Delete outputs/dataset.py

outputs/dataset.py

@@ -1,50 +0,0 @@
-import csv
-from torch.utils.data import IterableDataset
-from huggingface_hub import hf_hub_download
-
-class ParsedMultiCharDataset(IterableDataset):
-    def __init__(self, 
-                 repo_id: str, 
-                 delimiter: str = ".,|,.",
-                 start_file: int = 0, 
-                 num_files: int = 190,
-                 guess_total_count = True):
-        self.repo_id = repo_id
-        self.files = [f"captions/caption_{i+start_file:03d}.csv" for i in range(num_files)]
-        self.delimiter = ".,|,."
-        self.total_rows = -1
-        if guess_total_count:
-            self.total_rows = self.guess_total_rows()
-            print(f"Total rows: {self.total_rows} totaling {len(self.files) * self.total_rows}")
-
-
-    def guess_total_rows(self):
-      # count the rows in the first file
-      path = hf_hub_download(self.repo_id, self.files[0], repo_type="dataset")
-      with open(path, encoding="utf-8") as f:
-          reader = csv.DictReader(f)
-          return sum(1 for _ in reader)
-
-    def __iter__(self):
-        for rel_path in self.files:
-            path = hf_hub_download(self.repo_id, rel_path, repo_type="dataset")
-            with open(path, encoding="utf-8") as f:
-                reader = csv.DictReader(f)
-                for row in reader:
-                    id_ = row.get("id", "").strip()
-                    text_field = row.get("text", "")
-                    for caption in text_field.split(self.delimiter):
-                        caption = caption.strip()
-                        if caption:
-                            yield (id_, caption)
-
-#ds = ParsedMultiCharDataset(
-#    repo_id="AbstractPhil/human-templated-captions-1b",
-#    start_file=0,
-#    num_files=10
-#)
-#for i, ex in enumerate(ds):
-#    print(ex)
-#    if i > 10:
-#        break
-#