diff --git a/ch02/05_bpe-from-scratch/tests/tests.py b/ch02/05_bpe-from-scratch/tests/tests.py index 97ee010..4ed2a16 100644 --- a/ch02/05_bpe-from-scratch/tests/tests.py +++ b/ch02/05_bpe-from-scratch/tests/tests.py @@ -58,7 +58,7 @@ def gpt2_files(imported_module): return paths -def test_tokenizer_training(imported_module, gpt2_files): +def test_tokenizer_training(imported_module): BPETokenizerSimple = getattr(imported_module, "BPETokenizerSimple", None) download_file_if_absent = getattr(imported_module, "download_file_if_absent", None) diff --git a/ch05/10_llm-training-speed/02_opt_multi_gpu_ddp.py b/ch05/10_llm-training-speed/02_opt_multi_gpu_ddp.py index 29db397..746cc7f 100644 --- a/ch05/10_llm-training-speed/02_opt_multi_gpu_ddp.py +++ b/ch05/10_llm-training-speed/02_opt_multi_gpu_ddp.py @@ -312,7 +312,7 @@ def generate_and_print_sample(model, device, start_context): def train_model_simple_with_timing(model, train_loader, val_loader, optimizer, device, - num_epochs, eval_freq, eval_iter, start_context, tokenizer): + num_epochs, eval_freq, eval_iter, start_context): train_losses, val_losses, track_tokens = [], [], [] total_tokens, global_step, last_tokens = 0, -1, 0 @@ -524,8 +524,6 @@ def main(gpt_config, settings, rank, world_size): # Train model ############################## - tokenizer = tiktoken.get_encoding("gpt2") - train_losses, val_losses, tokens_seen = train_model_simple_with_timing( model=model, train_loader=train_loader, @@ -536,7 +534,6 @@ def main(gpt_config, settings, rank, world_size): eval_freq=5, eval_iter=1, start_context="Every effort moves you", - tokenizer=tokenizer ) # NEW: Clean up distributed processes diff --git a/ch06/01_main-chapter-code/gpt_class_finetune.py b/ch06/01_main-chapter-code/gpt_class_finetune.py index 8308304..239f374 100644 --- a/ch06/01_main-chapter-code/gpt_class_finetune.py +++ b/ch06/01_main-chapter-code/gpt_class_finetune.py @@ -175,7 +175,7 @@ def evaluate_model(model, train_loader, val_loader, device, eval_iter): def train_classifier_simple(model, train_loader, val_loader, optimizer, device, num_epochs, - eval_freq, eval_iter, tokenizer): + eval_freq, eval_iter): # Initialize lists to track losses and tokens seen train_losses, val_losses, train_accs, val_accs = [], [], [], [] examples_seen, global_step = 0, -1 @@ -408,7 +408,6 @@ if __name__ == "__main__": train_losses, val_losses, train_accs, val_accs, examples_seen = train_classifier_simple( model, train_loader, val_loader, optimizer, device, num_epochs=num_epochs, eval_freq=50, eval_iter=5, - tokenizer=tokenizer ) end_time = time.time()