[Bugfix] Remove duplicated config keyword max batch size (#1851)

Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
Signed-off-by: Zhou Taichang <tzhouam@connect.ust.hk>

docs/user_guide/examples/offline_inference/bagel.md

@@ -130,7 +130,7 @@ The default yaml configuration deploys Thinker and DiT on the same GPU. You can
 | :------------------------------- | :------------------------------ | :----------------------- |
 | `stage_type`                     | `llm`                           | Stage type               |
 | `devices`                        | `"0"`                           | GPU device ID            |
-| `max_batch_size`                 | `1`                             | Maximum batch size       |
+| `max_num_seqs`                   | `1`                             | Maximum batch size       |
 | `model_stage`                    | `thinker`                       | Model stage identifier   |
 | `model_arch`                     | `BagelForConditionalGeneration` | Model architecture       |
 | `gpu_memory_utilization`         | `0.4`                           | GPU memory utilization   |
@@ -146,7 +146,7 @@ The default yaml configuration deploys Thinker and DiT on the same GPU. You can
 | :------------------------------- | :---------- | :-------------------------- |
 | `stage_type`                     | `diffusion` | Stage type                  |
 | `devices`                        | `"0"`       | GPU device ID               |
-| `max_batch_size`                 | `1`         | Maximum batch size          |
+| `max_num_seqs`                   | `1`         | Maximum batch size          |
 | `model_stage`                    | `dit`       | Model stage identifier      |
 | `gpu_memory_utilization`         | `0.4`       | GPU memory utilization      |
 | `omni_kv_config.need_recv_cache` | `true`      | Whether to receive KV cache |

docs/user_guide/examples/offline_inference/qwen3_tts.md

@@ -107,7 +107,7 @@ completes. This demonstrates that audio data is available progressively rather t
 
 ## Batched Decoding
 
-The Code2Wav stage (stage 1) supports batched decoding, where multiple requests are decoded in a single forward pass through the SpeechTokenizer. To use it, provide a stage config with `max_batch_size > 1` and pass multiple prompts via `--txt-prompts` with a matching `--batch-size`.
+The Code2Wav stage (stage 1) supports batched decoding, where multiple requests are decoded in a single forward pass through the SpeechTokenizer. To use it, provide a stage config with `max_num_seqs > 1` and pass multiple prompts via `--txt-prompts` with a matching `--batch-size`.
 
 ```
 python end2end.py --query-type CustomVoice \
@@ -116,7 +116,7 @@ python end2end.py --query-type CustomVoice \
     --stage-configs-path vllm_omni/model_executor/stage_configs/qwen3_tts_batch.yaml
 ```
 
-**Important:** `--batch-size` must match a CUDA graph capture size (1, 2, 4, 8, 16...) because the Talker's code predictor KV cache is sized to `max_num_seqs`, and CUDA graphs pad the batch to the next capture size. Both stages need `max_batch_size >= batch_size` in the stage config for batching to take effect. If only stage 1 has a higher `max_batch_size`, it won't help — stage 1 can only batch chunks from requests that are in-flight simultaneously, which requires stage 0 to also process multiple requests concurrently.
+**Important:** `--batch-size` must match a CUDA graph capture size (1, 2, 4, 8, 16...) because the Talker's code predictor KV cache is sized to `max_num_seqs`, and CUDA graphs pad the batch to the next capture size. Both stages need `max_num_seqs >= batch_size` in the stage config for batching to take effect. If only stage 1 has a higher `max_num_seqs`, it won't help — stage 1 can only batch chunks from requests that are in-flight simultaneously, which requires stage 0 to also process multiple requests concurrently.
 
 ## Notes
 

docs/user_guide/examples/offline_inference/text_to_image.md

@@ -49,7 +49,7 @@ if __name__ == "__main__":
 
 !!! info
 
-    For diffusion pipelines, the stage config field `stage_args.[].runtime.max_batch_size` is 1 by default, and the input
+    For diffusion pipelines, the stage config field `stage_args.[].engine_args.max_num_seqs` is 1 by default, and the input
     list is sliced into single-item requests before feeding into the diffusion pipeline. For models that do internally support
     batched inputs, you can [modify this configuration](https://github.com/vllm-project/vllm-omni/tree/main/configuration/stage_configs.md) to let the model accept a longer batch of prompts.