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Fix issue 724: unused args (#726)

* Fix issue 724: unused args

* Update 02_opt_multi_gpu_ddp.py
Matthew Hernandez 4 ヶ月 前
コミット
83c76891fc

+ 1 - 1
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)
 

+ 1 - 4
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

+ 1 - 2
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()