loading files

childes_data.py

@@ -0,0 +1,112 @@
+# The majority of this file was taken and adapted from this file, on 6/3/21: https://github.com/huggingface/datasets/blob/master/datasets/snli/snli.py
+
+
+# License reproduced from the original code:
+
+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+# The changes to the file include:
+# Changing all of the parameters to reflect childes data and information
+# Changing the dl_manager to be essentially unused in split_generators and loading from text files instead
+# Changing generate_examples to load directly from text files and clean the lines of text.
+
+
+import datasets
+import os
+
+class Childes(datasets.GeneratorBasedBuilder):
+     
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="childes_data",
+            version=datasets.Version("1.0.0", ""),
+            description="Childes language modeling dataset",
+        )
+    ]
+    
+
+    
+    def _info(self):
+        
+        citation_text = """\\
+@article{sanchez2019childes,
+    title={childes-db: A flexible and reproducible interface to the child language data exchange system},
+    author={Sanchez, Alessandro and Meylan, Stephan C and Braginsky, Mika and MacDonald, Kyle E and Yurovsky, Daniel and Frank, Michael C},
+    journal={Behavior research methods},
+    volume={51},
+    number={4},
+    pages={1928--1941},
+    year={2019},
+    publisher={Springer}}
+    """
+            
+            
+        return datasets.DatasetInfo(
+            description = "CHILDES data for language modeling",
+            citation = citation_text,
+            # 6/3 Citation info is directly taken from Google Scholar
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            homepage="https://childes-db.stanford.edu/",
+        )
+    
+    
+    def _split_generators(self, download_helper):
+        
+        paths = {
+            'train' : 'https://www.dropbox.com/s/dl/i282barrzlari08/train.txt?dl=1',
+            'val' : 'https://www.dropbox.com/s/gx0rngo3v5mvlcf/validation.txt?dl=1',
+        }
+        
+        list_datasets = []
+        
+        phases = ['train', 'val']
+        dataset_names = [
+            datasets.Split.TRAIN,
+            datasets.Split.VALIDATION,
+        ]
+        
+        for phase, phase_name in zip(phases, dataset_names):
+            
+            path = paths[phase]
+            this_true_path = download_helper.download_and_extract(path)
+            
+            this_dataset = datasets.SplitGenerator(
+                name=phase_name, gen_kwargs={"file_path": this_true_path}
+            )
+            
+            list_datasets.append(this_dataset)
+            
+        
+        return list_datasets
+    
+    def _generate_examples(self, file_path):
+        
+        clean_text = lambda s : s.strip('\
+').strip('[CHI] ')
+        
+        with open(file_path, 'r') as f:
+            for idx, line in enumerate(map(clean_text, f.readlines())):
+                yield idx, {"text" : line}
+                
+                
+