Delete loading script

code_x_glue_cc_code_completion_token.py

@@ -1,220 +0,0 @@
-import os
-import os.path
-from typing import List
-
-import datasets
-
-from .common import Child
-from .generated_definitions import DEFINITIONS
-
-
-_DESCRIPTION = """Predict next code token given context of previous tokens. Models are evaluated by token level accuracy.
-Code completion is a one of the most widely used features in software development through IDEs. An effective code completion tool could improve software developers' productivity. We provide code completion evaluation tasks in two granularities -- token level and line level. Here we introduce token level code completion. Token level task is analogous to language modeling. Models should have be able to predict the next token in arbitary types.
-"""
-
-_CITATION = """@article{raychev2016probabilistic,
-    title={Probabilistic Model for Code with Decision Trees},
-    author={Raychev, Veselin and Bielik, Pavol and Vechev, Martin},
-    journal={ACM SIGPLAN Notices},
-    pages={731--747},
-    year={2016},
-    publisher={ACM New York, NY, USA}
-}
-@inproceedings{allamanis2013mining,
-    title={Mining Source Code Repositories at Massive Scale using Language Modeling},
-    author={Allamanis, Miltiadis and Sutton, Charles},
-    booktitle={2013 10th Working Conference on Mining Software Repositories (MSR)},
-    pages={207--216},
-    year={2013},
-    organization={IEEE}
-}
-@dataset{rafael_michael_karampatsis_2020_3628665,
-  author       = {Rafael - Michael Karampatsis and
-                  Hlib Babii and
-                  Romain Robbes and
-                  Charles Sutton and
-                  Andrea Janes},
-  title        = {Preprocessed Java Code Corpus},
-  month        = jan,
-  year         = 2020,
-  publisher    = {Zenodo},
-  version      = {1.0},
-  doi          = {10.5281/zenodo.3628665},
-  url          = {https://doi.org/10.5281/zenodo.3628665}
-}"""
-
-
-class CodeXGlueCcCodeCompletionTokenImpl(Child):
-    _DESCRIPTION = _DESCRIPTION
-    _CITATION = _CITATION
-
-
-class CodeXGlueCcCodeCompletionTokenJavaImpl(CodeXGlueCcCodeCompletionTokenImpl):
-    SPLITS = {
-        "training": datasets.Split.TRAIN,
-        "validation": datasets.Split.VALIDATION,
-        "test": datasets.Split.TEST,
-    }
-
-    _FEATURES = {
-        "id": datasets.Value("int32"),  # Index of the sample
-        "code": datasets.features.Sequence(datasets.Value("string")),  # Code Tokens
-    }
-
-    def generate_urls(self, split_name):
-        language = self.info["parameters"]["language"]
-        if language != "java":
-            raise RuntimeError(f"Unknown language {language}: should be java.")
-
-        yield "data", f"https://huggingface.co/datasets/code_x_glue_cc_code_completion_token/resolve/main/data/java/java_{split_name}_pre"
-
-    def _generate_examples(self, split_name, file_paths):
-        with open(file_paths["data"], encoding="utf-8") as f:
-            for idx, line in enumerate(f):
-                new_data = []
-                for token in line.strip().split():
-                    if len(token) > 100:
-                        continue
-                    new_data.append(token)
-                entry = dict(id=idx, code=new_data)
-                yield idx, entry
-
-
-class CodeXGlueCcCodeCompletionTokenPythonImpl(CodeXGlueCcCodeCompletionTokenImpl):
-    SPLITS = {"train": datasets.Split.TRAIN, "test": datasets.Split.TEST}
-
-    _FEATURES = {
-        "id": datasets.Value("int32"),  # Index of the sample
-        "path": datasets.Value("string"),  # Original path in the dataset
-        "code": datasets.features.Sequence(datasets.Value("string")),  # Code Tokens
-    }
-
-    PYTHON_FILE_MAPPING = dict(train="python100k_train.txt", test="python50k_eval.txt")
-
-    def generate_urls(self, split_name):
-        language = self.info["parameters"]["language"]
-        if language != "python":
-            raise RuntimeError(f"Unknown language {language}")
-
-        yield "data", "https://huggingface.co/datasets/code_x_glue_cc_code_completion_token/resolve/main/data/python/py150_files.zip"
-
-    def process_string(self, token):
-        # Copyright (c) Microsoft Corporation.
-        # Licensed under the MIT License.
-        import re
-
-        str_quote_options = ["'''", '"""', "'", '"']
-        start_quote = ""
-        end_quote = ""
-        qualifier_regex = r"^[a-z]+"
-        qualifier_match = re.search(qualifier_regex, token)
-        # string qualifiers like 'r' for regex, 'f' for formatted string, 'b' for bytes, 'u' for unicode, etc (or combination of them)
-        qualifier = "" if not qualifier_match else qualifier_match[0]
-        # token string without qualifiers
-        token_string = re.sub(qualifier_regex, "", token)
-        # string literal without quotes
-        str_lit = token_string
-        for q in str_quote_options:
-            if token_string.startswith(q):
-                start_quote = q
-                str_lit = str_lit[len(q) :]
-                if token_string.endswith(q):
-                    end_quote = q
-                    str_lit = str_lit[: -len(q)]
-                break
-        if start_quote in str_quote_options[:2]:
-            return ""
-        return (
-            f"{qualifier}{start_quote}{str_lit}{end_quote}"
-            if len(str_lit) < 15
-            and "\n" not in str_lit
-            and "</s>" not in str_lit
-            and "<s>" not in str_lit
-            and "<pad>" not in str_lit
-            and "<EOL>" not in str_lit
-            else f"{qualifier}{start_quote}{end_quote}"
-        )
-
-    def py_tokenize(self, base_dir, file_name):
-        # Copyright (c) Microsoft Corporation.
-        # Licensed under the MIT License.
-        from io import BytesIO
-        from tokenize import COMMENT, ENCODING, ENDMARKER, INDENT, NEWLINE, NL, NUMBER, STRING, tokenize
-
-        file_paths = open(os.path.join(base_dir, file_name), encoding="utf-8").readlines()
-        for ct, path in enumerate(file_paths):
-            try:
-                code = open(os.path.join(base_dir, path.strip()), encoding="utf-8").read()
-                token_gen = tokenize(BytesIO(bytes(code, "utf8")).readline)
-                out_tokens = []
-                prev_eol = False
-                for toknum, tokval, _, _, _ in token_gen:
-                    tokval = " ".join(tokval.split())
-                    if len(tokval) > 100:
-                        continue
-                    if toknum == STRING:
-                        add_token = self.process_string(tokval)
-                        if len(add_token) > 0:
-                            out_tokens.append(add_token)
-                            prev_eol = False
-                    elif toknum == NUMBER:
-                        if len(tokval) < 50:
-                            out_tokens.append(tokval)
-                            prev_eol = False
-                    elif toknum in [NEWLINE, NL]:
-                        if not prev_eol:
-                            out_tokens.append("<EOL>")
-                            prev_eol = True
-                    elif toknum in [COMMENT, INDENT, ENCODING, ENDMARKER] or len(tokval) == 0:
-                        continue
-                    else:
-                        out_tokens.append(tokval)
-                        prev_eol = False
-                if out_tokens[0] == "<EOL>":
-                    out_tokens = out_tokens[1:]
-                if out_tokens[-1] == "<EOL>":
-                    out_tokens = out_tokens[:-1]
-            except Exception:
-                out_tokens = []
-            out_tokens = ["<s>"] + out_tokens + ["</s>"]
-            yield path, out_tokens
-
-    def _generate_examples(self, split_name, file_paths):
-        base_dir = file_paths["data"]
-        filename = self.PYTHON_FILE_MAPPING[split_name]
-
-        idx = 0
-        for entry in self.py_tokenize(base_dir=base_dir, file_name=filename):
-            path, out_tokens = entry
-            path = path[len("data/") :]
-            yield idx, dict(id=idx, path=path, code=out_tokens)
-            idx += 1
-
-
-CLASS_MAPPING = {
-    "CodeXGlueCcCodeCompletionTokenJava": CodeXGlueCcCodeCompletionTokenJavaImpl,
-    "CodeXGlueCcCodeCompletionTokenPython": CodeXGlueCcCodeCompletionTokenPythonImpl,
-}
-
-
-class CodeXGlueCcCodeCompletionToken(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIG_CLASS = datasets.BuilderConfig
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=name, description=info["description"]) for name, info in DEFINITIONS.items()
-    ]
-
-    def _info(self):
-        name = self.config.name
-        info = DEFINITIONS[name]
-        if info["class_name"] in CLASS_MAPPING:
-            self.child = CLASS_MAPPING[info["class_name"]](info)
-        else:
-            raise RuntimeError(f"Unknown python class for dataset configuration {name}")
-        ret = self.child._info()
-        return ret
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        return self.child._split_generators(dl_manager=dl_manager)
-
-    def _generate_examples(self, split_name, file_paths):
-        return self.child._generate_examples(split_name, file_paths)