python file fixed

PEYMA.py

@@ -0,0 +1,128 @@
+import json
+import datasets
+import os
+
+_CITATION = """\\
+@article{shahshahani2018peyma,
+    title={PEYMA: A Tagged Corpus for Persian Named Entities},
+    author={Mahsa Sadat Shahshahani and Mahdi Mohseni and Azadeh Shakery and Heshaam Faili},
+    year=2018,
+    journal={ArXiv},
+    volume={abs/1801.09936}
+}
+"""
+_DESCRIPTION = """PEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes."""
+
+_DATA_PATH = {
+  'train': os.path.join('PEYMA', 'data', 'train.txt'),
+  'test': os.path.join('PEYMA', 'data', 'test.txt'),
+  'val': os.path.join('PEYMA', 'data', 'dev.txt')
+}
+
+class PEYMAConfig(datasets.BuilderConfig):
+    """BuilderConfig for PEYMA."""
+    def __init__(self, **kwargs):
+        super(PEYMAConfig, self).__init__(**kwargs)
+
+
+class PEYMA(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        PEYMAConfig(name="PEYMA", version=datasets.Version("1.0.0"), description="persian ner dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                "tokens": datasets.Sequence(datasets.Value("string")),
+                "tags": datasets.Sequence(
+                    datasets.ClassLabel(
+                        names=[
+                          "O",
+                          "B_DAT",
+                          "B_LOC",
+                          "B_MON",
+                          "B_ORG",
+                          "B_PCT",
+                          "B_PER",
+                          "B_TIM",
+                          "I_DAT",
+                          "I_LOC",
+                          "I_MON",
+                          "I_ORG",
+                          "I_PCT",
+                          "I_PER",
+                          "I_TIM",
+                          ]
+                    )
+                ),
+                }
+            ),
+            supervised_keys=('tokens', 'tags'),
+            # Homepage of the dataset for documentation
+            homepage="https://hooshvare.github.io/docs/datasets/ner#peyma",
+            citation=_CITATION,
+        )
+        
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        return [
+                datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": _DATA_PATH["train"],
+                    "split": "train",
+                },),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": _DATA_PATH["test"], 
+                        "split": "test"},),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": _DATA_PATH["val"],
+                        "split": "validation",
+                    },
+                ),    
+                ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, "r", encoding="utf-8") as f:
+            id_ = 0
+            tokens = []
+            ner_labels = []
+            for line in f:
+                stripped_line = line.strip(" \n")  # strip away whitespaces AND new line characters
+                if len(stripped_line) == 0:
+                    # If line is empty, it means we reached the end of a sentence.
+                    # We can yield the tokens and labels
+                    if len(tokens) > 0 and len(ner_labels) > 0:
+                        yield id_, {
+                            "tokens": tokens,
+                            "tags": ner_labels,
+                        }
+                    else:
+                        # Do not yield if tokens or ner_labels is empty
+                        # It can be the case if several empty lines are contiguous
+                        continue
+                    # Then we need to increment the _id and reset the tokens and ner_labels list
+                    id_ += 1
+                    tokens = []
+                    ner_labels = []
+                else:
+                  try:
+                    token, ner_label = line.split("|")  # Retrieve token and label
+                    tokens.append(token)
+                    ner_labels.append(ner_label)
+                  except:
+                    continue
+                
+
+

README.md

@@ -1,3 +1,39 @@
 ---
 license: apache-2.0
+dataset_info:
+  config_name: PEYMA
+  features:
+  - name: tokens
+    sequence: string
+  - name: tags
+    sequence:
+      class_label:
+        names:
+          '0': O
+          '1': B_DAT
+          '2': B_LOC
+          '3': B_MON
+          '4': B_ORG
+          '5': B_PCT
+          '6': B_PER
+          '7': B_TIM
+          '8': I_DAT
+          '9': I_LOC
+          '10': I_MON
+          '11': I_ORG
+          '12': I_PCT
+          '13': I_PER
+          '14': I_TIM
+  splits:
+  - name: train
+    num_bytes: 4885030
+    num_examples: 8028
+  - name: test
+    num_bytes: 648919
+    num_examples: 1026
+  - name: validation
+    num_bytes: 535910
+    num_examples: 925
+  download_size: 0
+  dataset_size: 6069859
 ---