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import pickle
from BPE import get_stats, merge
import regex as re
# Load merges and vocab from the file
with open('bpe_results.pkl', 'rb') as f:
merges, ids, num_merges = pickle.load(f)
# Define the GPT-2 regex pattern (same as in BPE.py)
gpt2pat = re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""")
vocab = {idx: bytes([idx]) for idx in range(256)}
for (p0, p1), idx in merges.items():
vocab[idx] = vocab[p0] + vocab[p1]
def decode(ids):
# given ids (list of integers), return Python string
tokens = [vocab[idx] for idx in ids]
# Decode each token separately and join with tabs
decoded_tokens = [token.decode("utf-8", errors="replace") for token in tokens]
text = '\t'.join(decoded_tokens)
# Write the decoded text to a new file
with open('decoded_output.txt', 'w', encoding='utf-8') as f:
f.write(text)
return text
# Example: Decode a list of IDs
set_of_ids = [1072, 415, 308, 1406, 103, 279, 999, 260, 550, 46, 301, 39, 299, 1076, 1172, 562, 284, 111, 414, 1460, 46, 301, 116, 373, 308, 259, 562, 798, 832, 1460, 1449, 44, 892, 415, 308, 311, 112, 112, 549, 46]
decoded_text = decode(set_of_ids) # Pass the list of IDs
print(decoded_text)
def encode():
# Read input text from a new file
with open('encode_input.txt', 'r', encoding='utf-8') as f:
text = f.read()
# Tokenize the text using the regex pattern
tokens = re.findall(gpt2pat, text)
# Convert tokens to byte sequences and maintain grouping
byte_tokens = [token.encode('utf-8') for token in tokens]
token_list = [list(token) for token in byte_tokens]
# Process each token
final_tokens = []
for token in token_list:
current_token = list(token)
while len(current_token) >= 2:
stats = get_stats([current_token])
if not stats:
break
pair = min(stats, key=lambda p: merges.get(p, float("inf")))
if pair not in merges:
break
idx = merges[pair]
current_token = merge([current_token], pair, idx)[0]
final_tokens.extend(current_token)
return final_tokens
# Example: Encode text from a file
encoded_tokens = encode()
print(encoded_tokens) |