Datasets:
				
			
			
	
			
	
		
			
	
		Tasks:
	
	
	
	
	Text Retrieval
	
	
	Modalities:
	
	
	
		
	
	Text
	
	
	Formats:
	
	
	
		
	
	parquet
	
	
	Sub-tasks:
	
	
	
	
	document-retrieval
	
	
	Languages:
	
	
	
		
	
	code
	
	
	Size:
	
	
	
	
	10K - 100K
	
	
	License:
	
	
	
	
	
	
	
Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
- README.md +1 -0
- code_x_glue_cc_clone_detection_poj104.py +30 -24
    	
        README.md
    CHANGED
    
    | @@ -1,4 +1,5 @@ | |
| 1 | 
             
            ---
         | 
|  | |
| 2 | 
             
            annotations_creators:
         | 
| 3 | 
             
            - found
         | 
| 4 | 
             
            language_creators:
         | 
|  | |
| 1 | 
             
            ---
         | 
| 2 | 
            +
            pretty_name: CodeXGlueCcCloneDetectionPoj104
         | 
| 3 | 
             
            annotations_creators:
         | 
| 4 | 
             
            - found
         | 
| 5 | 
             
            language_creators:
         | 
    	
        code_x_glue_cc_clone_detection_poj104.py
    CHANGED
    
    | @@ -1,5 +1,3 @@ | |
| 1 | 
            -
            import os
         | 
| 2 | 
            -
            import os.path
         | 
| 3 | 
             
            from typing import List
         | 
| 4 |  | 
| 5 | 
             
            import datasets
         | 
| @@ -34,27 +32,16 @@ class CodeXGlueCcCloneDetectionPoj104Impl(TrainValidTestChild): | |
| 34 |  | 
| 35 | 
             
                SPLIT_RANGES = {"train": (1, 65), "valid": (65, 81), "test": (81, 195)}
         | 
| 36 |  | 
| 37 | 
            -
                def  | 
| 38 | 
            -
                    yield "data", "programs.tar.gz"
         | 
| 39 | 
            -
             | 
| 40 | 
            -
                def _generate_examples(self, split_name, file_paths):
         | 
| 41 | 
            -
                    def files(path):
         | 
| 42 | 
            -
                        g = os.walk(path)
         | 
| 43 | 
            -
                        file = []
         | 
| 44 | 
            -
                        for path, dir_list, file_list in g:
         | 
| 45 | 
            -
                            for file_name in file_list:
         | 
| 46 | 
            -
                                file.append(os.path.join(path, file_name))
         | 
| 47 | 
            -
                        return file
         | 
| 48 | 
            -
             | 
| 49 | 
            -
                    root_path = file_paths["data"]
         | 
| 50 | 
             
                    cont = 0
         | 
| 51 | 
            -
                    for  | 
| 52 | 
            -
                         | 
| 53 | 
            -
                         | 
|  | |
| 54 | 
             
                            js = {}
         | 
| 55 | 
            -
                            js["label"] =  | 
| 56 | 
             
                            js["id"] = cont
         | 
| 57 | 
            -
                            js["code"] =  | 
| 58 | 
             
                            yield cont, js
         | 
| 59 | 
             
                            cont += 1
         | 
| 60 |  | 
| @@ -81,7 +68,26 @@ class CodeXGlueCcCloneDetectionPoj104(datasets.GeneratorBasedBuilder): | |
| 81 | 
             
                    return ret
         | 
| 82 |  | 
| 83 | 
             
                def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
         | 
| 84 | 
            -
                     | 
| 85 | 
            -
             | 
| 86 | 
            -
             | 
| 87 | 
            -
                    return  | 
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | 
|  | |
|  | |
|  | |
| 1 | 
             
            from typing import List
         | 
| 2 |  | 
| 3 | 
             
            import datasets
         | 
|  | |
| 32 |  | 
| 33 | 
             
                SPLIT_RANGES = {"train": (1, 65), "valid": (65, 81), "test": (81, 195)}
         | 
| 34 |  | 
| 35 | 
            +
                def _generate_examples(self, files, split_name):
         | 
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
| 36 | 
             
                    cont = 0
         | 
| 37 | 
            +
                    for path, f in files:
         | 
| 38 | 
            +
                        # path are in the format ProgramData/{index}/{filename}
         | 
| 39 | 
            +
                        label = int(path.split("/")[1])
         | 
| 40 | 
            +
                        if self.SPLIT_RANGES[split_name][0] <= label <= self.SPLIT_RANGES[split_name][1]:
         | 
| 41 | 
             
                            js = {}
         | 
| 42 | 
            +
                            js["label"] = str(label)
         | 
| 43 | 
             
                            js["id"] = cont
         | 
| 44 | 
            +
                            js["code"] = f.read().decode("latin-1")
         | 
| 45 | 
             
                            yield cont, js
         | 
| 46 | 
             
                            cont += 1
         | 
| 47 |  | 
|  | |
| 68 | 
             
                    return ret
         | 
| 69 |  | 
| 70 | 
             
                def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
         | 
| 71 | 
            +
                    name = self.config.name
         | 
| 72 | 
            +
                    info = DEFINITIONS[name]
         | 
| 73 | 
            +
                    archive = dl_manager.download(info["raw_url"] + "/programs.tar.gz")
         | 
| 74 | 
            +
                    return [
         | 
| 75 | 
            +
                        datasets.SplitGenerator(
         | 
| 76 | 
            +
                            name=datasets.Split.TRAIN,
         | 
| 77 | 
            +
                            # These kwargs will be passed to _generate_examples
         | 
| 78 | 
            +
                            gen_kwargs={"files": dl_manager.iter_archive(archive), "split_name": "train"},
         | 
| 79 | 
            +
                        ),
         | 
| 80 | 
            +
                        datasets.SplitGenerator(
         | 
| 81 | 
            +
                            name=datasets.Split.VALIDATION,
         | 
| 82 | 
            +
                            # These kwargs will be passed to _generate_examples
         | 
| 83 | 
            +
                            gen_kwargs={"files": dl_manager.iter_archive(archive), "split_name": "valid"},
         | 
| 84 | 
            +
                        ),
         | 
| 85 | 
            +
                        datasets.SplitGenerator(
         | 
| 86 | 
            +
                            name=datasets.Split.TEST,
         | 
| 87 | 
            +
                            # These kwargs will be passed to _generate_examples
         | 
| 88 | 
            +
                            gen_kwargs={"files": dl_manager.iter_archive(archive), "split_name": "test"},
         | 
| 89 | 
            +
                        ),
         | 
| 90 | 
            +
                    ]
         | 
| 91 | 
            +
             | 
| 92 | 
            +
                def _generate_examples(self, files, split_name):
         | 
| 93 | 
            +
                    return self.child._generate_examples(files, split_name)
         | 

