format train.py

minor fix train.py

egs/speech_llm/ASR_LLM/whisper_llm_zh/train.py

@@ -18,18 +18,6 @@
 # limitations under the License.
 """
 Usage:
-# fine-tuning with whisper and Qwen2
-pip install huggingface_hub['cli']
-mkdir -p models/whisper models/qwen
-
-# For aishell fine-tuned whisper model
-huggingface-cli download --local-dir models/whisper    yuekai/icefall_asr_aishell_whisper exp_large_v2/whisper-large-v2-aishell1-epoch-10-avg-6.pt
-# For multi-hans fine-tuned whisper model
-# huggingface-cli download --local-dir models/whisper    yuekai/icefall_asr_multi-hans-zh_whisper v1.1/whisper-large-v2-multi-hans-zh-epoch-3-avg-10.pt
-
-# huggingface-clie download  --local-dir models/qwen     Qwen/Qwen2-7B-Instruct
-huggingface-clie download  --local-dir models/qwen     Qwen/Qwen2-1.5B-Instruct
-
 torchrun --nproc_per_node 8 ./whisper_llm_zh/train.py \
   --max-duration 200 \
   --exp-dir ./whisper_llm_zh/exp_test \
@@ -39,7 +27,8 @@ torchrun --nproc_per_node 8 ./whisper_llm_zh/train.py \
   --deepspeed \
   --deepspeed_config ./whisper_llm_zh/ds_config_zero1.json \
   --use-flash-attn True \
-  --use-lora True --unfreeze-llm True
+  --use-lora True \
+  --unfreeze-llm True
 """
 
 import argparse
@@ -333,7 +322,6 @@ def compute_loss(
     feature = feature.to(device)
     feature = feature.transpose(1, 2)  # (N, C, T)
 
-    batch_idx_train = params.batch_idx_train
     supervisions = batch["supervisions"]
     texts = batch["supervisions"]["text"]
 
@@ -378,7 +366,7 @@ def compute_loss(
 
 def compute_validation_loss(
     params: AttributeDict,
-    tokenizer: whisper.tokenizer.Tokenizer,
+    tokenizer: AutoTokenizer,
     model: nn.Module,
     valid_dl: torch.utils.data.DataLoader,
     world_size: int = 1,