diff options
Diffstat (limited to 'data/shakespeare/prepare.py')
| -rw-r--r-- | data/shakespeare/prepare.py | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/data/shakespeare/prepare.py b/data/shakespeare/prepare.py new file mode 100644 index 0000000..bda25b1 --- /dev/null +++ b/data/shakespeare/prepare.py @@ -0,0 +1,33 @@ +import os +import requests +import tiktoken +import numpy as np + +# download the tiny shakespeare dataset +input_file_path = os.path.join(os.path.dirname(__file__), 'input.txt') +if not os.path.exists(input_file_path): + data_url = 'https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt' + with open(input_file_path, 'w', encoding='utf-8') as f: + f.write(requests.get(data_url).text) + +with open(input_file_path, 'r', encoding='utf-8') as f: + data = f.read() +n = len(data) +train_data = data[:int(n*0.9)] +val_data = data[int(n*0.9):] + +# encode with tiktoken gpt2 bpe +enc = tiktoken.get_encoding("gpt2") +train_ids = enc.encode_ordinary(train_data) +val_ids = enc.encode_ordinary(val_data) +print(f"train has {len(train_ids):,} tokens") +print(f"val has {len(val_ids):,} tokens") + +# export to bin files +train_ids = np.array(train_ids, dtype=np.uint16) +val_ids = np.array(val_ids, dtype=np.uint16) +train_ids.tofile(os.path.join(os.path.dirname(__file__), 'train.bin')) +val_ids.tofile(os.path.join(os.path.dirname(__file__), 'val.bin')) + +# train.bin has 301,966 tokens +# val.bin has 36,059 tokens |
