Support streaming (#3)

- Do not extract uncompressed files (1e2ad5d30828fc7dc6761f59944feaa456e17895)
- Delete legacy dataset_infos.json (31e765220da43898b9994902a1373bbe518eac11)
- Update citation information (d53259bcb2908dee2464f5cb7b4e80650913e9f3)
- Add paper (4ba38d82058576f06f0cdf455e6192a9c0dbf31a)

README.md

@@ -69,13 +69,15 @@ dataset_info:
 ## Dataset Description
 
 - **Homepage:** https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans
+- **Paper:** https://arxiv.org/abs/2102.04664
 
 ### Dataset Summary
 
 CodeXGLUE code-to-code-trans dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans
 
 The dataset is collected from several public repos, including Lucene(http://lucene.apache.org/), POI(http://poi.apache.org/), JGit(https://github.com/eclipse/jgit/) and Antlr(https://github.com/antlr/).
-        We collect both the Java and C# versions of the codes and find the parallel functions. After removing duplicates and functions with the empty body, we split the whole dataset into training, validation and test sets.
+
+We collect both the Java and C# versions of the codes and find the parallel functions. After removing duplicates and functions with the empty body, we split the whole dataset into training, validation and test sets.
 
 ### Supported Tasks and Leaderboards
 
@@ -174,9 +176,35 @@ Computational Use of Data Agreement (C-UDA) License.
 ### Citation Information
 
 ```
-@article{CodeXGLUE,
-         title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
-         year={2020},}
+@article{DBLP:journals/corr/abs-2102-04664,
+  author    = {Shuai Lu and
+               Daya Guo and
+               Shuo Ren and
+               Junjie Huang and
+               Alexey Svyatkovskiy and
+               Ambrosio Blanco and
+               Colin B. Clement and
+               Dawn Drain and
+               Daxin Jiang and
+               Duyu Tang and
+               Ge Li and
+               Lidong Zhou and
+               Linjun Shou and
+               Long Zhou and
+               Michele Tufano and
+               Ming Gong and
+               Ming Zhou and
+               Nan Duan and
+               Neel Sundaresan and
+               Shao Kun Deng and
+               Shengyu Fu and
+               Shujie Liu},
+  title     = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
+               and Generation},
+  journal   = {CoRR},
+  volume    = {abs/2102.04664},
+  year      = {2021}
+}
 ```
 
 ### Contributions

common.py

@@ -47,7 +47,7 @@ class Child:
 
         downloaded_files = {}
         for k, v in urls_to_download.items():
-            downloaded_files[k] = dl_manager.download_and_extract(v)
+            downloaded_files[k] = dl_manager.download(v)
 
         return [
             datasets.SplitGenerator(

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "CodeXGLUE code-to-code-trans dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans\n\nThe dataset is collected from several public repos, including Lucene(http://lucene.apache.org/), POI(http://poi.apache.org/), JGit(https://github.com/eclipse/jgit/) and Antlr(https://github.com/antlr/).\n        We collect both the Java and C# versions of the codes and find the parallel functions. After removing duplicates and functions with the empty body, we split the whole dataset into training, validation and test sets.", "citation": "@article{DBLP:journals/corr/abs-2102-04664,\n  author    = {Shuai Lu and\n               Daya Guo and\n               Shuo Ren and\n               Junjie Huang and\n               Alexey Svyatkovskiy and\n               Ambrosio Blanco and\n               Colin B. Clement and\n               Dawn Drain and\n               Daxin Jiang and\n               Duyu Tang and\n               Ge Li and\n               Lidong Zhou and\n               Linjun Shou and\n               Long Zhou and\n               Michele Tufano and\n               Ming Gong and\n               Ming Zhou and\n               Nan Duan and\n               Neel Sundaresan and\n               Shao Kun Deng and\n               Shengyu Fu and\n               Shujie Liu},\n  title     = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding\n               and Generation},\n  journal   = {CoRR},\n  volume    = {abs/2102.04664},\n  year      = {2021}\n}", "homepage": "https://github.com/madlag/CodeXGLUE/tree/main/Code-Code/code-to-code-trans", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "java": {"dtype": "string", "id": null, "_type": "Value"}, "cs": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "code_x_glue_cc_code_to_code_trans", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4372657, "num_examples": 10300, "dataset_name": "code_x_glue_cc_code_to_code_trans"}, "validation": {"name": "validation", "num_bytes": 226415, "num_examples": 500, "dataset_name": "code_x_glue_cc_code_to_code_trans"}, "test": {"name": "test", "num_bytes": 418595, "num_examples": 1000, "dataset_name": "code_x_glue_cc_code_to_code_trans"}}, "download_checksums": {"https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/code-to-code-trans/data/train.java-cs.txt.cs": {"num_bytes": 2387613, "checksum": "8f9e154e38b17cf19840a44c50a00b6fa16397336c302e3cf514b29ddfafa0e9"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/code-to-code-trans/data/train.java-cs.txt.java": {"num_bytes": 1861428, "checksum": "3d2ba1a8f5de30688663ce76bf9b061574d330fc54eb08c4b7eccda74f42be67"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/code-to-code-trans/data/valid.java-cs.txt.cs": {"num_bytes": 124022, "checksum": "687c61db799e9e3369a0822184ba67bb5b007c48025f25d44084cc6f525ce4ea"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/code-to-code-trans/data/valid.java-cs.txt.java": {"num_bytes": 96385, "checksum": "aed88f2a31af5b6367100bfbca6d9c4888fa63685502b21db817d8b0f0ad5272"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/code-to-code-trans/data/test.java-cs.txt.cs": {"num_bytes": 229147, "checksum": "4137527f96c898372e368c75deb3ec8c17c1187ac5a1ae641da1df65e143cd2d"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/code-to-code-trans/data/test.java-cs.txt.java": {"num_bytes": 177440, "checksum": "cad0fb08ae59443baeeb1f58de3af83786358dac8ce3a81fd026708ca1b9b2ee"}}, "download_size": 4876035, "post_processing_size": null, "dataset_size": 5017667, "size_in_bytes": 9893702}}