Update climate-evaluation.py

climate-evaluation.py

@@ -5,6 +5,7 @@ import datasets
 import csv
 import textwrap
 import json
+from pathlib import Path
 
 
 _CITATION = """
@@ -28,6 +29,10 @@ _URL = "https://huggingface.co/datasets/eci-io/climate-evaluation/blob/main/"
 
 _LICENSE = ""
 
+_BASE_HF_URL = Path("./")
+
+print(f"_BASE_HF_URL: {_BASE_HF_URL}")
+
 _ClimateEvaluation_BASE_KWARGS = dict(
     citation=_CITATION,
     url=_HOMEPAGE,
@@ -174,7 +179,7 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
                 """\
                 CDP-QA is a dataset compiled from the questionnaires of the Carbon Disclosure Project, where cities, corporations, and states disclose their environmental information. The dataset presents pairs of questions and answers, and the objective is to predict whether a given answer is valid for the corresponding question. We benchmarked ClimateGPT on the questionnaires from the Combined split. """
             ),
-            data_dir="CDP/Combined/",
+            data_dir="CDP/Combined",
             text_features={"question": "question", "answer": "answer"},
             label_classes=["0", "1"],
             label_column="label",
@@ -315,7 +320,7 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
                     text_feature: datasets.Value("string")
                     for text_feature in self.config.text_features.keys()
                 }
-                features["category"] = datasets.Value("string")
+                # features["category"] = datasets.Value("string")
             else:
                 features = {
                     text_feature: datasets.Value("string")
@@ -342,7 +347,7 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
 
         if self.config.name == "exams" or self.config.name == "translated_exams":
             urls_to_download={
-                "test": _URL + os.path.join(data_dir or "", "test.csv")
+                "test": _BASE_HF_URL / data_dir / f"test.csv"
             }
             downloaded_files = dl_manager.download_and_extract(urls_to_download)
             return [
@@ -357,9 +362,9 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
         
         if self.config.name == "exeter":
             urls_to_download={
-                "train": _URL + data_dir + "training.csv",
-                "valid": _URL + data_dir + "validation.csv",
-                "test": _URL + data_dir + "test.csv"
+                "train": _BASE_HF_URL / data_dir / f"training.csv",
+                "valid": _BASE_HF_URL / data_dir / f"validation.csv",
+                "test": _BASE_HF_URL / data_dir / f"test.csv"
             }
             downloaded_files = dl_manager.download_and_extract(urls_to_download)
             return [
@@ -400,9 +405,9 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
                 ],
             }
             urls_to_download={
-                "train": [_URL+os.path.join(data_dir or "", f) for f in files["train"]], 
-                "valid": [_URL+os.path.join(data_dir or "", f) for f in files["valid"]],
-                "test": [_URL+os.path.join(data_dir or "", f) for f in files["test"]],
+                "train": [_BASE_HF_URL / data_dir / f for f in files["train"]], 
+                "valid": [_BASE_HF_URL / data_dir / f for f in files["valid"]],
+                "test": [_BASE_HF_URL / data_dir / f for f in files["test"]],
             }
             downloaded_files = dl_manager.download_and_extract(urls_to_download)
             return [
@@ -440,11 +445,13 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
             #     "combined": "Combined",
             # }
             urls_to_download={
-                "train": _URL + os.path.join(data_dir or "", "train_qa.csv"),
-                "valid": _URL + os.path.join(data_dir or "", "val_qa.csv"),
-                "test": _URL + os.path.join(data_dir or "", "test_qa.csv")
+                "train": _BASE_HF_URL / data_dir / f"train_qa.csv", 
+                "valid": _BASE_HF_URL / data_dir / f"val_qa.csv", 
+                "test": _BASE_HF_URL / data_dir / f"test_qa.csv" 
             }
             downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+            print(f"downloaded_files: {downloaded_files['train']}")
             
             return [
                 datasets.SplitGenerator(
@@ -483,10 +490,12 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
             ]
         
         urls_to_download={
-                "train": _URL + os.path.join(data_dir or "", "train.csv"),
-                "valid": _URL + os.path.join(data_dir or "", "val.csv"),
-                "test": _URL + os.path.join(data_dir or "", "test.csv")
+                "train": _BASE_HF_URL / data_dir / f"train.csv", #os.path.join(data_dir or "", "train.csv"),
+                "valid": _BASE_HF_URL / data_dir / f"val.csv", #+ os.path.join(data_dir or "", "val.csv"),
+                "test": _BASE_HF_URL / data_dir / f"test.csv", #+ os.path.join(data_dir or "", "test.csv")
             }
+        # print(f"urls_to_download['train']: {urls_to_download['train']}")
+        # print(f"urls_to_download['valid']: {urls_to_download['valid']}")
         downloaded_files = dl_manager.download_and_extract(urls_to_download)
 
         return [
@@ -520,17 +529,24 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
                 yield from self._process_file(file, delimiter="\t", idx=idx)
         elif self.config.name == "cdp_qa":
             idx = iter(range(10000000))
-            for category, file in data_file:
-                yield from self._process_file(file, idx=idx, category=category)
+            print(f"!!!data_file: {data_file}")
+            # for file in data_file:
+            yield from self._process_file(data_file, idx=idx)
         else:
             yield from self._process_file(data_file)
 
     def _process_file(self, data_file, delimiter=",", idx=None, category=None):
+        print(f"data_file: {data_file}")
         with open(data_file, encoding="utf8") as f:
             process_label = self.config.process_label
             label_classes = self.config.label_classes
+            # print(f"self.config.text_features: {self.config.text_features}")
+            # data = f.read()
+            # print(f"data: {data}")
             reader = csv.DictReader(f, delimiter=delimiter, quoting=csv.QUOTE_ALL)
+            # print(f"reader: {reader}")
             for n, row in enumerate(reader):
+                # print(f"row: {row}")
                 example = {
                     feat: row[col] for feat, col in self.config.text_features.items()
                 }
@@ -539,8 +555,8 @@ class ClimateEvaluation(datasets.GeneratorBasedBuilder):
                 else:
                     example["idx"] = n
 
-                if category:
-                    example["category"] = category
+                # if category:
+                #     example["category"] = category
 
                 if self.config.label_column in row:
                     # print(f"self.config.label_column: {self.config.label_column}")