as rp:
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for line in rp:
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sample = json.loads(line)
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for pre_feature in list(sample.keys()):
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if pre_feature not in _TEXT_FEATURES[task_name]:
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sample.pop(pre_feature)
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_TEXT_FEATURES = {
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"apr": {
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+
"file_name",
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"similarity_score",
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"equal_cnt",
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"replace_cnt",
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"lang_cluster",
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},
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"code_translation": {
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+
"file_name",
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"lang",
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"source_code",
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"code_uid",
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"exec_outcome",
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},
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"program_synthesis": {
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+
"file_name",
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"lang",
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"source_code",
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"tags",
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"exec_outcome"
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},
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"retrieval_code_code": {
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+
"file_name",
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"positive_code",
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"negative_code",
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"src_uid",
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"source_code",
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},
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"retrieval_nl_code": {
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+
"file_name",
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"nl",
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"positive_code",
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"negative_code",
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"src_uid",
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},
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"retrieval_corpus": {
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+
"file_name",
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"idx",
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"source_code",
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},
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"code_compilation": {
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+
"file_name",
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"lang",
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"source_code",
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"compilation_error",
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"difficulty",
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},
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"tag_classification": {
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+
"file_name",
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"lang",
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"source_code",
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"tags",
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idx = 0
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for filepath in filepaths:
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+
file_name = filepath.split("/")[-1]
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with open(filepath) as rp:
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for line in rp:
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sample = json.loads(line)
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+
sample["file_name"] = file_name
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for pre_feature in list(sample.keys()):
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if pre_feature not in _TEXT_FEATURES[task_name]:
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sample.pop(pre_feature)
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