import os | |
import json | |
import random | |
import pandas as pd | |
DATA_DIR = f"/home/{os.environ['USER']}/data/wit/all_jsons" | |
SEED = 0 | |
PROPORTION_TRAIN = 0.98 | |
PROPORTION_VALID = 0.01 | |
random.seed(SEED) | |
all_files = [f"{DATA_DIR}/{file_}" for file_ in os.listdir(DATA_DIR) if ("all" not in file_)] | |
print(all_files) | |
examples = [] | |
for file_ in all_files: | |
print(file_) | |
with open(file_) as f: | |
file_examples = [json.dumps(json.loads(line), ensure_ascii=False) for line in f.readlines()] | |
print(len(file_examples)) | |
examples.extend(file_examples) | |
print(f"Before dedup: {len(examples)}") | |
examples = list(set(examples)) | |
print(f"After dedup: {len(examples)}") | |
print(examples[0]) | |
# Shuffle examples | |
random.shuffle(examples) | |
print(examples[0]) | |
split_dataset = {} | |
split_dataset["train"] = examples[:int(len(examples) * PROPORTION_TRAIN)] | |
split_dataset["valid"] = examples[int(len(examples) * PROPORTION_TRAIN): int(len(examples) * (PROPORTION_TRAIN + PROPORTION_VALID))] | |
split_dataset["test"] = examples[int(len(examples) * (PROPORTION_TRAIN + PROPORTION_VALID)):] | |
for split in ["train", "valid", "test"]: | |
print("-----") | |
print(len(split_dataset[split])) | |
print("-----") | |
with open(f"/home/{os.environ['USER']}/data/wit/all_jsons/{split}_dataset_all_98_1_1_split.json", "w") as f: | |
f.write("\n".join(split_dataset[split])) | |