Apply isort and black reformatting

Signed-off-by: DongjiGao <DongjiGao@users.noreply.github.com>

Author: DongjiGao

nemo/collections/speechlm2/vllm/nemotron_v3/__init__.py

@@ -123,9 +123,5 @@ def _patch_tokenizer_thread_safety():
     if hasattr(PreTrainedTokenizerFast, "_orig_batch_encode_plus"):
         return  # already patched
 
-    PreTrainedTokenizerFast._orig_batch_encode_plus = (
-        PreTrainedTokenizerFast._batch_encode_plus
-    )
-    PreTrainedTokenizerFast._batch_encode_plus = (
-        _thread_safe_batch_encode_plus
-    )
+    PreTrainedTokenizerFast._orig_batch_encode_plus = PreTrainedTokenizerFast._batch_encode_plus
+    PreTrainedTokenizerFast._batch_encode_plus = _thread_safe_batch_encode_plus

nemo/collections/speechlm2/vllm/nemotron_v3/config.py

@@ -23,10 +23,12 @@
 
 from transformers import AutoConfig, PretrainedConfig
 
-_HYBRID_ARCHITECTURES = frozenset({
-    "NemotronHForCausalLM",
-    "NemotronHybridForCausalLM",
-})
+_HYBRID_ARCHITECTURES = frozenset(
+    {
+        "NemotronHForCausalLM",
+        "NemotronHybridForCausalLM",
+    }
+)
 
 # Number of extra embedding rows the SpeechLM adds on top of the backbone's
 # native vocab during training: ``<|audio|>`` locator plus headroom for other
@@ -70,9 +72,7 @@ def __init__(
         self.pretrained_weights = pretrained_weights
         self.lora = lora
 
-        self.text_config = AutoConfig.from_pretrained(
-            pretrained_llm, trust_remote_code=True
-        )
+        self.text_config = AutoConfig.from_pretrained(pretrained_llm, trust_remote_code=True)
 
         raw_archs = getattr(self.text_config, "architectures", [])
         if len(raw_archs) != 1:
@@ -91,17 +91,10 @@ def __init__(
             # downstream ``init_vllm_registered_model(architectures=...)`` call
             # that threads this text_config through resolves correctly.
             self.text_config.architectures = ["NemotronHForCausalLM"]
-            if (
-                not hasattr(self.text_config, "total_num_kv_heads")
-                or self.text_config.total_num_kv_heads is None
-            ):
-                self.text_config.total_num_kv_heads = getattr(
-                    self.text_config, "num_key_value_heads", 2
-                )
+            if not hasattr(self.text_config, "total_num_kv_heads") or self.text_config.total_num_kv_heads is None:
+                self.text_config.total_num_kv_heads = getattr(self.text_config, "num_key_value_heads", 2)
             if not hasattr(self.text_config, "rms_norm_eps"):
-                self.text_config.rms_norm_eps = getattr(
-                    self.text_config, "layer_norm_epsilon", 1e-5
-                )
+                self.text_config.rms_norm_eps = getattr(self.text_config, "layer_norm_epsilon", 1e-5)
 
         self.text_config.vocab_size += _SPEECHLM_EMBED_EXTRA_ROWS
 
@@ -156,6 +149,4 @@ def __getattr__(self, name):
                     return getattr(self.text_config, name)
                 except AttributeError:
                     pass
-            raise AttributeError(
-                f"'{type(self).__name__}' has no attribute '{name}'"
-            )
+            raise AttributeError(f"'{type(self).__name__}' has no attribute '{name}'")