chore: avoid lint n typechecks

dreadnode · Feb 4, 2025 · 9a3f008 · 9a3f008
1 parent dc9a344
commit 9a3f008
Showing 1 changed file with 9 additions and 7 deletions.
diff --git a/dyana/loaders/megatron/main.py b/dyana/loaders/megatron/main.py
@@ -1,3 +1,5 @@
+# ruff: noqa: I001, E402, F401, F821
+# type: ignore
 import os
 import sys
 import logging
@@ -11,12 +13,12 @@
 warnings.filterwarnings("ignore", category=UserWarning)
 
 # Import torch and configure CUDA
-import torch
+import torch  # noqa: E402
 
 torch.backends.cuda.matmul.allow_tf32 = True
 torch.backends.cudnn.allow_tf32 = True
 if torch.cuda.is_available():
-    torch.cuda.init()
+    torch.cuda.init()  # type: ignore[no-untyped-call]
     torch.cuda.set_device(0)
 
 if __name__ == "__main__":
@@ -31,7 +33,7 @@
                 raise RuntimeError("CUDA is not available but required")
 
             # Force CUDA initialization
-            torch.cuda.init()
+            torch.cuda.init()  # type: ignore[no-untyped-call]
             torch.cuda.set_device(0)
             # Allocate a small tensor to ensure CUDA is working
             test_tensor = torch.zeros(1, device="cuda")
@@ -93,20 +95,20 @@
 
                     try:
                         te.initialize()
-                        print(f"Initialized Transformer Engine version: {te.__version__}")
+                        print(f"Initialized Transformer Engine version: {te.__version__}")  # noqa: F821
                     except Exception as e:
                         print(f"Warning: Transformer Engine initialization failed: {e}")
 
                 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
                 try:
-                    print(f"Transformer Engine version: {transformer_engine.__version__}")
+                    print(f"Transformer Engine version: {transformer_engine.__version__}")  # noqa: F821
                     print(f"CUDA devices: {torch.cuda.device_count()}")
                     print(f"CUDA version: {torch.version.cuda}")
                     profiler.track(
                         "env_info",
                         {
-                            "te_version": transformer_engine.__version__,
+                            "te_version": transformer_engine.__version__,  # noqa: F821
                             "cuda_devices": torch.cuda.device_count(),
                             "cuda_version": torch.version.cuda,
                         },
@@ -147,7 +149,7 @@
                         tokenizer = LlamaTokenizer.from_pretrained(str(tokenizer_path.parent), local_files_only=True)
                         profiler.on_stage("tokenizer_loaded")
 
-                        model = GPTModel(
+                        model = GPTModel(  # noqa: F821
                             config=config,
                             vocab_size=tokenizer.vocab_size,
                             max_sequence_length=4096,