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import torch
with open("data/input.txt") as f:
text = f.read()
chars = sorted(list(set(text)))
vocab_size = len(chars)
stoi = {ch: i for i, ch in enumerate(chars)}
itos = {i: ch for i, ch in enumerate(chars)}
def encode(s):
return [stoi[c] for c in s]
def decode(l):
return "".join([itos[i] for i in l])
data = torch.tensor(encode(text), dtype=torch.long)
n = int(0.9 * len(data))
train_data = data[:n]
val_data = data[n:]
def get_batch(split, block_size, batch_size):
data = train_data if split == "train" else val_data
ix = torch.randint(len(data) - block_size, (batch_size,))
x = torch.stack([data[i : i + block_size] for i in ix])
y = torch.stack([data[i + 1 : i + block_size + 1] for i in ix])
return x, y
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