Update fs.py

fs.py

@@ -6,7 +6,7 @@ import json
 import os
 import datasets
 from datasets import load_dataset
-from transformers import AutoTokenizer
+from transformers import AutoTokenizer # TODO comment out when getting rid of __main__:
 
 _FS_CITATION = """
 TBD
@@ -66,7 +66,7 @@ _GOV_REPORT_CITATION = r"""
 class FSConfig(datasets.BuilderConfig):
     """BuilderConfig for FS."""
 
-    def __init__(self, features, data_url, citation, url, max_source_length, tokenizer, **kwargs):
+    def __init__(self, features, data_url, citation, url, max_source_length, tokenizer,prompt, **kwargs):
         """BuilderConfig for FS.
         Args:
           features: `list[string]`, list of the features that will appear in the
@@ -86,12 +86,13 @@ class FSConfig(datasets.BuilderConfig):
         self.url = url
         self.max_source_length = max_source_length
         self.tokenizer = tokenizer
+        self.prompt = prompt
 
 
 class Fs(datasets.GeneratorBasedBuilder):
     """The SCROLLS benchmark."""
 
-    features = ["id", "pid", "input", "output", "source", "target"]
+    features = ["id", "pid", "input", "output"]
     DEFAULT_WRITER_BATCH_SIZE = 1000  # because Narrative QA is a rather large dataset
     BUILDER_CONFIGS = [
         FSConfig(
@@ -103,6 +104,7 @@ class Fs(datasets.GeneratorBasedBuilder):
             url="https://github.com/mingdachen/SummScreen",
             max_source_length=None,
             tokenizer=None,
+            prompt=None
         ),
         FSConfig(
             name="gov_report",
@@ -113,6 +115,7 @@ class Fs(datasets.GeneratorBasedBuilder):
             url="https://gov-report-data.github.io/",
             max_source_length=None,
             tokenizer=None,
+            prompt=None
         ),
     ]
 
@@ -141,6 +144,7 @@ class Fs(datasets.GeneratorBasedBuilder):
                     "data_file": os.path.join(dl_dir, "train.jsonl"),
                     "split": datasets.Split.TRAIN,
                     "max_source_length": self.config.max_source_length,
+                    "prompt": self.config.prompt,
                     "tokenizer": self.config.tokenizer,
                 },
             ),
@@ -150,6 +154,7 @@ class Fs(datasets.GeneratorBasedBuilder):
                     "data_file": os.path.join(dl_dir, "validation.jsonl"),
                     "split": datasets.Split.VALIDATION,
                     "max_source_length": self.config.max_source_length,
+                    "prompt": self.config.prompt,
                     "tokenizer": self.config.tokenizer,
                 },
             ),
@@ -159,6 +164,7 @@ class Fs(datasets.GeneratorBasedBuilder):
                     "data_file": os.path.join(dl_dir, "test.jsonl") if data_files is None else data_files["test"],
                     "split": datasets.Split.TEST,
                     "max_source_length": self.config.max_source_length,
+                    "prompt": self.config.prompt,
                     "tokenizer": self.config.tokenizer,
                 },
             ),
@@ -168,25 +174,21 @@ class Fs(datasets.GeneratorBasedBuilder):
         with open(data_file, encoding="utf-8") as f:
             for line in f:
                 row = json.loads(line)
+                prefix = row["source"].strip()
+                suffix = "\n" + self.config.prompt
+                encoded_input = tokenizer.encode(prefix + suffix)
 
-                prefix, addition = row["source"].strip(), "Summary:"
-                encoded_input = tokenizer.encode(prefix + "\n" + addition)
-                input_length = len(encoded_input)
-                
                 n_truncations = 0
-                while input_length > max_source_length:
-                    overflow = input_length - max_source_length
+                while len(encoded_input) > max_source_length:
+                    overflow = len(encoded_input) - max_source_length
                     tokenized_prefix = tokenizer.encode(prefix, add_special_tokens=False)
                     if overflow > 0:
                         tokenized_prefix = tokenized_prefix[:-overflow]
                     n_truncations += 1
                     prefix = tokenizer.decode(tokenized_prefix, skip_special_tokens=False).strip()
-                    encoded_input = tokenizer.encode(prefix + "\n" + addition)
-                    input_length = len(encoded_input)
-                    
-                valid_input = prefix + "\n" + addition
+                    encoded_input = tokenizer.encode(prefix + suffix)
 
-                row["input"] = valid_input
+                row["input"] = prefix + suffix
                 row["output"] = row["target"]
 
                 yield row["pid"], row
@@ -198,10 +200,9 @@ def _get_task_name_from_data_url(data_url):
 
 if __name__ == '__main__':
     tokenizer = AutoTokenizer.from_pretrained("t5-base")
-    dataset = load_dataset("tau/fs", "summ_screen_fd", max_source_length=512, tokenizer=tokenizer)
+    dataset = load_dataset("tau/fs",name="summ_screen_fd", max_source_length=512, tokenizer=tokenizer, prompt="Summary:")
     x = 5
 #    builder = Scrolls("scrolls", "summ_screen_fd")
 #    builder.download_and_prepare()
 #    dataset = builder.as_dataset("validation")
-#    x = 5
-
+#    x = 5