From 85ec5484cde4fd5bcac1cf2d877009202aa58d06 Mon Sep 17 00:00:00 2001 From: supermario_leo Date: Tue, 26 May 2026 03:18:23 +0800 Subject: [PATCH] fix: correct 'Unsupport' typo to 'Unsupported' in error messages The error/log messages used 'Unsupport datatype', 'Unsupport input types', etc., which read as ungrammatical. Switch to 'Unsupported' across all visual/audio model files and shared utilities. Also fix 'recieved' -> 'received' in the visual websocket log line. Pure string-only change, no behavior change. --- lightllm/models/gemma3/gemma3_visual.py | 2 +- lightllm/models/internvl/internvl_visual.py | 2 +- lightllm/models/llava/llava_visual.py | 2 +- lightllm/models/qwen2_5_vl/qwen2_5_visual.py | 6 +++--- lightllm/models/qwen2_vl/qwen2_visual.py | 4 ++-- lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_audio.py | 2 +- lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_visual.py | 4 ++-- lightllm/models/qwen3_vl/qwen3_visual.py | 4 ++-- lightllm/models/qwen_vl/qwen_visual.py | 2 +- lightllm/models/tarsier2/tarsier2_visual.py | 4 ++-- lightllm/models/vit/model.py | 4 ++-- lightllm/server/config_server/api_http.py | 2 +- lightllm/utils/envs_utils.py | 2 +- lightllm/utils/torch_dtype_utils.py | 2 +- 14 files changed, 21 insertions(+), 21 deletions(-) diff --git a/lightllm/models/gemma3/gemma3_visual.py b/lightllm/models/gemma3/gemma3_visual.py index b2f7a6b779..b2cdf1ec54 100644 --- a/lightllm/models/gemma3/gemma3_visual.py +++ b/lightllm/models/gemma3/gemma3_visual.py @@ -127,7 +127,7 @@ def encode(self, images: List[ImageItem]): t = self.image_processor.preprocess(image_data, return_tensors="pt")["pixel_values"] img_tensors.append(t) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) cur_num = img_tensors[-1].shape[0] valid_ids.append([valid_id, valid_id + cur_num]) diff --git a/lightllm/models/internvl/internvl_visual.py b/lightllm/models/internvl/internvl_visual.py index 093ad2b5d1..8add1568f3 100644 --- a/lightllm/models/internvl/internvl_visual.py +++ b/lightllm/models/internvl/internvl_visual.py @@ -58,7 +58,7 @@ def encode(self, images: List[ImageItem]): t = self.load_image_func(image_data, max_num=img.extra_params["image_patch_max_num"]) img_tensors.append(t) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) cur_num = img_tensors[-1].shape[0] valid_ids.append([valid_id, valid_id + cur_num]) diff --git a/lightllm/models/llava/llava_visual.py b/lightllm/models/llava/llava_visual.py index 293bcd4450..d4310a66db 100644 --- a/lightllm/models/llava/llava_visual.py +++ b/lightllm/models/llava/llava_visual.py @@ -138,7 +138,7 @@ def encode(self, images: List[ImageItem]): t = self.image_processor.preprocess(image_data, return_tensors="pt")["pixel_values"] img_tensors.append(t) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) cur_num = img_tensors[-1].shape[0] valid_ids.append([valid_id, valid_id + cur_num]) diff --git a/lightllm/models/qwen2_5_vl/qwen2_5_visual.py b/lightllm/models/qwen2_5_vl/qwen2_5_visual.py index 7156a5ce23..1b3a5f0db7 100644 --- a/lightllm/models/qwen2_5_vl/qwen2_5_visual.py +++ b/lightllm/models/qwen2_5_vl/qwen2_5_visual.py @@ -221,7 +221,7 @@ def _init_datatype(self): elif self.data_type in ["fp32", "float32"]: self.data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {self.data_type}!") + raise ValueError(f"Unsupported datatype {self.data_type}!") return def rot_pos_emb(self, grid_thw): @@ -346,7 +346,7 @@ def load_image(self, img: List[ImageItem]): image_data = resize_image(image_data) pixel_values, image_grid_thw = self.processor.preprocess(image_data) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) return pixel_values.to(dtype=self.data_type), image_grid_thw def load_model(self, weight_dir): @@ -387,7 +387,7 @@ def encode(self, images: List[ImageItem]): img_tensors.append(pixel_values) img_grids.append(image_grid_thw) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) # must devide merge_length cur_num = img_tensors[-1].shape[0] // (self.spatial_merge_size ** 2) diff --git a/lightllm/models/qwen2_vl/qwen2_visual.py b/lightllm/models/qwen2_vl/qwen2_visual.py index 6076756043..e02c3d9aa3 100644 --- a/lightllm/models/qwen2_vl/qwen2_visual.py +++ b/lightllm/models/qwen2_vl/qwen2_visual.py @@ -235,7 +235,7 @@ def _init_datatype(self): elif self.data_type in ["fp32", "float32"]: self.data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {self.data_type}!") + raise ValueError(f"Unsupported datatype {self.data_type}!") return def load_model(self, weight_dir): @@ -319,7 +319,7 @@ def encode(self, images: List[ImageItem]): img_tensors.append(pixel_values) img_grids.append(image_grid_thw) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) # must devide merge_length cur_num = img_tensors[-1].shape[0] // (self.spatial_merge_size ** 2) diff --git a/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_audio.py b/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_audio.py index 4ad4300fc0..162999caa7 100644 --- a/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_audio.py +++ b/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_audio.py @@ -217,7 +217,7 @@ def _init_datatype(self): elif self.data_type in ["fp32", "float32"]: self.data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {self.data_type}!") + raise ValueError(f"Unsupported datatype {self.data_type}!") return def _freeze_parameters(self): diff --git a/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_visual.py b/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_visual.py index 0276724749..8fa255cf48 100644 --- a/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_visual.py +++ b/lightllm/models/qwen3_omni_moe_thinker/qwen3_omni_visual.py @@ -204,7 +204,7 @@ def _init_datatype(self): elif self.data_type in ["fp32", "float32"]: self.data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {self.data_type}!") + raise ValueError(f"Unsupported datatype {self.data_type}!") return def concat_img_embed_and_deepstack_features(self, image_embed, deepstack_feature_lists, valid_ids): @@ -388,7 +388,7 @@ def encode(self, images: List[ImageItem]): img_tensors.append(pixel_values) img_grids.append(image_grid_thw) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) # must devide merge_length cur_num = img_tensors[-1].shape[0] // (self.spatial_merge_size ** 2) diff --git a/lightllm/models/qwen3_vl/qwen3_visual.py b/lightllm/models/qwen3_vl/qwen3_visual.py index bed8898115..151ea475e5 100644 --- a/lightllm/models/qwen3_vl/qwen3_visual.py +++ b/lightllm/models/qwen3_vl/qwen3_visual.py @@ -199,7 +199,7 @@ def _init_datatype(self): elif self.data_type in ["fp32", "float32"]: self.data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {self.data_type}!") + raise ValueError(f"Unsupported datatype {self.data_type}!") return def concat_img_embed_and_deepstack_features(self, image_embed, deepstack_feature_lists, valid_ids): @@ -386,7 +386,7 @@ def encode(self, images: List[ImageItem]): img_tensors.append(pixel_values) img_grids.append(image_grid_thw) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) # must devide merge_length cur_num = img_tensors[-1].shape[0] // (self.spatial_merge_size ** 2) diff --git a/lightllm/models/qwen_vl/qwen_visual.py b/lightllm/models/qwen_vl/qwen_visual.py index 07a7412020..e12cdb5745 100644 --- a/lightllm/models/qwen_vl/qwen_visual.py +++ b/lightllm/models/qwen_vl/qwen_visual.py @@ -427,7 +427,7 @@ def encode(self, image_uuids: List): t = self.image_transform(image_data) img_tensors.append(t) else: - raise Exception("Unsupport input types: {} for {}".format(type(item), item)) + raise Exception("Unsupported input types: {} for {}".format(type(item), item)) valid_ids.append([valid_id, valid_id + 1]) valid_id += 1 diff --git a/lightllm/models/tarsier2/tarsier2_visual.py b/lightllm/models/tarsier2/tarsier2_visual.py index 9deaf08575..72ff301711 100644 --- a/lightllm/models/tarsier2/tarsier2_visual.py +++ b/lightllm/models/tarsier2/tarsier2_visual.py @@ -187,7 +187,7 @@ def __init__( projector_hidden_act, ) elif projection_head == "auto_map": - raise Exception("Unsupport projection_head auto_map") + raise Exception("Unsupported projection_head auto_map") elif projection_head is None: self.multi_modal_projector = lambda x, *args, **kwargs: x self.llm_model_type = text_config["model_type"] @@ -259,7 +259,7 @@ def encode(self, images: List[ImageItem]): img_tensors.append(pixel_values) img_grids.append(image_grid_thw) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) # must devide merge_length cur_num = img_tensors[-1].shape[0] // (self.merge_size ** 2) diff --git a/lightllm/models/vit/model.py b/lightllm/models/vit/model.py index 13f8e2827f..0befb50166 100644 --- a/lightllm/models/vit/model.py +++ b/lightllm/models/vit/model.py @@ -155,7 +155,7 @@ def _init_datatype(self): elif self.data_type in ["fp32", "float32"]: self.data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {self.data_type}!") + raise ValueError(f"Unsupported datatype {self.data_type}!") @torch.no_grad() def forward(self, pixel_values): @@ -181,7 +181,7 @@ def encode(self, images: List[ImageItem]): t = self.load_image_func(image_data, max_num=img.extra_params["image_patch_max_num"]) img_tensors.append(t) else: - raise Exception("Unsupport input types: {} for {}".format(type(img), img)) + raise Exception("Unsupported input types: {} for {}".format(type(img), img)) cur_num = img.token_num valid_ids.append([valid_id, valid_id + cur_num]) diff --git a/lightllm/server/config_server/api_http.py b/lightllm/server/config_server/api_http.py index 5c015f234c..3ce39bb6e6 100644 --- a/lightllm/server/config_server/api_http.py +++ b/lightllm/server/config_server/api_http.py @@ -81,7 +81,7 @@ async def visual_websocket_endpoint(websocket: WebSocket): client_ip, client_port = websocket.client logger.info(f"ws connected from IP: {client_ip}, Port: {client_port}") registered_visual_server_obj: VIT_Obj = pickle.loads(await websocket.receive_bytes()) - logger.info(f"recieved registered_visual_server_obj {registered_visual_server_obj}") + logger.info(f"received registered_visual_server_obj {registered_visual_server_obj}") with registered_visual_server_obj_lock: registered_visual_server_objs[registered_visual_server_obj.node_id] = registered_visual_server_obj diff --git a/lightllm/utils/envs_utils.py b/lightllm/utils/envs_utils.py index 350507e897..eb50606c20 100644 --- a/lightllm/utils/envs_utils.py +++ b/lightllm/utils/envs_utils.py @@ -59,7 +59,7 @@ def get_llm_data_type() -> torch.dtype: elif data_type in ["fp32", "float32"]: data_type = torch.float32 else: - raise ValueError(f"Unsupport datatype {data_type}!") + raise ValueError(f"Unsupported datatype {data_type}!") return data_type diff --git a/lightllm/utils/torch_dtype_utils.py b/lightllm/utils/torch_dtype_utils.py index 09372ebf91..05071e566b 100644 --- a/lightllm/utils/torch_dtype_utils.py +++ b/lightllm/utils/torch_dtype_utils.py @@ -9,4 +9,4 @@ def get_torch_dtype(data_type: str) -> torch.dtype: elif data_type in ["fp32", "float32"]: return torch.float32 else: - raise ValueError(f"Unsupport datatype {data_type}!") + raise ValueError(f"Unsupported datatype {data_type}!")