fix silly issue in dataloader, this version is much faster and more portable to mps too

Author: karpathy

nanochat/dataloader.py

@@ -16,7 +16,6 @@ def tokenizing_distributed_data_loader(B, T, split, tokenizer_threads=4, tokeniz
     bos_token = tokenizer.get_bos_token_id()
     # scratch buffer holds the tokens for one iteration
     token_buffer = deque() # we stream tokens on the right and pop from the left
-    scratch = torch.empty(needed_tokens, dtype=torch.int64, pin_memory=True)
 
     # infinite iterator over document batches
     def document_batches():
@@ -38,8 +37,8 @@ def document_batches():
                 token_buffer.extend(tokens)
             batch_index += 1
         # Move tokens from the deque into the scratch buffer
-        for i in range(needed_tokens):
-            scratch[i] = token_buffer.popleft()
+        tokens = [token_buffer.popleft() for _ in range(needed_tokens)]
+        scratch = torch.tensor(tokens, dtype=torch.int64, pin_memory=True)
         # Create the inputs/targets as 1D tensors
         inputs_cpu = scratch[:-1].to(dtype=torch.int32)
         targets_cpu = scratch[1:]