Add dataset deduplication

deduplicate.py

@@ -0,0 +1,63 @@
+# adapted from: https://github.com/huggingface/transformers/blob/master/examples/research_projects/codeparrot/scripts/preprocessing.py
+
+import datasets
+
+def get_hash(example):
+    """Get hash of text field."""
+    return {"hash": hash(example["text"])}
+
+def check_uniques(example, uniques):
+    """Check if current hash is still in set of unique hashes and remove if true."""
+    if example["hash"] in uniques:
+        uniques.remove(example["hash"])
+        return True
+    else:
+        return False
+
+def filter(example, uniques):
+    """Filter dataset with unique values."""
+    if not check_uniques(example, uniques):
+        return False
+    else:
+        return True
+
+dataset = datasets.load_dataset("csv", data_files={"train": "train.csv", "validation": "valid.csv"})
+
+# TRAIN SPLIT DEDUPLICATION
+
+len_train = len(dataset["train"])
+print(f"Size of original dataset train: {len_train}")
+
+dataset["train"] = dataset["train"].map(get_hash, num_proc=64, writer_batch_size=100000)
+
+# Deduplicate hashes
+uniques = set(dataset["train"].unique("hash"))
+frac = len(uniques) / len(dataset["train"])
+print(f"Fraction of duplicates: {1-frac:.2%}")
+
+# Deduplicate data
+dataset_train_deduplicated = dataset["train"].filter(filter, fn_kwargs={"uniques": uniques})
+print(f"Size of filtered dataset train: {len(dataset_train_deduplicated)}")
+
+# VALIDATION SPLIT DEDUPLICATION
+
+len_val = len(dataset["validation"])
+print(f"Size of original dataset valid: {len_val}")
+
+dataset["validation"] = dataset["validation"].map(get_hash, num_proc=64, writer_batch_size=100000)
+
+# Deduplicate hashes
+uniques = set(dataset["validation"].unique("hash"))
+frac = len(uniques) / len(dataset["validation"])
+print(f"Fraction of duplicates: {1-frac:.2%}")
+
+# Deduplicate data
+dataset_valid_deduplicated = dataset["validation"].filter(filter, fn_kwargs={"uniques": uniques})
+print(f"Size of filtered dataset valid: {len(dataset_valid_deduplicated)}")
+
+# SAVE DEDUPLICATED DATASET
+dataset_train_deduplicated = dataset_train_deduplicated.remove_columns(["hash"])
+dataset_valid_deduplicated = dataset_valid_deduplicated.remove_columns(["hash"])
+
+dataset_train_deduplicated.to_csv("train.csv", num_proc=64, index=False)
+dataset_valid_deduplicated.to_csv("valid.csv", num_proc=64, index=False)

train.csv

@@ -1,3 +1,3 @@
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-size 64564250147
+oid sha256:857db09dc9d10a5606768ff8885d6fe1162f5dbbbb2aa82977278499530a3fd9
+size 64553318366

valid.csv

@@ -1,3 +1,3 @@
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-oid sha256:59f60f38dec64cb813103f43e64d7aab1736a27ea79693438730ff3e78c30472
-size 63930699
+oid sha256:816cb816f2f002e158bba01e19eee6cec58d18a37919f1284de45decbe331289
+size 63928522